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American control Conference (ACC)

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

Differential linear repetitive processes are a distinct class of 2D continuous-discrete linear systems of both applications and systems theoretic interest. In applications, they arise in iterative learning control schemes and in iterative solution algorithms for nonlinear dynamic optimal control algorithms based on the maximum principle. Repetitive processes cannot be analysed/controlled by direct application of the existing systems theory and hence a 'mature' systems theory must be developed for them followed (where appropriate) by onward translation into efficient controller design algorithms. This paper continues the development of the former area by developing some significant new results on the application of currently available delay differential systems theory to these processes.

关键词： Delay control theory control systems Iterative algorithms automatic control Ear Metals industry Optimal control System testing computer science

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A neural approach to an attentive navigation for 3D intelligent virtual agents

A neural approach to an attentive navigation for 3D intellig...

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IEEE International Conference on Systems, Man and Cybernetics

作者： M. Lozano J. Molina Artec Group Institute of Robotics. Computer Science Department University of Valencia Valencia Spain Neurotechnology Control and Robotics Group Engineering and Automatic Systems Department Politechnic University of Cartagena Spain

This paper presents an attempt to integrate attention and navigation skills in 3D embodied agents (virtual humanoids). The neural model presented has been divided in two main phases. Firstly the environment-categorization phase, where an online pattern recognition and categorization of the agent current sensory input data is carried out by an adaptive resonance driven self organizing neural network, which will finally simulate the agent's short term memory (STM). Secondly, the model must also learn how and when to map its current STM state into the navigation and attention motor layers of the 3D agent. We also review the world modelling and the agent vision system, and finally we present the first results extracted from two of the subsystems which conforms the complete neural model, such as, the environment categorization subsystem and the base navigation neural model.

关键词： Navigation Intelligent agent Intelligent robots Robotics and automation Humans Graphics Virtual environment Machine vision computer science Augmented virtuality

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A pattern recognition approach to intelligent behaviour: switching the strategies

A pattern recognition approach to intelligent behaviour: swi...

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International IEEE Conference on Intelligent Systems, IS

作者： L. Frangu E. Ceanga S. Caraman Y. Boutalis Department of Automatic Control E2809CDunarea de Jos#x201D University Galati Romania Department of Electrical and Computer Engineering Democritus University of Thrace Xanthi Greece

The paper deals with the intelligent pattern recognition control systems. The concept of strategic situation is introduced, in the context of hierarchical structured control systems. It allows the investigation of the properties of the pattern recognition based control systems. The interaction between the system that recognizes strategies and the environment is described, along with the examples of control systems that allow such an approach. A case study, carried out on a simple process, is presented, to illustrate the method in a plausible context.

关键词： Pattern recognition control systems automatic control Intelligent control Process control Switches Humans Mobile robots Genetic algorithms Adaptive systems

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Model reference parametric adaptive iterative learning control 15th

Model reference parametric adaptive iterative learning contr...

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15th World Congress of the International Federation of automatic control, 2002

作者： Yu, H. Deng, M. Yang, T.C. Owens, D.H. School of Engineering and Computer Science Exeter University ExeterEX4 4QF United Kingdom School of Engineering and Information Technology Sussex University BrightonBN1 9QT United Kingdom Department of Automatic Control and Systems Sheffield University SheffieldS1 3JD United Kingdom

ISBN: (纸本)9783902661746

Most of iterative learning control (ILC) methods requires that the relative degree of the plant is less than 2 for a linear system or the plant is passive for a non-linear system. A new model reference parametric adaptive iterative learning control using the command generator tracker (CGT) theory is proposed in this paper. The method can be applied to control a plant with a higher relative degree and it only requires to iteratively adjust nm + 2 parameters for an SISO plant. Therefore, the ILC control system is very simple. The proposed method is in the spirit of simple adaptive control which has received intensive researches during past two decades. Simulation results show the effectiveness and usefulness of the proposed method. Copyright © 2002 IFAC.

关键词： Model reference adaptive control

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ROBUST SPECIFICATION INFLUENCE ON FEEDBACK control STRATEGIES

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IFAC Proceedings Volumes 2002年第1期35卷 425-430页

作者： M. Gil-Martínez M. García-Sanz System Engineering and Automation Group Electrical Engineering Department University of La Rioja. Luis de Ulloa 20 26004 Logroño SPAIN Automatic Control and Computer Science Department Public University of Navarra. Campus Arrosadía 31006 Pamplona SPAIN

The feedback control structures are required in the presence of any kind of uncertainty. The benefits of the feedback are mainly paid with an excessive bandwidth that amplifies the sensor noise, saturating the actuators. This implies the necessity of design tradeoffs highly transparent from the Quantitative Feedback Theory. Supposing a given uncertainty for a plant, the set of performance and stability requirements will condition the problem solution. Taking advantage of the QFT bound typology and formulation, the contribution of the robust specification values to their simultaneous achievement will be analysed and particularly as regards the challenging task of the controller design.

关键词： Robust control Uncertain dynamical systems Quantitative Feedback Theory

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TWO - LEVEL DISSOLVED OXYGEN control FOR ACTIVATED SLUDGE PROCESSES

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IFAC Proceedings Volumes 2002年第1期35卷 467-472页

作者： M.A. Brdys W. Chotkowski K. Duzinkiewicz K. Konarczak R. Piotrowski Department of Automatic Control Technical University of Gdansk ul. G Narutowicza 11/12 80 952 Gdansk Poland School of Electronic Electrical and Computer Engineering The University of Birmingham Birmingham B15 2TT UK

Two-level controllers for dissolved oxygen reference trajectory tracking for activated sludge processes is proposed and investigated. Both the nutrient and the phosphorous removal from a wastewater by its biological treatment using an activated sludge technology are considered. Typically, an aeration system itself is a complicated hybrid nonlinear dynamical system with faster dynamics compared to internal dynamics of the dissolved oxygen at a biological reactor. It is common approach to neglect this dynamics and also important operational limitations of this system such as a limited frequency of allowed switching of the blowers. The paper proposes a two level controller to track prescribed dissolved oxygen trajectory. The upper level control unit produces desired aeration flow set points. For this unit the aeration system is an actuator. The nonlinear model predictive control algorithm is applied to design this controller unit. Also, the predictive control is used to design the lower level control unit based on a linearised hybrid dynamics of the aeration process. The overall controller is validated by simulation using real data sets and ASM2d model of the biological reactor.

关键词： bio-technical processes nonlinear systems set-point control predictive control hierarchical control

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An algebraic approach to iterative learning control

An algebraic approach to iterative learning control

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IEEE International Symposium on Intelligent control (ISIC)

作者： J. Hatonen K.L. Moore D.H. Owens Automatic Control and Systems Engineering Department University of Sheffield Sheffield UK Systems Engineering Laboratory University of Oulu Linnanmaa Finland Department of Electrical and Computer Engineering College of Engineering Utah State University Logan UT USA

In this paper discrete-time iterative learning control (ILC) systems are analysed from an algebraic point of view. The algebraic analysis shows that an ILC synthesis problem can be considered as a tracking problem of a multi-channel step-function. Furthermore, the plant to be controlled is a static multivariable plant. Another major contribution of this paper is a general convergence theory of ILC systems in terms of their closed-loop poles. This convergence theory shows that time-variant ILC control laws should be typically used instead of time-invariant control laws in order to guarantee good transient tracking behaviour. Simulations high-light the different theoretical findings in this paper.

关键词： Iterative methods automatic control control systems Convergence Systems engineering and theory Intelligent systems Educational institutions Laboratories control system synthesis Modeling

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Towards research on software cybernetics

Towards research on software cybernetics

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IEEE International Symposim on High Assurance Systems Engineering

作者： Kai-Yuan Cai T.Y. Chen T.H. Tse Department of Automatic Control Beijing Aeronautics and Astronautics University Beijing China School of Information Technology Swinburne University of Technology Hawthorn Australia Department of Computer Science and Information Systems University of Hong Kong Hong Kong China

Software cybernetics is a newly proposed area in software engineering. It makes better use of the interplay between control theory/engineering and software engineering. In this paper, we look into the research potenti... 详细信息

关键词： Cybernetics Software testing Software engineering control theory automatic control System testing control systems Adaptive control Programming Information technology

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Hybrid position/force control of constrained robot manipulator based on a feedforward neural network

Hybrid position/force control of constrained robot manipulat...

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IEEE International Conference on Industrial Technology (ICIT)

作者： Lianfang Tian Jun Wang Zongyuan Mao Department of Mechanical Engineering University of California Riverside CA USA Department of Automation and Computer-aided Engineering Chinese University of Hong Kong New Territories Hong Kong China Department of Automatic Control Engineering South China University of Technology Guangzhou China

In this paper, the control of constrained robotic manipulators is addressed and the solution of a reduced order model is obtained through a nonlinear transformation. A set of differential-algebraic equations are first derived. Then controllers are designed for position and force control. The position control involves the position and velocity feedback of end-effector, while the force control is developed based on an artificial neural network. The weights of the neural network are updated online using the force error as the objective function. An example of a 2-DOF manipulator system is studied in detail. Comparisons between a conventional PID controller and the designed controller are made and a practical application is carried out. The results demonstrate the effective performance of the system.

关键词： Force control Manipulators Neural networks Feedforward neural networks Artificial neural networks Robot control Reduced order systems Differential equations Nonlinear equations Position control

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Constrained motion control of flexible manipulators based on a dynamic neural network

Constrained motion control of flexible manipulators based on...

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IEEE International Conference on Industrial Technology (ICIT)

ISBN: (纸本)0780376579

In this paper, a neural network approach is proposed for the motion control of a constrained flexible manipulator system, whereby both the contact force and the position of the end-effector contacting with a surface are controlled. The dynamic equations, vibration of the flexible link and constrained force are derived. The developed control scheme can adaptively estimate the dynamics of the manipulator by utilizing a dynamic recurrent neural network (DRNN) to approximate the underlying dynamics. Local stability of the system is discussed. The results confirm that the designed controller performs remarkably well.

关键词： Manipulator dynamics Motion control Neural networks automatic control Uncertainty control systems Motion planning Force control Equations Stability

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