scispace - formally typeset
Search or ask a question
Journal ArticleDOI

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

TL;DR: Three control methods—iterative learning control, repetitive control (RC), and run-to-run control (R2R)—are studied and compared and some promising fields for learning-type control are revealed.
About: This article is published in Journal of Process Control.The article was published on 2009-12-01. It has received 679 citations till now. The article focuses on the topics: Repetitive control & Iterative learning control.
Citations
More filters
Journal ArticleDOI
TL;DR: The main objective of this paper is to review and summarize the recent achievements in data-based techniques, especially for complicated industrial applications, thus providing a referee for further study on the related topics both from academic and practical points of view.
Abstract: This paper provides an overview of the recent developments in data-based techniques focused on modern industrial applications. As one of the hottest research topics for complicated processes, the data-based techniques have been rapidly developed over the past two decades and widely used in numerous industrial sectors nowadays. The core of data-based techniques is to take full advantage of the huge amounts of available process data, aiming to acquire the useful information within. Compared with the well-developed model-based approaches, data-based techniques provide efficient alternative solutions for different industrial issues under various operating conditions. The main objective of this paper is to review and summarize the recent achievements in data-based techniques, especially for complicated industrial applications, thus providing a referee for further study on the related topics both from academic and practical points of view. This paper begins with a brief evolutionary overview of data-based techniques in the last two decades. Then, the methodologies only based on process measurements and the model-data integrated techniques will be further introduced. The recent developments for modern industrial applications are, respectively, presented mainly from perspectives of monitoring and control. The new trends of data-based technique as well as potential application fields are finally discussed.

856 citations


Cites background from "Survey on iterative learning contro..."

  • ...trial to trial plays a key role in encouraging researchers to seek for the practical implementation in dynamic systems [16]....

    [...]

  • ...Recent developments and comprehensive comparisons with standard control strategies can be found in [15] and [16]....

    [...]

Journal ArticleDOI
TL;DR: A learning model predictive controller for iterative tasks is presented in this article, where a safe set and a terminal cost function are used in order to guarantee recursive feasibility and non-decreasing performance at each iteration.
Abstract: A learning model predictive controller for iterative tasks is presented. The controller is reference-free and is able to improve its performance by learning from previous iterations. A safe set and a terminal cost function are used in order to guarantee recursive feasibility and nondecreasing performance at each iteration. This paper presents the control design approach, and shows how to recursively construct terminal set and terminal cost from state and input trajectories of previous iterations. Simulation results show the effectiveness of the proposed control logic.

261 citations

Journal ArticleDOI
TL;DR: This manuscript surveys the current state of the art in SILC from the perspective of key techniques, which are divided into three parts: SILC for linear stochastic systems, SilC for nonlinear stochastics systems, and systems with other stochastically signals.

190 citations

Journal ArticleDOI
TL;DR: A distributed D-type iterative learning scheme is developed for the multi-agent system with switching topology, whose switching time and sequence are allowed to be varied at different iterations according to the actual trajectories of agents.

183 citations

Proceedings ArticleDOI
21 May 2018
TL;DR: This work exploits the fact that in modern assembly domains, geometric information about the task is readily available via the CAD design files, and proposes a neural network architecture that can learn to track the motion plan, thereby generalizing the assembly controller to changes in the object positions.
Abstract: In this work, motivated by recent manufacturing trends, we investigate autonomous robotic assembly. Industrial assembly tasks require contact-rich manipulation skills, which are challenging to acquire using classical control and motion planning approaches. Consequently, robot controllers for assembly domains are presently engineered to solve a particular task, and cannot easily handle variations in the product or environment. Reinforcement learning (RL) is a promising approach for autonomously acquiring robot skills that involve contact-rich dynamics. However, RL relies on random exploration for learning a control policy, which requires many robot executions, and often gets trapped in locally suboptimal solutions. Instead, we posit that prior knowledge, when available, can improve RL performance. We exploit the fact that in modern assembly domains, geometric information about the task is readily available via the CAD design files. We propose to leverage this prior knowledge by guiding RL along a geometric motion plan, calculated using the CAD data. We show that our approach effectively improves over traditional control approaches for tracking the motion plan, and can solve assembly tasks that require high precision, even without accurate state estimation. In addition, we propose a neural network architecture that can learn to track the motion plan, thereby generalizing the assembly controller to changes in the object positions.

136 citations


Cites background from "Survey on iterative learning contro..."

  • ...Given a fixed motion plan, iterative learning control (ILC) [19], [20], [21], [22] sequentially adapts a controller to track it....

    [...]

References
More filters
Book
01 Jan 1975
TL;DR: In this paper, the Bellman-Gronwall Lemma has been applied to the small gain theorem in the context of linear systems and convolutional neural networks, and it has been shown that it can be applied to linear systems.
Abstract: Preface to the Classics edition Preface Acknowledgments Note to the reader List of symbols 1. Memoryless nonlinearities 2. Norms 3. General theorems 4. Linear systems 5. Applications of the small gain theorem 6. Passivity Appendix A. Integrals and series Appendix B. Fourier transforms Appendix C. Convolution Appendix D. Algebras Appendix E. Bellman-Gronwall Lemma References Index.

2,894 citations

Journal ArticleDOI
01 Nov 2007
TL;DR: 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.
Abstract: 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.

1,417 citations


"Survey on iterative learning contro..." refers background in this paper

  • ...Each of them cite many references; for example, an overview paper on ILC [4] has 514 references; a survey on repetitive control [5] includes 107 references; while a survey about run-torun control [6] cites 42 references....

    [...]

Journal ArticleDOI
TL;DR: In this article, a control scheme called repetitive control is proposed, in which the controlled variables follow periodic reference commands, and 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.
Abstract: 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. >

1,352 citations


"Survey on iterative learning contro..." refers background or methods in this paper

  • ...In fact, as early as 1988, an indirect RC was proposed in [48]....

    [...]

  • ...The small gain theorem [47] is a popular tool for analysis of the stability of an RC [48]....

    [...]

Journal ArticleDOI
TL;DR: In this paper, structural stability of linear multivariable regulators is defined and necessary and sufficient structural criteria are obtained for linear multi-variable regulators which retain loop stability and output regulation in the presence of small perturbations, of specified types, in system parameters.
Abstract: Necessary structural criteria are obtained for linear multivariable regulators which retain loop stability and output regulation in the presence of small perturbations, of specified types, in system parameters. It is shown that structural stability thus defined requires feedback of the regulated variable, together with a suitably reduplicated model, internal to the feedback loop, of the dynamic structure of the exogenous reference and disturbance signals which the regulator is required to process. Necessity of these structural features constitutes the ‘internal model principle’.

1,090 citations

Book
01 Feb 1985
TL;DR: In the last two decades considerable effort and progress have been made in the two-dimensional and multidimensional systems theory and its industrial applications as mentioned in this paper, and this part of the book summarizes some recent developments in 2D linear systems theory.
Abstract: In the last two decades considerable effort and progress have been made in the two-dimensional (2D) and multidimensional systems theory and its industrial applications. This part of the book summarizes some recent developments in 2D linear systems theory and its applications.

830 citations