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检索条件"任意字段=Proceedings of the IEEE/IFAC Joint Symposium on Computer-Aided Control System Design"

共 1780 条记录，以下是161-170 订阅

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A Matlab toolbox for LMI-based analysis and synthesis of LPV/LFT self-scheduled H∞ control systems

A Matlab toolbox for LMI-based analysis and synthesis of LPV...

引用

ieee International symposium on computer-aided control system design

作者： De Vito, Daniele Kron, Aymeric De Lafontaine, Jean Lovera, Marco Politecnico di Milano Dipartimento di Elettronica e Informazione Via Ponzio 34/5 20133 Milano Italy NGC Aerospace Ltd Office 202 1650 Rue King Ouest Sherbrooke QC J1J 2C3 Canada

ISBN: (纸本)9781424453542

When controlling a Linear Parameter Varying (LPV) system, a LPV regulator is advisable, since it ensures better performance than a simple Linear Time Invariant actually does. In fact, real-time scheduling to the variations of the system allows the achievement of stability and performance requirements for a number of operating points. Within this setting, this paper discusses a Matlab toolbox achieving a self- scheduled LPV controller for an LPV model of the plant, robust in an H∞ sense in the face of uncertainties affecting the sys- tem's dynamics, through a Linear Matrix Inequality approach. The resulting algorithm alternatively implements synthesis and analysis steps, until the desired closed-loop performance level has been reached or no improvement between two successive steps arises. © 2010 ieee.

关键词： Linear matrix inequalities

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On the complexity of randomized approximations of nonconvex sets

On the complexity of randomized approximations of nonconvex ...

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ieee International symposium on computer-aided control system design

作者： Dabbene, Fabrizio Lagoa, Constantino Shcherbakov, Pavel IEIIT-CNR Italy Penn State University United States Institute of Control Science Moscow Russia

ISBN: (纸本)9781424453542

We consider a nonconvex set X ∈ n endowed with a probability measure P, and assume that random samples taken according to this measure are available. For Ε ∈ (0;1), we say that the set A ∈ n is an Ε-probabilistic approximation of X if the probability of a point to belong to X and not to A is less than Ε. In this paper, we show that a simple randomized algorithm returning with high probability convex Ε-approximations of X can be easily devised. In particular, we consider different possible shapes for the set A, namely ellipsoids, hyperrectangles, and parallelotopes, and show how specific approximations based on such shapes can be constructed. Moreover, we derive explicit bounds on the complexity of such approximations, in terms of the number of samples needed in the different cases. It turns out that, while the complexity of ellipsoidal and parallelotopic approximations grow quadratically with respect to the dimension n, in the case of orthotopes one obtains linear dependence. The second part of the paper is devoted to the study of tighter approximations, based on recent results on the connection between chanceconstrained problems and scenario problems with discarded constraints. There are numerous applications of this result in systems and control theory;a specific motivation for the research conducted in this paper is the characterization of the reachable sets of nonlinear systems, and the related problem of nonlinear filtering. © 2010 ieee.

关键词： Probability

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A closed-loop brain-machine interface simulator based on computer mouse control

A closed-loop brain-machine interface simulator based on com...

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ieee International symposium on computer-aided control system design

作者： Kwon, Yoomi Kim, Sung-Phil Department of Brain and Cognitive Engineering Korea University Seoul Korea Republic of

ISBN: (纸本)9781424453542

Brain Machine Interface (BMIs), which delivers information from the brain to external devices, can provide independence to the disabled who cannot control their body voluntarily. Over the last decade, BMIs have been developed rapidly by the support of a number of non-human and human studies to provide the proof-of-concept of a BMI. BMI development draws upon the findings and insights from neuroscience, engineering, mathematics and computer science, typically testing new approaches using the pre-existing neural database due to practical issues such as time limit, subject training and on-site system maintenance. For those studies which involve repetitive changes of parameters and models, the cost of performing closed-loop experiments would exponentially increase. However, testing in an offline condition may not assure that the concept confirmed in an open-loop (OL) analysis also applies to closed-loop (CL) applications. To provide both OL and CL testing environments, we propose a new software-based tool that simulates closed-loop neural control through BMIs. In this tool, neural data are generated by the user's computer mouse input through a linear tuning function whose parameters are configured from the real neural data. The decoding algorithm as well as the control interface can be easily customized and one can execute a closed-loop experiment in a similar way to real BMI control environment. We present a case study of using this BMI simulator to investigate the effect of closed-loop training on control performance. It is anticipated that the BMI simulator may be able to allow researchers to investigate the entire process of a closed-loop BMI study and address the issues which cannot be resolved in an open loop data analysis. © 2010 ieee.

关键词： Brain computer interface

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Code generation for receding horizon control

Code generation for receding horizon control

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ieee International symposium on computer-aided control system design

作者： Mattingley, Jacob Wang, Yang Boyd, Stephen

ISBN: (纸本)9781424453542

Receding horizon control (RHC), also known as model predictive control (MPC), is a general purpose control scheme that involves repeatedly solving a constrained optimization problem, using predictions of future costs, disturbances, and constraints over a moving time horizon to choose the control action. RHC handles constraints, such as limits on control variables, in a direct and natural way, and generates sophisticated feed-forward actions. The main disadvantage of RHC is that an optimization problem has to be solved at each step, which leads many control engineers to think that it can only be used for systems with slow sampling (say, less than one Hz). Several techniques have recently been developed to get around this problem. In one approach, called explicit MPC, the optimization problem is solved analytically and explicitly, so evaluating the control policy requires only a lookup table search. Another approach, which is our focus here, is to exploit the structure in the optimization problem to solve it efficiently. This approach has previously been applied in several specific cases, using custom, hand written code. However, this requires significant development time, and specialist knowledge of optimization and numerical algorithms. Recent developments in convex optimization code generation have made the task much easier and quicker. With code generation, the RHC policy is specified in a high-level language, then automatically transformed into source code for a custom solver. The custom solver is typically orders of magnitude faster than a generic solver, solving in milliseconds or microseconds on standard processors, making it possible to use RHC policies at kilohertz rates. In this paper we demonstrate code generation with two simple control examples. They show a range of problems that may be handled by RHC. In every case, we show a speedup of several hundred times from generic parser-solvers. © 2010 ieee.

关键词： Convex optimization

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A framework for model-based design of experiments in the presence of continuous measurement systems

A framework for model-based design of experiments in the pre...

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9th International symposium on Dynamics and control of Process systems, DYCOPS 2010

作者： Galvanin, Federico Barolo, Massimiliano Bezzo, Fabrizio CAPE-Lab. - Computer-Aided Process Engineering Laboratory Dipartimento di Principi e Impianti di Ingegneria Chimica Università di Padova via Marzolo 9 35131 Padova Italy

ISBN: (纸本)9783902661692

Model-based design of experiments (MBDoE) techniques are a useful tool to maximise the information content of experimental trials when the purpose is identifying the set of parameters of a deterministic model in a statistically sound way. When samples are collected in a discrete way, the formulation of the optimal design problem is based on the maximisation of the expected information, usually calculated from discrete forms of the Fisher information matrix. However, if a continuous measurement system is available, information can be acquired gradually in a continuous way, and a new MBDoE approach is required to take into account the specificity of the measurement system. In this paper a novel design criterion is formulated by optimising a continuous measurement of the Fisher information matrix, with the purpose of reaching a statistically satisfactory estimation of model parameters in the easiest and quickest way. The benefits of the proposed strategy are discussed through a simulated case study, where the effectiveness of the design is assessed by comparison to a standard MBDoE approach. © 2009 ifac.

关键词： Parameter estimation

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control-theoretic analysis of exploitation and exploration of the PSO algorithm

Control-theoretic analysis of exploitation and exploration o...

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作者： Wakasa, Yuji Tanaka, Kanya Nishimura, Yuki Graduate School of Science and Engineering Yamaguchi University 2-16-1 Tokiwadai Ube Yamaguchi 755-8611 Japan

ISBN: (纸本)9781424453542

The behavior of the particle swarm optimization (PSO) algorithm is analyzed by regarding its dynamics as a system with multiplicative noise and applying control-theoretic analysis methods. In order to evaluate the convergence and diversity of the PSO algorithm, two measures related to the decay rate and l2 gain of the PSO dynamics are used. These measures are characterized by linear matrix inequalities (LMIs) and are therefore efficiently computed by convex optimization tools. As for the measure related to the decay rate, moreover, an alternative condition in terms of nonlinear scalar inequalities is presented which can be checked more shortly and accurately than the LMI. Numerical experiments suggest that the measures are effective enough to evaluate the convergence and diversity of the PSO algorithm, which results in better understanding of the PSO algorithm from the viewpoints of exploitation and exploration abilities. © 2010 ieee.

关键词： Linear matrix inequalities

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Human factor and computational intelligence limitations in resilient control systems

Human factor and computational intelligence limitations in r...

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International symposium on Resilient control systems

作者： Wilamowski, Bogdan M. Auburn University United States

ISBN: (纸本)9781424459544

Humans are very capable of solving many scientific and engineering problems, but during the solution process they have a tendency to make mistakes. For example, humans without computer aided tools, would not be able to design VLSI chips larger than 100 transistors. This imperfection of humans make them very unreliable elements in resilient control systems. There is a tendency of replacing humans with computers using artificial intelligence, expert systems, or methods of computational intelligence. The methods of computational intelligence can be most successful but they have to be used with great care. Limitations of fuzzy and neural networks are presented and it is shown how to avoid these limitations so resilient control systems can be developed. It turns out that often popular training algorithms are not capable of tuning neural networks to proper accuracy without losing generalization abilities. As a consequence, such system of computational intelligence may not work properly for cases which were not used in training. The comparison of different neural network architectures follows and also it is shown how to develop and train close to optimal topologies, so resilient control systems can be developed. © 2010 ieee.

关键词： Expert systems

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Object-oriented input signal design for system identification

Object-oriented input signal design for system identificatio...

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15th ifac symposium on system Identification, SYSID 2009

作者： Barker, H.A. Tan, A.H. Godfrey, K.R. School of Engineering Swansea University Swansea SA2 8PP United Kingdom Faculty of Engineering Multimedia University 63100 Cyberjaya Malaysia School of Engineering University of Warwick Coventry CV4 7AL United Kingdom

ISBN: (纸本)9783902661470

The paper describes how object-oriented methods may be applied to the design of input signals for system identification. Their terminology and concepts are defined, and it is shown that although they are best known as computer programming methods, they are also modelling methods applicable to engineering design. In particular, the concepts of aggregation and inheritance lead to a new method for creating input signals with a wide range of levels and periods, with an additional advantage that the objects created can be reused. The method, which involves operations in Galois fields, is described in detail and illustrated by an example. Copyright © 2009 ifac.

关键词： Identification (control systems)

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Tutorial on system identification of polynomial and of rational systems

Tutorial on system identification of polynomial and of ratio...

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15th ifac symposium on system Identification, SYSID 2009

作者： Němcová, Jana Van Schuppen, Jan H. CWI P.O.Box 94079 1090 GB Amsterdam Netherlands

ISBN: (纸本)9783902661470

The aim of this tutorial paper is to provide an overview of system identification of polynomial and of rational systems. It is an introduction to a session included in the program of the ifac symposium system Identification (SYSID.2009). Polynomial and rational systems arise in systems biology where there is a great need to have algorithms and methods for obtaining realistic models. The paper presents a system identification procedure for these classes of systems consisting of: (1) Modeling;(2) Experiment design and data processing;(3) Identifiability;(4) Approximation;and (5) Evaluation. Major open problems include the approximation problem and computer-algebra algorithms for checking identifiability. © 2009 ifac.

关键词： Polynomials

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A scenario based approach to robust experiment design

A scenario based approach to robust experiment design

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15th ifac symposium on system Identification, SYSID 2009

作者： Welsh, James S. Rojas, Cristian R. School of Electrical Engineering and Computer Science University of Newcastle NSW 2308 Australia ACCESS Linnaeus Center Electrical Engineering KTH-Royal Institute of Technology S-100 44 Stockholm Sweden

ISBN: (纸本)9783902661470

Robust optimal experiment design is an infinite dimensional optimisation problem. Typically it is solved by discretisation of the design space resulting in a discrete semi-infinite convex programming problem which is computationally expensive. In this paper we propose a new computational approach to solve robust optimal experiment design problems based on a recently developed method for robust convex optimisation known as the 'scenario approach'. © 2009 ifac.

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