Engineering › Control and Systems Engineering

Iterative Learning Control Systems

Works Count: 38273

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Description

This cluster of papers focuses on Iterative Learning Control (ILC) and its applications in engineering practice. It covers topics such as repetitive control, model-free adaptive control, data-driven control, motion control, robotic systems, feed drive systems, batch processes, nonlinear systems, and convergence analysis.

Keywords

Iterative Learning Control; Repetitive Control; Model-Free Adaptive Control; Data-Driven Control; Motion Control; Robotic Systems; Feed Drive Systems; Batch Processes; Nonlinear Systems; Convergence Analysis

Control Systems Theory and Applications for Linear Repetitive Processes

2007-01-01

Eric Rogers , Krzysztof Gałkowski , D.H. Owens

Iterative Learning Control for Deterministic Systems

1993-01-01

Kevin L. Moore

Sliding Mode Control In Engineering

2002-01-29

Wilfrid Perruquetti , Jean-Pierre Barbot

1. Introduction: An Overview of Classical Sliding Mode Control 2. Differential Inclusions and Sliding Mode Control 3. Higher-Order Sliding Modes 4. Sliding Mode Observers 5. Dynamic Sliding Mode Control and … 1. Introduction: An Overview of Classical Sliding Mode Control 2. Differential Inclusions and Sliding Mode Control 3. Higher-Order Sliding Modes 4. Sliding Mode Observers 5. Dynamic Sliding Mode Control and Output Feedback 6. Sliding Modes, Passivity, and Flatness 7. Stability and Stabilization 8. Discretization Issues 9. Adaptive and Sliding Mode Control 10. Steady Modes in Relay Systems with Delay 11. Sliding Mode Control for Systems with Time Delay 12. Sliding Mode Control of Infinite-Dimensional Systems 13. Application of Sliding Mode Control to Robotic Systems 14. Sliding Modes Control of the Induction Motor: A Benchmark Experimental Test

Iterative Learning Control: An Expository Overview

1999-01-01

Kevin L. Moore

In this chapter we give an overview of the field of iterative learning control (ILC). We begin with a detailed description of the ILC technique, followed by two illustrative examples … In this chapter we give an overview of the field of iterative learning control (ILC). We begin with a detailed description of the ILC technique, followed by two illustrative examples that give a flavor of the nature of ILC algorithms and their performance. This is followed by a topical classification of some of the literature of ILC and a discussion of the connection between ILC and other common control paradigms, including conventional feedback control, optimal control, adaptive control, and intelligent control. Next, we give a summary of the major algorithms, results, and applications of ILC given in the literature. This discussion also considers some emerging research topics in ILC. As an example of some of the new directions in ILC theory, we present some of our recent results that show how ILC can be used to force a desired periodic motion in an initially non-repetitive process: a gas-metal arc welding system. The chapter concludes with summary comments on the past, present, and future of ILC.

Zero Phase Error Tracking Algorithm for Digital Control

1987-03-01

Masayoshi Tomizuka

A digital feedforward control algorithm for tracking desired time varying signals is presented. The feedforward controller cancels all the closed-loop poles and cancellable closed-loop zeros. For uncancellable zeros, which include … A digital feedforward control algorithm for tracking desired time varying signals is presented. The feedforward controller cancels all the closed-loop poles and cancellable closed-loop zeros. For uncancellable zeros, which include zeros outside the unit circle, the feedforward controller cancels the phase shift induced by them. The phase cancellation assures that the frequency response between the desired output and actual output exhibits zero phase shift for all the frequencies. The algorithm is particularly suited to the general motion control problems including robotic arms and positioning tables. A typical motion control problem is used to show the effectiveness of the proposed feedforward controller.

High speed CNC system design. Part I: jerk limited trajectory generation and quintic spline interpolation

2001-07-01

Kaan Erkorkmaz , Yusuf Altintaş

Iterative learning control synthesis based on 2-D system theory

1993-01-01

J. E. Kurek , Marek B. Zaremba

An algorithm is presented for iterative learning of the control input for a linear discrete-time multivariable system. Necessary and sufficient conditions are stated for convergence of the proposed algorithm. The … An algorithm is presented for iterative learning of the control input for a linear discrete-time multivariable system. Necessary and sufficient conditions are stated for convergence of the proposed algorithm. The algorithm synthesis and analysis are based on two-dimensional (2-D) system theory. A numerical example is given.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>

Adaptive Prescribed Performance Motion Control of Servo Mechanisms with Friction Compensation

2013-01-16

Jing Na , Qiang Chen , Xuemei Ren +1 more

This paper proposes an adaptive control for a class of nonlinear mechanisms with guaranteed transient and steady-state performance. A performance function characterizing the convergence rate, maximum overshoot, and steady-state error … This paper proposes an adaptive control for a class of nonlinear mechanisms with guaranteed transient and steady-state performance. A performance function characterizing the convergence rate, maximum overshoot, and steady-state error is used for the output error transformation, such that stabilizing the transformed system is sufficient to achieve the tracking control of the original system with a priori prescribed performance. A continuously differentiable friction model is adopted to account for the friction nonlinearities, for which primary model parameters are online updated. A novel high-order neural network with only a scalar weight is developed to approximate unknown nonlinearities and to dramatically diminish the computational costs. Comparative experiments on a turntable servo system are included to verify the reliability and effectiveness.

Adaptive algorithms for the rejection of sinusoidal disturbances with unknown frequency

1997-12-01

Marc Bodson , S.C. Douglas

The Application of Model-Referenced Adaptive Control to Robotic Manipulators

1979-09-01

Steven Dubowsky , Daniel Desforges

The achievement of quality dynamic performance in manipulator systems is difficult using conventional control methods because of both the inherent geometric nonlinearities of these systems and the dependence of the … The achievement of quality dynamic performance in manipulator systems is difficult using conventional control methods because of both the inherent geometric nonlinearities of these systems and the dependence of the system dynamics on the characteristics of manipulated objects. A model-referenced adaptive control law is developed for maintaining uniformly good performance over a wide range of motions and payloads. The effectiveness of the approach is demonstrated in several simulations and the system stability as a function of input is investigated. Also developed is a “learning signal” approach designed to minimize initial transients arising from abrupt changes in the inertial payload.

Adaptive friction compensation with partially known dynamic friction model

1997-02-01

Carlos Canudas de Wit , P. Lischinsky

This paper illustrates the application of a model-based adaptive friction compensation on a DC motor servomechanism. The dynamic friction model and the control structure studied previously by the authors were … This paper illustrates the application of a model-based adaptive friction compensation on a DC motor servomechanism. The dynamic friction model and the control structure studied previously by the authors were used as a basis for this study. The paper first proposes a two-step off-line method to estimate the nominal static and dynamic parameters associated with the model. Then two adaptive globally stable mechanisms are introduced to deal with structured normal forces and temperature variations. Assuming that a nominal friction model is known and that the friction variations can be suitably structured, adaptation is performed on the basis of only one parameter. The paper presents experimental results validating the identification of the dynamic friction model and the adaptive control scheme. These results show that the adaptive loop improves over a fixed compensation scheme and over a PID controller without friction compensation. © 1997 by John Wiley & Sons, Ltd.

Iterative learning control and repetitive control for engineering practice

2000-01-01

Richard W. Longman

This paper discusses linear iterative learning and repetitive control, presenting general purpose control laws with only a few parameters to tune. The method of tuning them is straightforward, making tuning … This paper discusses linear iterative learning and repetitive control, presenting general purpose control laws with only a few parameters to tune. The method of tuning them is straightforward, making tuning easy for the practicing control engineer. The approach can then serve the same function for learning/repetitive control, as PID controllers do in classical control. Anytime one has a controller that is to perform the same tacking command repeatedly, one simply uses such a law to adjust the command given to an existing feedback controller and achieves a substantial decrease in tracking error. Experiments with the method show that decreases by a factor between 100 and 1000 in the RMS tracking error on a commercial robot, performing a high speed trajectory can easily be obtained in 8 to 12 trials for learning. It is shown that in engineering practice, the same design criteria apply to learning control as apply to repetitive control. Although the conditions for stability are very different for the two problems, one must impose a good transient condition, and once such a condition is formulated, it is likely to be the same for both learning and repetitive control.

Variable-Gain Cross-Coupling Controller for Contouring

1991-01-01

Yoram Koren , Ch.-Ch. Lo

On a nonlinear multivariable servomechanism problem

1990-11-01

Jie Huang , Wilson J. Rugh

A survey of iterative learning control

2006-06-01

Douglas A. Bristow , Marina Tharayil , Andrew G. Alleyne

This article surveyed the major results in iterative learning control (ILC) analysis and design over the past two decades. Problems in stability, performance, learning transient behavior, and robustness were discussed … This article surveyed the major results in iterative learning control (ILC) analysis and design over the past two decades. Problems in stability, performance, learning transient behavior, and robustness were discussed along with four design techniques that have emerged as among the most popular. The content of this survey was selected to provide the reader with a broad perspective of the important ideas, potential, and limitations of ILC. Indeed, the maturing field of ILC includes many results and learning algorithms beyond the scope of this survey. Though beginning its third decade of active research, the field of ILC shows no sign of slowing down.

Model-based iterative learning control with a quadratic criterion for time-varying linear systems

2000-05-01

Jay H. Lee , Kwang‐Sik Lee , Won C. Kim

Iterative learning control for discrete-time systems with exponential rate of convergence

1996-03-01

N. Amann , D.H. Owens , Eric Rogers

An algorithm for iterative learning control is proposed based on an optimisation principle used by other authors to derive gradient-type algorithms. The new algorithm is a descent algorithm and has … An algorithm for iterative learning control is proposed based on an optimisation principle used by other authors to derive gradient-type algorithms. The new algorithm is a descent algorithm and has potential benefits which include realisation in terms of Riccati feedback and feedforward components. This realisation also has the advantage of implicitly ensuring automatic step-size selection and hence guaranteeing convergence without the need for empirical choice of parameters. The algorithm achieves a geometric rate of convergence for invertible plants. One important feature of the proposed algorithm is the dependence of the speed of convergence on weight parameters appearing in the norms of the signals chosen for the optimisation problem.

Data-Driven Model-Free Adaptive Control for a Class of MIMO Nonlinear Discrete-Time Systems

2011-12-01

Zhongsheng Hou , Shangtai Jin

In this paper, a data-driven model-free adaptive control (MFAC) approach is proposed based on a new dynamic linearization technique (DLT) with a novel concept called pseudo-partial derivative for a class … In this paper, a data-driven model-free adaptive control (MFAC) approach is proposed based on a new dynamic linearization technique (DLT) with a novel concept called pseudo-partial derivative for a class of general multiple-input and multiple-output nonlinear discrete-time systems. The DLT includes compact form dynamic linearization, partial form dynamic linearization, and full form dynamic linearization. The main feature of the approach is that the controller design depends only on the measured input/output data of the controlled plant. Analysis and extensive simulations have shown that MFAC guarantees the bounded-input bounded-output stability and the tracking error convergence.

Robust motion controller design for high-accuracy positioning systems

1996-01-01

Hoseong Lee , Masayoshi Tomizuka

This paper presents a controller structure for robust high speed and accuracy motion control systems. The overall control system consists of four elements: a friction compensator; a disturbance observer for … This paper presents a controller structure for robust high speed and accuracy motion control systems. The overall control system consists of four elements: a friction compensator; a disturbance observer for the velocity loop; a position loop feedback controller; and a feedforward controller acting on the desired output. A parameter estimation technique coupled with friction compensation is used as the first step in the design process. The friction compensator is based on the experimental friction model and it compensates for unmodeled nonlinear friction. Stability of the closed-loop is provided by the feedback controller. The robust feedback controller based on the disturbance observer compensates for external disturbances and plant uncertainties. Precise tracking is achieved by the zero phase error tracking controller. Experimental results are presented to demonstrate performance improvement obtained by each element in the proposed robust control structure.

Analysis and Synthesis of Discrete-Time Repetitive Controllers

1989-09-01

Masayoshi Tomizuka , Tsu‐Chin Tsao , Kok-Kia Chew

Repetitive control is formulated and analyzed in the discrete-time domain. Sufficiency conditions for the asymptotic convergence of a class of repetitive controllers are given. The “plug-in” repetitive controller is introduced … Repetitive control is formulated and analyzed in the discrete-time domain. Sufficiency conditions for the asymptotic convergence of a class of repetitive controllers are given. The “plug-in” repetitive controller is introduced and applied to track-following in a disk-file actuator system. Inter-sample ripples in the tracking error were present when the “plug-in” repetitive controller was installed. The performance is enhanced, however, when the zero-holding device is followed by a low-pass filter or replaced by a delayed first-order hold.

Adaptive Robust Control of DC Motors With Extended State Observer

2013-09-09

Jianyong Yao , Zongxia Jiao , Dawei Ma

Structured and unstructured uncertainties always exist in physical servo systems and degrade their tracking accuracy. In this paper, a practical method named adaptive robust control with extended state observer (ESO) … Structured and unstructured uncertainties always exist in physical servo systems and degrade their tracking accuracy. In this paper, a practical method named adaptive robust control with extended state observer (ESO) is synthesized for high-accuracy motion control of a dc motor. The proposed controller accounts for not only the structured uncertainties (i.e., parametric uncertainties) but also the unstructured uncertainties (i.e., nonlinear friction, external disturbances, and/or unmodeled dynamics). Adaptive control for the structured uncertainty and ESO for the unstructured uncertainty are designed for compensating them respectively and integrated together via a feedforward cancellation technique. The global robustness of the controller is guaranteed by a feedback robust law. Furthermore, the controller theoretically guarantees a prescribed tracking performance in the presence of various uncertainties, which is very important for high-accuracy control of motion systems. Extensive comparative experimental results are obtained to verify the high-performance nature of the proposed control strategy.

Direct repetitive control of SPWM inverter for UPS purpose

2003-05-01

Kai Zhang , Yong Kang , Jian Xiong +1 more

A novel repetitive controller directly combined with an open loop SPWM inverter is presented in this paper. To cope with the high-resonant peak of the open loop inverter that may … A novel repetitive controller directly combined with an open loop SPWM inverter is presented in this paper. To cope with the high-resonant peak of the open loop inverter that may cause instability, a zero-phase-shift notch filter other than the inverse transfer function of the inverter or a conventional second-order filter is incorporated in the controller. The proposed method has good harmonic rejection and large tolerance to parameter variations. To further reduce the steady-state error, a low-pass-filter Q(z) algorithm is applied. The DC bias problem is also taken into consideration and solved with the repetitive controller itself. The method is implemented with a digital signal processor and achieves low THD% (1.4%-1.7%) with nonlinear loads and fast error convergence (3-5 fundamental periods). It proves to be a cost-effective solution for common UPS products where high-quality output voltage is more stressed than fast dynamic response.

New integration algorithms for estimating motor flux over a wide speed range

1998-09-01

Jun Hu , Bin Wu

Three new integration algorithms for motor flux estimation are proposed in this paper. These algorithms are developed for use in high-performance sensorless AC motor drives. The first algorithm is used … Three new integration algorithms for motor flux estimation are proposed in this paper. These algorithms are developed for use in high-performance sensorless AC motor drives. The first algorithm is used to elaborate the basic operating principle. The second one is designed for the drives that require a constant air-gap flux during operation. The third algorithm, in which an adaptive controller is used, can have wide industrial applications. The proposed algorithms can effectively solve the problems associated with pure integrators. These algorithms can be used to accurately measure the motor flux including its magnitude and phase angle over a wide speed range (1:100). The provenance of the algorithms is investigated, compared, and verified experimentally.

Stabilization of a mini rotorcraft with four rotors

2005-12-01

P. Castillo , Rogelio Lozano , Alejandro Dzul

Multilayer neural-net robot controller with guaranteed tracking performance

1996-03-01

Frank L. Lewis , Aydın Yeşildirek , Kai Liu

A multilayer neural-net (NN) controller for a general serial-link rigid robot arm is developed. The structure of the NN controller is derived using a filtered error/passivity approach. No off-line learning … A multilayer neural-net (NN) controller for a general serial-link rigid robot arm is developed. The structure of the NN controller is derived using a filtered error/passivity approach. No off-line learning phase is needed for the proposed NN controller and the weights are easily initialized. The nonlinear nature of the NN, plus NN functional reconstruction inaccuracies and robot disturbances, mean that the standard delta rule using backpropagation tuning does not suffice for closed-loop dynamic control. Novel online weight tuning algorithms, including correction terms to the delta rule plus an added robust signal, guarantee bounded tracking errors as well as bounded NN weights. Specific bounds are determined, and the tracking error bound can be made arbitrarily small by increasing a certain feedback gain. The correction terms involve a second-order forward-propagated wave in the backpropagation network. New NN properties including the notions of a passive NN, a dissipative NN, and a robust NN are introduced.

Application of a General Learning Algorithm to the Control of Robotic Manipulators

1987-06-01

Wallace T. Miller , Filson H. Glanz , L.G. Kraft

In this paper, we discuss the use of a general learning algo rithm for the dynamic control of robot manipulators. Unlike some other learning control schemes, learning is based solely … In this paper, we discuss the use of a general learning algo rithm for the dynamic control of robot manipulators. Unlike some other learning control schemes, learning is based solely on observations of the input-output relationship of the system being controlled and is independent of control objectives. Information learned previously can be applied to new control objectives as long as similar regions of the system state space are involved. The control scheme requires no a priori knowl edge of the robot dynamics and is easy to apply to a particu lar control problem or to modify to accommodate changes in the physical system. The control scheme is computationally efficient and well suited to fixed-point implementation. The learning controller is evaluated in a series of computer simu lations involving a two-axis-articulated robot arm during simulated repetitive and nonrepetitive movements. We inves tigate the effects of varying learning algorithm parameters as well as control system performance in the presence of obser vation noise and changing manipulator payloads. The learn ing control system presented promises to provide good dy namic performance in complex situations at a reasonable cost as measured in terms of both hardware and software devel opment.

Disturbance observer and feedforward design for a high-speed direct-drive positioning table

1999-01-01

Carl J. Kempf , S. Kobayashi

Design and implementation of a discrete-time tracking controller for a precision positioning table actuated by direct-drive motors is considered. The table has acceleration capabilities in excess of 5 G, positioning … Design and implementation of a discrete-time tracking controller for a precision positioning table actuated by direct-drive motors is considered. The table has acceleration capabilities in excess of 5 G, positioning accuracy at the micron level, and is used in applications such as semiconductor packaging. The controller proposed uses a disturbance observer and proportional derivative (PD) compensation in the feedback path and a zero phase error tracking controller and zero phase low-pass filter in the feedforward path. The existing disturbance observer design techniques are extended to account for time delay in the plant. Practical difficulties with excessive feedforward gains are examined and a low-order filter design method is proposed. Experimental results for quantized low-order position reference trajectories, which are commonly used in industrial systems, demonstrate the effectiveness of the approach.

L2-Gain and Passivity Techniques in Nonlinear Control

2016-12-04

Arjan van der Schaft

This standard text gives a unified treatment of passivity and L2-gain theory for nonlinear state space systems, preceded by a compact treatment of classical passivity and small-gain theorems for nonli This standard text gives a unified treatment of passivity and L2-gain theory for nonlinear state space systems, preceded by a compact treatment of classical passivity and small-gain theorems for nonli

On the iterative learning control theory for robotic manipulators

1988-01-01

P. Bondi , Giuseppe Casalino , Luca Maria Gambardella

An iterative learning technique is applied to robot manipulators, using an inherently nonlinear analysis of the learning procedure. In particularly, a 'high-gain feedback' point of view is utilized to prove … An iterative learning technique is applied to robot manipulators, using an inherently nonlinear analysis of the learning procedure. In particularly, a 'high-gain feedback' point of view is utilized to prove the possibility of setting up uniform upper bounds to the trajectory errors occurring at each trial. The subsequent analysis of convergence shows that apart from minor conditions, the existence of a finite (but not necessarily narrow) bound on the trajectory deviations can substantially suffice to guarantee the zeroing of the errors after a sufficient number of trials. This in turn leaves open the possibility of obtained the exact tracking of the desired motion, even in the presence of moderate values assigned to the feedback gains.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>

Bettering operation of Robots by learning

1984-06-01

Suguru Arimoto , Sadao Kawamura , Fumio Miyazaki

Abstract This article proposes a betterment process for the operation of a mechanical robot in a sense that it betters the next operation of a robot by using the previous … Abstract This article proposes a betterment process for the operation of a mechanical robot in a sense that it betters the next operation of a robot by using the previous operation's data. The process has an iterative learning structure such that the ( k + 1)th input to joint actuators consists of the k th input plus an error increment composed of the derivative difference between the k th motion trajectory and the given desired motion trajectory. The convergence of the process to the desired motion trajectory is assured under some reasonable conditions. Numerical results by computer simulation are presented to show the effectiveness of the proposed learning scheme.

A survey on iterative learning control for nonlinear systems

2011-06-16

Jian‐Xin Xu

In this article we review the recent advances in iterative learning control (ILC) for nonlinear dynamic systems. In the research field of ILC, two categories of system nonlinearities are considered, … In this article we review the recent advances in iterative learning control (ILC) for nonlinear dynamic systems. In the research field of ILC, two categories of system nonlinearities are considered, namely, the global Lipschitz continuous (GLC) functions and local Lipschitz continuous (LLC) functions. ILC for GLC systems is widely studied and analysed using contraction mapping approach, and the focus of recent exploration moves to application problems, though a number of theoretical issues remain open. ILC for LLC systems is currently a hot area and the recent research focuses on ILC design and analysis by means of Lyapunov approach. The objectives of this article are to introduce recent development and advances in nonlinear ILC schemes, highlight their effectiveness and limitations, as well as discuss the directions for further exploration of nonlinear ILC.

Tracking control of non-linear systems using sliding surfaces, with application to robot manipulators†

1983-08-01

J.-J.E. Slotine , Shankar Sastry

Abstract A methodology of feedback control is developed to achieve accurate tracking in a. class of non-linear, time-varying systems in the presence of disturbances and para meter variations. The methodology … Abstract A methodology of feedback control is developed to achieve accurate tracking in a. class of non-linear, time-varying systems in the presence of disturbances and para meter variations. The methodology uses in its idealized form piecewise continuous feedback control, resulting in the state trajectory sliding along a time-varying sliding surface in the state space. This idealized control law achieves perfect tracking; however, non-idealities in its implementation result in the generation of an undesirable high-frequency component in the state trajectory. To rectify this, it is shown how continuous control laws may be used to approximate the discontinuous control law to obtain robust tracking to within a prescribed accuracy without generating undesirable high-frequency signal. The method is applied to the control of a two-link manipulator handling variable loads in a flexible manufacturing system environment. Notes Research supported in part by the AFOSR under grant 82-0258 and by the ONR under N00014-82-K-0582 (NR-606-003)

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Practical Nonsingular Terminal Sliding-Mode Control of Robot Manipulators for High-Accuracy Tracking Control

2009-06-10

Maolin Jin , Jinoh Lee , Pyung Hun Chang +1 more

This paper presents a practical nonsingular terminal sliding-mode (TSM) tracking control design for robot manipulators using time-delay estimation (TDE). The proposed control assures fast convergence due to the nonlinear TSM, … This paper presents a practical nonsingular terminal sliding-mode (TSM) tracking control design for robot manipulators using time-delay estimation (TDE). The proposed control assures fast convergence due to the nonlinear TSM, and requires no prior knowledge about the robot dynamics due to the TDE. Despite its model-free nature, the proposed control provides high-accuracy control and robustness against parameters variations. The simplicity, robustness, and fast convergence of the proposed control are verified through both 2-DOF planar robot simulations and 3-DOF PUMA-type robot experiments.

Iterative Learning Control: Brief Survey and Categorization

2007-10-23

Hyo‐Sung Ahn , YangQuan Chen , Kevin L. Moore

In this paper, the iterative learning control (ILC) literature published between 1998 and 2004 is categorized and discussed, extending the earlier reviews presented by two of the authors. The papers … In this paper, the iterative learning control (ILC) literature published between 1998 and 2004 is categorized and discussed, extending the earlier reviews presented by two of the authors. The papers includes a general introduction to ILC and a technical description of the methodology. The selected results are reviewed, and the ILC literature is categorized into subcategories within the broader division of application-focused and theory-focused results.

Bounded error adaptive control

1982-12-01

B. Peterson , Kumpati S. Narendra

The paper discusses the adaptive control of a linear time-invariant plant when the measurement of the plant output is corrupted by a bounded disturbance. The principal contribution is the demonstration … The paper discusses the adaptive control of a linear time-invariant plant when the measurement of the plant output is corrupted by a bounded disturbance. The principal contribution is the demonstration of the boundedness of all the signals of the overall system using a nonlinear adaptive law involving a dead zone. A statement of the prior information needed to determine the adaptive algorithm as well as a discussion of the limitations of the scheme are given. Computer simulations are presented to illustrate the effect of various parameters.

A nonlinear integrator for servomechanisms

1958-03-01

J. C. Clegg

INTEGRATION in the forward part of a servomechanism loop has long been known to reduce steady-state errors. With one perfect integrator, there will be no steady-state error following a simple … INTEGRATION in the forward part of a servomechanism loop has long been known to reduce steady-state errors. With one perfect integrator, there will be no steady-state error following a simple step-function input; with two tandem integrators there will be no steady-state error due to a ramp input, etc. The major drawback to the linear integrator is the time delay involved. Each linear integrator introduces 90 degrees of phase lag at all frequencies, and so it takes only two integrators to make a basically unstable system. A nonlinear integrator is to be described which is superior in this respect to a linear type.

Repetitive control system: a new type servo system for periodic exogenous signals

1988-07-01

Shinji Hara , Yutaka Yamamoto , Tohru OMATA +1 more

A control scheme called repetitive control is proposed, in which the controlled variables follow periodic reference commands. A high-accuracy asymptotic tracking property is achieved by implementing a model that generates … A control scheme called repetitive control is proposed, in which the controlled variables follow periodic reference commands. A high-accuracy asymptotic tracking property is achieved by implementing a model that generates the periodic signals of period L into the closed-loop system. Sufficient conditions for the stability of repetitive control systems and modified repetitive control systems are derived by applying the small-gain theorem and the stability theorem for time-lag systems. Synthesis algorithms are presented by both the state-space approach and the factorization approach. In the former approach, the technique of the Kalman filter and perfect regulation is utilized, while coprime factorization over the matrix ring of proper stable rational functions and the solution of the Hankel norm approximation are used in the latter one.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>

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Survey on iterative learning control, repetitive control, and run-to-run control

2009-10-15

Youqing Wang , Furong Gao , Francis J. Doyle

Adaptive iterative learning control for robot manipulators

2004-04-10

Abdelhamid Tayebi

An Overview of Dynamic-Linearization-Based Data-Driven Control and Applications

2016-12-06

Zhongsheng Hou , Ronghu Chi , Huijun Gao

A brief overview on the model-based control and data-driven control methods is presented. The data-driven equivalent dynamic linearization, as a foundational analysis tool of data-driven control methods for discrete-time nonlinear … A brief overview on the model-based control and data-driven control methods is presented. The data-driven equivalent dynamic linearization, as a foundational analysis tool of data-driven control methods for discrete-time nonlinear systems, is introduced in detail with motivations and distinct features. The prototype model-free adaptive control schemes by using the dynamic linearization to an unknown nonlinear plant model, as well as the alternative model-free adaptive control methods by using the dynamic linearization to an unknown ideal nonlinear controller, are discussed. Furthermore, the extensions of the dynamic linearization to unknown nonlinear repetitive systems and the corresponding model-free adaptive iterative learning control methods are also overviewed and summarized. This work highlights the characteristics and comments of the different model-free adaptive control schemes in detail to facilitate the understanding of the readers. Finally, some perspectives on data-driven control methods in information-rich age are given.

Semi-global nonlinear output regulation with adaptive internal model

2001-01-01

Andrea Serrani , Alberto Isidori , Lorenzo Marconi

We address the problem of output regulation for nonlinear systems driven by a linear, neutrally stable exosystem whose frequencies are not known a priori. We present a classical solution in … We address the problem of output regulation for nonlinear systems driven by a linear, neutrally stable exosystem whose frequencies are not known a priori. We present a classical solution in terms of the parallel connection of a robust stabilizer and an internal model, where the latter is adaptively tuned to the device that reproduces the steady-state control necessary to maintain the output-zeroing condition. We obtain robust regulation (i.e. in presence of parameter uncertainties) with a semi-global domain of convergence for a significant class of nonlinear minimum-phase system.

Iterative Learning Control

1998-01-01

Zeungnam Bien , Jian‐Xin Xu

On Model-Free Adaptive Control and Its Stability Analysis

2019-01-22

Zhongsheng Hou , Shuangshuang Xiong

In this paper, the main issues of model-based control methods are first reviewed, followed by the motivations and the state of the art of the model-free adaptive control (MFAC). MFAC … In this paper, the main issues of model-based control methods are first reviewed, followed by the motivations and the state of the art of the model-free adaptive control (MFAC). MFAC is a novel data-driven control method for a class of unknown nonaffine nonlinear discrete-time systems since neither explicit physical model nor Lyapunov stability theory or key technical lemma is used in the controller design and theoretical analysis except only for the input/output (I/O) measurement data. The basis of MFAC is the dynamic linearization data modeling method at each operating point of the closed-loop system. The established dynamic linearization data model is a virtual equivalent data relationship in the I/O sense to the original nonlinear plant by means of a novel concept called pseudo-partial derivative (PPD) or pseudo-gradient (PG) vector. Based on this virtual equivalent dynamic linearization data model and the time-varying PPD or PG estimation algorithm designed merely using the I/O measurements of a controlled plant, the MFAC system is constructed. The main contribution of this paper is that the theoretical analysis of the bounded-input bounded-output stability, the monotonic convergence of the tracking error dynamics, and the internal stability of the full form dynamic linearization based MFAC scheme are rigorously presented by the contraction mapping principle; the well known PID control and the traditional adaptive control for linear time-invariant systems are explicitly shown as the special cases of this MFAC. The simulation results verify the effectiveness of the proposed approach.

L2 - Gain and Passivity Techniques in Nonlinear Control

2000-01-01

Arjan van der Schaft

Linear and Nonlinear Iterative Learning Control

2003-01-01

Jian‐Xin Xu , Ying Tan

Autogeneration and optimization of pick-and-place trajectories in robotic systems: A data-driven approach

2025-06-24

Mingkun Wu , Alisa Rupenyan , Burkhard Corves | Robotics and Computer-Integrated Manufacturing

A Data-Driven Iterative Feedforward Tuning Strategy with a Variable-Gain Feedback Controller for Linear Servo Systems

2025-06-23

Jiaqian Fu , Shanhu Li | Energies

Iterative feedforward tuning (IFFT) compensates for the dynamic tracking error in linear servo systems caused by reference trajectory and nonlinear friction. The feedback controller with infinite DC gain makes the … Iterative feedforward tuning (IFFT) compensates for the dynamic tracking error in linear servo systems caused by reference trajectory and nonlinear friction. The feedback controller with infinite DC gain makes the steady-state tracking error zero. This paper analyzes the effect of the DC gain of the feedback controller on IFFT and proposes an IFFT strategy with a variable-gain feedback controller. This strategy makes the dynamic tracking error due to Coulomb friction behave as a continuous and easy-to-construct window function, which makes the feedforward basis function vector consistent with the dimensionality of the dynamic tracking error. This strategy improves both the efficiency and accuracy of IFFT compared to IFFT using a fixed-gain feedback controller. The dynamic tracking error is compensated to the maximum extent possible, and the steady-state tracking error is zero. Theoretical verification and experimental results indicate the excellent iterative efficiency and accuracy of IFFT with a variable-gain feedback controller.

Spatial-terminal iterative learning control for registration error elimination in roll-to-roll gravure printing systems

2025-06-23

Zhengkai WANG , Jingyang Yan , Rui Ma +2 more | Journal of Manufacturing Processes

Dynamic Error Modeling and Predictive Compensation for Direct-Drive Turntables Based on CEEMDAN-TPE-LightGBM-APC Algorithm

2025-06-22

Manzhi Yang , Hao Ren , Shijia Liu +4 more | Micromachines

The direct-drive turntable serves as the core actuator in high-precision macro-micro drive systems, where its positioning accuracy fundamentally determines overall system performance. Accurate error prediction and compensation technology represent a … The direct-drive turntable serves as the core actuator in high-precision macro-micro drive systems, where its positioning accuracy fundamentally determines overall system performance. Accurate error prediction and compensation technology represent a critical prerequisite for achieving continuous error compensation and predictive control in direct-drive turntables, making research on positioning error modeling, prediction, and compensation of vital importance. This study presents a dynamic continuous error compensation model for direct-drive turntables, based on an analysis of positioning error mechanisms and the implementation of a “decomposition-modeling-integration-correction” strategy, which features high flexibility, adaptability, and online prediction-correction capabilities. Our methodology comprises four key stages: Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN)-based decomposition of historical error data, development of component-specific prediction models using Tree-structured Parzen Estimator (TPE)-optimized Light Gradient Boosting Machine (LightGBM) algorithms for each Intrinsic Mode Function (IMF), integration of component predictions to generate initial values, and application of the Adaptive Prediction Correction (APC) module to produce final predictions. Validation results demonstrate substantial performance improvements, with compensated positioning error ranges reduced from [−31.83″, 41.59″] to [−15.09″, 12.07″] (test set) and from [−22.50″, 9.15″] to [−8.15″, 8.56″] (extrapolation test set), corresponding to standard deviation reductions of 71.2% and 61.6%, respectively. These findings conclusively establish the method’s effectiveness in significantly enhancing accuracy while maintaining prediction stability and operational efficiency, underscoring its considerable theoretical and practical value for error compensation in precision mechanical systems.

Ultra-Local Model-Based Adaptive Enhanced Model-Free Control for PMSM Speed Regulation

2025-06-21

Chunlei Hua , Difen Shi , Xi Chen +1 more | Machines

Conventional model-free control (MFC) is widely used in motor drives due to its simplicity and model independence, yet its performance suffers from imperfect disturbance estimation and input gain mismatch. To … Conventional model-free control (MFC) is widely used in motor drives due to its simplicity and model independence, yet its performance suffers from imperfect disturbance estimation and input gain mismatch. To address these issues, this paper proposes an adaptive enhanced model-free speed control (AEMFSC) scheme based on an ultra-local model for permanent magnet synchronous motor (PMSM) drives. First, by integrating a nonlinear disturbance observer (NDOB) and a PD control law into the generalized model-free controller, an enhanced model-free speed controller (EMFSC) was developed to ensure closed-loop stability. Compared with a conventional MFSC, the proposed method eliminated steady-state errors, reduced the speed overshoot, and achieved faster settling with improved disturbance rejection. Second, to address the performance degradation induced by input gain α mismatch during time-varying load conditions, we developed an online parameter identification method for real-time α estimation. This adaptive mechanism enabled automatic controller parameter adjustment, which significantly enhanced the transient tracking performance of the PMSM drive. Furthermore, an algebraic-framework-based high-precision identification technique is proposed to optimize the initial α selection, which effectively reduces the parameter tuning effort. Simulation and experimental results demonstrated that the proposed AEMFSC significantly enhanced the PMSM’s robustness against load torque variations and parameter uncertainties.

Anti-pitching of high-speed multihull ship based on fast predictive control and iterative learning control

2025-06-21

Zheng‐Ming Huang , Jun Zhang , Weidong Xu +1 more | Ocean Engineering

Dual-variable iterative learning control for switched systems with iteration experience succession strategy

2025-06-19

Yiwen Qi , C.-Y. Yao , Choon Ki Ahn +2 more | Automatica

Robust tracking control for fast steering mirror based on iterative learning enhanced 2-DOF disturbance observer

2025-06-18

Wen Wang , Bowen Chen , Rui Xu +1 more | Sensors and Actuators A Physical

Iterative Learning Control for Distributed Parameter Systems with Sensor/Actuator Networks Based on High-Order Internal Mode

2025-06-18

Jianxiang Zhang , Min Mao | Journal of Control Automation and Electrical Systems

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2025-06-18

Lakshmi Mandal , Shalabh Bhatnagar | Automatica

A Decentralized Optimal Iterative Learning Control Approach With Efficient Computation for Collaborative Tracking

2025-06-17

Luyuan Gao , Zhihe Zhuang , Hongfeng Tao +3 more | International Journal of Robust and Nonlinear Control

ABSTRACT In practical industries, multiple subsystems are often required to collaborate on a particular repetitive collaborative tracking task, taking a lot of computation. Norm optimal iterative learning control (NOILC) can … ABSTRACT In practical industries, multiple subsystems are often required to collaborate on a particular repetitive collaborative tracking task, taking a lot of computation. Norm optimal iterative learning control (NOILC) can effectively improve the tracking accuracy for such tasks, and also provide the monotonic convergence of tracking error. However, the high‐dimensional matrices and supervectors generated by the lifting technique lead to a computationally expensive problem in the lifted NOILC approach, making it difficult to apply to the collaborative tracking task with a long trial length. In order to achieve efficient computation, this paper proposes a novel non‐lifted NOILC (N‐NOILC) approach for collaborative tracking, with only linear computational complexity regarding the trial length. Exploiting the decomposability of the designed performance criterion, the N‐NOILC optimization problem is reformulated as a “sharing” problem, and the alternating direction method of multipliers (ADMM) is introduced for its decentralized solution. Theoretical analysis shows that the proposed algorithm makes the error converge monotonically to zero under the corresponding convergence conditions. Its relevant parameter tuning guidelines are also provided. Finally, the effectiveness of the proposed decentralized N‐NOILC approach is verified by numerical simulation.

Adaptive fuzzy iterative learning fault‐tolerant control for uncertain nonstrict feedback systems

2025-06-17

Ning Sheng , Hanxue Cui , Yang Liu +1 more | Asian Journal of Control

Abstract Considering the main challenges of nonrepetitive initial conditions and the actuator faults, this article proposes an adaptive iterative learning fault‐tolerant control (AILFTC) for high‐order nonstrict feedback nonlinear systems. The … Abstract Considering the main challenges of nonrepetitive initial conditions and the actuator faults, this article proposes an adaptive iterative learning fault‐tolerant control (AILFTC) for high‐order nonstrict feedback nonlinear systems. The actuator faults are compensated by designing an iterative updating law to estimate its effective factor. Although the initial values are different for each iteration, an error tracking algorithm is proposed to ensure that the output converges to the desired trajectory within the initial time interval. By introducing fuzzy logic systems (FLSs) to address the strong nonlinearity of the system and further utilizing the Gaussian function property of the FLS, the nonstrict feedback problem of the system is solved. Stability and convergence are demonstrated by the proposed AILFTC through the design of a composite energy function. Simulation study verifies the results.

Set-to-set iterative learning control

2025-06-17

Reid D. Smith , Andrew G. Alleyne | Automatica

Adaptive friction compensation for synchronous force control of dual-servo riveting systems with high-energy nonlinear disturbance

2025-06-17

Sun Zhichao , Gongping Liu , Guoqing Cai +3 more | Research Square (Research Square)

<title>Abstract</title> In the aircraft industry, dual-servo riveting systems (DSRSs) face significant challenges in achieving high-performance synchronous force control due to nonlinear time-varying contact dynamics and complex friction disturbances. This paper … <title>Abstract</title> In the aircraft industry, dual-servo riveting systems (DSRSs) face significant challenges in achieving high-performance synchronous force control due to nonlinear time-varying contact dynamics and complex friction disturbances. This paper proposes a novel synchronous force control architecture that integrates adaptive friction compensation (SFCwF) with nonlinear disturbance rejection to address these challenges. For the high-energy nonlinear loads generated during riveting process, the distributed friction characteristics of the DSRS ball screw powertrain are analyzed using Hertz contact theory, and a parametric friction model is subsequently established. To address parameter perturbations in the friction model induced by nonlinear loads, a dual-observer structure is designed based on the LuGre model to manage parametric uncertainties. Furthermore, a nonlinear disturbance observer (NDOB) is designed to mitigate unknown disturbances without requiring acceleration measurements. The Lyapunov theory analysis demonstrates that the proposed control approach guarantees asymptotic stability of the closed-loop system, with both tracking and synchronization errors converging to zero, even in the presence of parametric uncertainties. Experimental validations on a custom-designed DSRS platform indicate that the proposed strategy achieves not only superior synchronous force control performance but also consistent riveting quality, with deviations of ±0.06 mm in driven head height, ±0.075 mm in driven head diameter, and a sheet waviness of ±0.116mm, all of which significantly exceed acceptable quality thresholds.

Tool center point acceleration feedback controller design for vibration suppression

2025-06-16

Xiaoke Wang , Linus Geiser , Ryan Wüest +2 more | International Journal of Dynamics and Control

Finite-time composite learning trajectory tracking control of USVs with prescribed performance

2025-06-15

Mingxuan Yang , Baofang Wang , Mingjie Cai | Ocean Engineering

Error Field Identification through Torque Balance on a Saturated Island in DIII-D

2025-06-13

E. J. Strait , Yanzheng Jiang , Qiming Hu +3 more | Plasma Physics and Controlled Fusion

Abstract Measurement of the electromagnetic torque on a magnetic island could be an attractive method for error field identification in the early phase of ITER operation. Previous DIII-D experiments [Strait … Abstract Measurement of the electromagnetic torque on a magnetic island could be an attractive method for error field identification in the early phase of ITER operation. Previous DIII-D experiments [Strait 2014], [Shiraki 2015] have demonstrated the principle of this approach using a stationary or slowly rotating island, while recent developments in magnetic data analysis [Sweeney 2019] allow the field of a rapidly rotating island to be readily distinguished from that of the wall currents induced by its rotation. In a recent experiment, a rotating n=1 magnetic perturbation forced a saturated magnetic island to rotate, thus sampling all toroidal phases periodically in a single discharge. The phase and amplitude of the error field are inferred from analysis of the time-dependent torque balance on the island, including torques from the error field, the applied magnetic perturbation, and the wall currents induced by rotation of the applied perturbation and the island. Results agree well with those from more conventional methods.

Dynamic analysis and neural adaptive control of multi-load coupled tracking system under foundation motion excitation

2025-06-13

Yu Chen , Kunkun Li , Mingliang Xie +5 more | Ain Shams Engineering Journal

Two-vector model predictive thrust force control of PMSLMs without weighting factor based on flux error

2025-06-12

Jian Lin , Xinyi Song , Lei Zhou +2 more | Journal of Power Electronics

Event‐Triggered Iterative Learning Control of Regular Time‐Varying Multi‐Agent Systems Under Switching Topology

2025-06-04

Wei Cao , Huanhuan Li , Jinjie Qiao +1 more | International Journal of Robust and Nonlinear Control

ABSTRACT An event‐triggered iterative learning control algorithm is proposed to address the consensus problem of regular time‐varying multi‐agent systems under switching topology, while considering the insufficient resource space of the … ABSTRACT An event‐triggered iterative learning control algorithm is proposed to address the consensus problem of regular time‐varying multi‐agent systems under switching topology, while considering the insufficient resource space of the system and the output saturation constraint phenomenon. Firstly, the algorithm utilizes the pseudo partial derivative estimates and output estimation errors to design an output observer to overcome the output constrained in the communication network. Secondly, the output estimation error of the observer and the trigger function are used to design the event trigger condition, and when the trigger function value satisfies the event trigger condition, the state values of the agents are updated; otherwise, the state values of the agents will remain unchanged. The gain error of the output observer is used as a variable to design the deadband controller function to avoid the Zeno phenomenon effectively. Then, the control algorithm utilizes the pseudo partial derivative estimation value to adjust the proportion of consistency error in real time, thereby continuously correcting the control input. Under the condition that both the pseudo partial derivative estimation and observer output estimation errors are bounded, the control algorithm proposed in this paper can enable the system to fully track the desired trajectory without the need for real‐time updates of state information. Finally, the effectiveness of the proposed control algorithm is further verified by simulation cases.

Study on the EHL behavior and mechanism under quantitative supply conditions

2025-06-01

Linfeng Sun , Wenzhong Wang , Yuxin Zhou +1 more | Tribology International

Cascaded FIR and half-sine filter-based smooth trajectory generation algorithm

2025-06-01

Yusuf Altintaş , Mahshad Keshtiarast Esfahani , Belhal Karimi +1 more | CIRP Annals

Vibrations control of two degree of freedoms system subject to external force using passive and time delay controllers

2025-06-01

Mai M. Agwa , A. T. EL-Sayed , Yasser A. Amer | Bulletin of Faculty of Science Zagazig University

Feedforward-adaptive neural network control for ultra-precision positioning in magnetic levitation motion stages

2025-06-01

Jinhe Yang , Peng Jiang , Tongjian Guo +3 more | Precision Engineering

Geometrically nonlinear analysis of operation of force exciter with working body made of shape memory alloy

2025-06-01

A. A. Movchan , N. M. Exter | Deformation and Fracture of Materials

A geometrically nonlinear description of the operation of a reusable power drive with a working body made of a shape memory alloy and a linear displacement body has been obtained. … A geometrically nonlinear description of the operation of a reusable power drive with a working body made of a shape memory alloy and a linear displacement body has been obtained. It is shown that the relative error occurring in case of solving this problem in a geometrically linear formulation increases with a development of the phase-structural deformation of the working body and can exceed 20% for some parameters.

Torque Ripple Suppression Control in Vector Control for SRM Drives using Two Types of Mathematical Models with Different Electrical Angular Frequencies

2025-05-31

Keitaro Kawarazaki , Ryoto Kojima , Nobukazu Hoshi | IEEJ Transactions on Industry Applications

Towards an Efficient Control Strategy for an Industrial Multi-DoF Robotic Arm

2025-05-31

Ngoc-Khoat Nguyen , Su-Ling Ho , Duy-Trung Nguyen +3 more | International Journal of Engineering Trends and Technology

State feedback tracking control of piezoelectric actuator based on an fully-actuated system approach

2025-05-30

Jia-bin Liu , Yangxuan Li , Hui Chen | Physica Scripta

Abstract To address the issues of modeling complexity and controller design difficulties due to the inherent nonlinear hysteresis of piezoelectric actuator (PEA), a state feedback control method based on the … Abstract To address the issues of modeling complexity and controller design difficulties due to the inherent nonlinear hysteresis of piezoelectric actuator (PEA), a state feedback control method based on the fully-actuated system (FAS) approach is proposed. Firstly, from a modeling perspective, the linear dynamic behavior is characterized by analyzing the electromechanical and mechanical equations of the PEA, and Bouc-Wen is introduced to describe the static hysteresis phenomenon, so that the second-order fully-actuated model of the PEA is established by connecting the linear dynamics and static hysteresis together in series. Subsequently, the controller design following the FAS approach is detailed, emphasizing the simplicity of the Direct Parameterization Method, The stability of the proposed controller is rigorously proven, In addition, the H∞ paradigm for the disturbance-to-output transfer function is optimized using the fmincon function in order to improve the robustness of the system. Finally, results from reference tracking experiments show that the PEA achieves high-precision tracking control with the designed controller, while disturbance suppression experiments verify that the proposed controllers exhibit a notable degree of disturbance suppression. This ensures stable system operation under various complex working conditions and demonstrates clear advantages over traditional control methods.&#xD;

Design of Composite Two-Channel Disturbance Estimation Adaptive Controller for Backlash-Like Hysteretic Nonlinear Systems

2025-05-30

Qunpo Liu , Jiakun Li , Shumin Fei +2 more | Journal of Shanghai Jiaotong University (Science)

An Improved ADRC Parameters Self-Tuning Controller for Multi-Color Register System in Unit-Type Flexographic Printing Machines

2025-05-26

Wenhui Zhao , Shanhui Liu , Haodi Ding +2 more

A self-tuning control strategy for Active Disturbance Rejection Control (ADRC) parameters based on a Radial Basis Function (RBF) neural network is proposed to improve the control accuracy of the roll-to-roll … A self-tuning control strategy for Active Disturbance Rejection Control (ADRC) parameters based on a Radial Basis Function (RBF) neural network is proposed to improve the control accuracy of the roll-to-roll flexographic printing multi-color register system for its multi-input–multi-output and multi-span coupling characteristics. Firstly, according to the actual physical structure of flexographic printing equipment and the multi-physical coupling interface between adjacent spans, a mathematical model of the register system is established, and the multi-span coupling model is decoupled. Then, the ADRC decoupling controller is designed to estimate the disturbance and control the coupling model, and the RBF neural network is used to adjust the parameters of the decoupling controller in real time. Finally, the robustness, system decoupling, and anti-disturbance performance of the designed controller are verified under simulated steady speed and acceleration conditions. The simulation results show that the designed controller has better control performance than the conventional Proportional-Integral-Derivative (PID) and decoupled PID controllers. In steady state and accelerated simulations of PET/BOPP materials, respectively, the error peak is reduced by 86.7% and is controlled within ± 10 μm, which satisfies the high-accuracy control requirements of the register system.