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Iterative learning control - What is it all about?

Iterative learning control - What is it all about?

2004 IFAC Workshop on Adaptation and Learning in control and Signal Processing, ALCOSP 2004 and IFAC Workshop on Periodic control systems, PSYCO 2004

作者： Hätönen, J. Harte, T.J. Owens, D.H. Ratcliffe, J. Lewin, P. Rogers, E. Department of Automatic Control and Systems Engineering University of Sheffield Mappin Street SheffieldS1 3JD United Kingdom Department of Electronics and Computer Science University of Southampton SouthamptonSO17 1BJ United Kingdom

The main objective of this paper is to show how one can benefit from using Iterative Learning control instead of conventional feedback control. As a main result it is shown that even if the nominal plant satisfies a given uncertainty condition, there always exists ILC algorithms that can drive the tracking error monotonically to zero. This same result cannot be achieved with conventional feedback control, or by inverting a nominal model of the plant. Hence ILC offers an unique tool to invert dynamical systems with uncertainty. Copyright © 2004 IFAC

关键词： Robust control

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Discrete-time Arimoto ILC-algorithm revisited

Discrete-time Arimoto ILC-algorithm revisited

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2004 IFAC Workshop on Adaptation and Learning in control and Signal Processing, ALCOSP 2004 and IFAC Workshop on Periodic control systems, PSYCO 2004

This paper revisits the Arimoto-algorithm in the discrete-time case. It is shown that if a plant satisfies a positivity condition, there always exists a learning gain so that the algorithm converges monotonically to zero tracking error. If the plant does not satisfy the positivity condition, a linear LQ tracker can be used to condition the plant so that it satisfies the positivity condition. the overall structure results in a novel combination of Arimoto ILC and LQ optimal control, that drives the tracking error monotonically to zero for an arbitrary discrete-time LTI plant. This is a very strong property for any ILC algorithm. Copyright © 2004 IFAC

关键词： Iterative methods

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A high-performance DSP-controller for parallel operation of online UPS systems

A high-performance DSP-controller for parallel operation of ...

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Annual IEEE Conference on Applied Power Electronics Conference and Exposition (APEC)

作者： J.M. Guerrero L.G. de Vicuna J. Matas J. Miret M. Castilla Department of Automatic Control Systems and Computer Engineering Barcelona Spain Department of Electronics Engineering Vilanova i la Geltru Spain

In this paper, a novel controller for parallel-connected online uninterruptible power supplies (UPS) without control interconnections based on the droop method is presented. The control approach consists in drop the frequency of every module when its output power increases, resulting in an unavoidable nominal frequency deviation. Consequently, this method in its original form is only applicable to off-line or line-interactive UPS systems. As opposed to the conventional droop method, the proposed control scheme endows proper transient response, strictly frequency and phase synchronization with the AC mains, and excellent power sharing even for nonlinear loads. Hence, this controller is suitable for paralleled online UPS systems. Experimental results are obtained from two parallel-connected 1-kVA online UPS by using TMS320LF2407A DSP.

关键词： Uninterruptible power systems control systems Power harmonic filters Voltage Power engineering and energy Power generation Transient response Frequency synchronization Digital signal processing Wires

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Integrating phrases to enhance HSOMART-based document clustering

Integrating phrases to enhance HSOMART-based document cluste...

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International Joint Conference on Neural Networks (IJCNN)

作者： M.F. Hussin M.S. Kamel Department of Computer Science & Automatic Control Alexandria University Alexandria Egypt Department of Systems Design Engineering University of Waterloo Waterloo ONT Canada

Document clustering is one of the popular techniques that assist users in organizing collections of documents. Two successful models of unsupervised neural networks, self-organizing map (SOM) and adaptive resonance theory (ART), have shown promising results in this task. Most of the existing neural network based document clustering techniques rely on a "bag of words" document representation. Each word in the document is considered as a separate feature, ignoring the word order. We investigate the use of phrases rather than words as document features applied to our proposed document clustering technique, called hierarchical SOMART (HSOMART), which is a hierarchical network built up from independent SOM and ART neural networks. We describe a phrase grammar extraction technique, and the proposed HSOMART. The experimental results of clustering documents from the REUTERS corpus using the extracted phrases as features show an improvement in the clustering performance evaluated using the entropy and F-measure.

关键词： Neural networks Clustering algorithms Subspace constraints Tree graphs Text categorization computer science automatic control Organizing Resonance Feature extraction

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Experimental evaluation of a new repetitive control algorithm on a non-minimum phase spring-mass-damper system

Experimental evaluation of a new repetitive control algorith...

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2004 IFAC Workshop on Adaptation and Learning in control and Signal Processing, ALCOSP 2004 and IFAC Workshop on Periodic control systems, PSYCO 2004

作者： Freeman, C.T. Hätönen, J.J. Lewin, P.L. Owens, D.H. Rogers, E. School of Electronics and Computer Science University of Southampton University Road SouthamptonSO17 1BJ United Kingdom Department of Automatic Control and Systems Engineering University of Sheffield Mappin Street SheffieldS1 3JD United Kingdom Systems Engineering Laboratory University of Oulu University of Oulu P.O. BOX 4300 FIN-90014 Finland

Recently, a novel optimality based Repetitive control algorithm was proposed in (Hätönen et al., 2003). According to the convergence analysis carried out in that paper, the algorithm will result in asymptotic convergence for an arbitrary discrete-time LTI plant and a T -periodic reference. However, the performance of the algorithm was tested only using simulation studies. In order to rigorously test how the algorithm performs with real systems, in this paper the algorithm is implemented on a non-minimum phase spring-mass-damper system. The results are very satisfactory, because the algorithm results in near perfect tracking with this rather demanding plant type. Copyright © 2004 IFAC.

关键词： Non-Minimum Phase systems Optimal control Polynomial systems Theory Repetitive control

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Practical implementation of a model inverse iterative learning controller

Practical implementation of a model inverse iterative learni...

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2004 IFAC Workshop on Adaptation and Learning in control and Signal Processing, ALCOSP 2004 and IFAC Workshop on Periodic control systems, PSYCO 2004

作者： Ratcliffe, J.D. Harte, T.J. Hätönen, J.J. Lewin, P.L. Rogers, E. Owens, D.H. School of Electronics and Computer Science University of Southampton University Road SouthamptonSO17 1BJ United Kingdom Department of Automatic Control and Systems Engineering University of Sheffield Mappin Street SheffieldS1 3JD United Kingdom Systems Engineering Laboratory University of Oulu University of Oulu P.O. BOX 4300 FIN-90014 Finland

In this paper, a new model inverse optimal iterative learning control algorithm is practically implemented on an industrial gantry robot. The algorithm has only one tuning parameter which can be adjusted to provide a balance between convergence speed and robustness. Results show that the algorithm is capable of learning the required trajectory in very few iterations. However at this convergence rate the lack of robustness is a major issue. Appropriate use of the tuning parameter is shown to greatly increase the algorithm robustness as demonstrated by tests which successfully reach 600 iterations. Copyright c 2004 IFAC. Copyright © 2004 IFAC

关键词： Iterative methods

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LMI based output feedback control of discrete linear repetitive processes

LMI based output feedback control of discrete linear repetit...

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American control Conference (ACC)

作者： B. Sulikowski K. Galkowski E. Rogers D.H. Owens Institute of Control and Computation Engineering University of Zielona Gora Zielona Gora Poland School of Electronics and Computer Science University of Southampton Southampton UK Department Automatic Control and Systems Engineering University of Sheffield Sheffield UK

Repetitive processes are a distinct class of 2D systems (i.e. information propagation in two independent directions) of both systems theoretic and applications interest. They cannot be controlled by direct extension of existing techniques from either standard (termed 1D here) or 2D systems theory. Here we give new results on the relatively open problem of the design of physically based control laws. These results are for the sub-class of so-called discrete linear repetitive processes, which arise in applications areas such as iterative learning control.

关键词： Output feedback Linear feedback control systems Iterative algorithms Optimal control automatic control automatic generation control Stability analysis Vectors Linear systems control systems

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H/sub /spl infin// control of differential linear repetitive processes

H/sub /spl infin// control of differential linear repetitive...

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American control Conference (ACC)

作者： W. Paszke K. Galkowski E. Rogers D.H. Owens Institute of Control and Computation Engineering University of Zielona Góra Zielona Gora Poland School of Electronics and Computer Science University of Southampton Southampton UK Department of Automatic Control and Systems Engineering University of Sheffield Sheffield UK

Repetitive processes are a distinct class of two-dimensional systems (i.e., information propagation in two independent directions) of both systems theoretic and applications interest. They cannot be controlled by direct extension of existing techniques from either standard (termed 1D here) or two-dimensional (2D) systems theory. Here, we give new results on the relatively open problem of the design of physically based control laws using an H/sub /spl infin// setting. These results are for the sub-class of so-called differential linear repetitive processes, which arise in application areas such as iterative learning control.

关键词： Linear matrix inequalities Symmetric matrices State-space methods Vectors Stability Robust control Boundary conditions Sufficient conditions Differential equations control systems

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Discrete-time Arimoto ILC-algorithm revisited

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IFAC Proceedings Volumes 2004年第12期37卷 541-546页

作者： J. Hätönen T.J. Harte D.H. Owens J. Ratcliffe P. Lewin E. Rogers Department of Automatic Control and Systems Engineering University of Sheffield Mappin Street Sheffield S1 3JD United Kingdom Department of Electronics and Computer Science University of Southampton Southampton SO17 1BJ United Kingdom

This paper revisits the Arimoto-algorithm in the discrete-time case. It is shown that if a plant satisfies a positivity condition, there always exists a learning gain so that the algorithm converges monotonically to zero tracking error. If the plant does not satisfy the positivity condition, a linear LQ tracker can be used to condition the plant so that it satisfies the positivity condition. The overall structure results in a novel combination of Arimoto ILC and LQ optimal control, that drives the tracking error monotonically to zero for an arbitrary discrete-time LTI plant. This is a very strong property for any ILC algorithm.

关键词： Iterative learning control positive-real systems

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Iterative Learning control - What is it all about?

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IFAC Proceedings Volumes 2004年第12期37卷 547-553页

关键词： Iterative learning control robust control positive-real systems

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