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20th World Congress of the International-Federation-of-Automatic-Control (IFAC)

作者： Woittennek, Frank Riesmeier, Marcus Ecklebe, Stefan Univ Hlth Sci Med Informat & Technol Inst Automat & Control Engn A-6060 Hall In Tirol Austria Tech Univ Dresden Inst Control Theory D-01069 Dresden Germany

This paper presents an approach for the efficient numerical implementation of transformation based state feedback laws for linear distributed parameter systems. The control laws considered may originate from backstepping or flatness-based design methods. They are, therefore, directly based on the underlying distributed parameter systems. In general, they are given as unbounded functionals on the infinite-dimensional state-space. By approximating a carefully chosen bounded part, the implementation of these feedback-operators can be considerably simplified. This is achieved by approximating the state in appropriate finite dimensional sub-spaces of the state-space. The choice of these sub-spaces as well as the controller implementation are discussed for both, a particular motivating example specific and the general case. For the implementation and validation of the obtained approximated controllers the python-based software toolbox Pylnduct is introduced. (C) 2017, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

关键词： distributed parameter system parabolic system hyperbolic system state feedback flatness backstepping late lumping feedback control

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Receding Horizon H∞ Guaranteed Cost Control for Uncertain distributed parameter systems with Actuator Saturation 38

Receding Horizon H∞ Guaranteed Cost Control for Uncertain D...

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38th Chinese Control Conference (CCC)

作者： Zhong, Jiaqi Yuan, Yupeng Liu, Rongxiang Wu, Tao Wen, Shengfu Chongqing Univ Posts & Telecommun Coll Automat Key Lab Ind Internet Things & Networked Control Minist Educ Chongqing 400065 Peoples R China China Elect Technol Grp Corp Chongqing Acoust Opt Elect Co Ltd Chongqing 401332 Peoples R China

ISBN: (纸本)9789881563972

distributed parameter systems (DPSs) widely exist in a variety of physical, chemical and biological systems. Due to the infinite dimensional characteristics of DPS, it is difficult for us to obtain the analytical solution and controller design. In this paper, the receding horizon H-infinity guaranteed cost controller is proposed for a class of DPSs. A finite-dimensional ODE is first derived by improving the spectral Galerkin method. Subsequently, a sufficient condition is proposed to access a tradeoff between the robust performance indexes and actuator saturation. Then, in the framework of linear matrix inequations (LMIs), the receding horizon H-infinity guaranteed cost controller can be obtained by on-line solving the optimization problem. Finally, the effectiveness of the proposed controller is demonstrated by conducting a simulation on the process of microwave heating Debye medium.

关键词： Robust Control H-infinity Norm Guaranteed Cost distributed parameter system Actuator Saturation

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Control distributed parameter systems with orthogonal neural network learning

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Informatica 1996年第4期7卷 431-454页

作者： Garliauskas, Algis Gupta, Madan M. Inst. of Mathematics and Informatics 2600 Vilnius Akademijos 4 Lithuania University of Saskatchewan Saskatoon Sask. S7N 5A9 Canada Computer Center Dept. of the USSR Acad. of Sciences Novosibirsk Russian Federation Laboratory of Neuroinformatics Instit. Math. and Inform. Lithuania Birla Engineering College Pilani India University of Warwick United Kingdom Department of Engineering Ctr. Excellence on Neuro-Vis. Res. University of Saskatchewan Saskatoon Sask. Canada Intelligent Syst. Res. Laboratory Ctr. Excellence on Neuro-Vis. Res. University of Saskatchewan Saskatoon Sask. Canada

Adaptive Control distributed parameter systems (ACDPS) with adaptive learning algorithms based on orthogonal neural network methodology are presented in this paper. We discuss a modification of orthogonal least squares learning to find appropriate efficient algorithms for solution of ACDPS problems. A two times problem linked with the real time of plant control dynamic processes and the learning time for adjustment of parameters in adaptive control of unknown distributed systems is discussed. The simulation results demonstrate that the orthogonal learning algorithms on a neural network concept allow to find perfectly tracked output control distributed parameters in ACDPS and have rather a good perspective in the development of generalised ACDSP theory and practice in the future.

关键词： Adaptive control distributed parameter system Nonlinear control Orthogonal neural network learning

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NEW ENGINEERING METHODS FOR QUANTITIES FIELDS distributed parameter-systemS CONTROL

NEW ENGINEERING METHODS FOR QUANTITIES FIELDS DISTRIBUTED PA...

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SYMP ON LOW COST AUTOMATION

作者： HULKO, G NAVRACIC, I ROHALILKIV, B SAPAK, L ZILKA, M ZELINKA, P Slovak Technical Univ Bratislava Slovakia

ISBN: (纸本)0080378668

New engineering methods for quantities fields control and for optimal design of technical systems for quantities fields interactions will be indicated in the paper on the basis of a new interpretation of distributed parameter systems (DPS) - by means of Lumped input and distributed output systems (LDS). The new concept of control theory: LDS gives wide possibilities for the solution of these problems also in intentions of LOW COST AUTOMATION.

关键词： QUANTITIES FIELDS distributed parameter system LUMPED INPUT AND distributed OUTPUT system LUMPED parameter system distributed parameter systemS OPTIMAL DESIGN CONTROL COMPUTER AIDED DESIGN OF distributed parameter systemS OF CONTROL

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A Fourier Space Basis Function Based 3D Modeling Method for distributed parameter systems 40

A Fourier Space Basis Function Based 3D Modeling Method for ...

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40th Chinese Control Conference (CCC)

作者： Zhang, Xianxia Li, Zhiyuan Yan, Runbin Shanghai Univ Sch Mechatron & Automat Shanghai Key Lab Power Stn Automat Technol Shanghai 200444 Peoples R China

ISBN: (纸本)9789881563804

A fourier space basis function based 3D fuzzy modeling method for distributed parameter systems is proposed in this paper. Unlike the traditional modeling method with model reduction, 3D fuzzy modeling integrates the time-space seperation and the time-space sysnsis into a 3D fuzzy model framework naturally. In this study, the construction of the 3D fuzzy model is of data-driven style. The antecedent parts of the 3D fuzzy rules is learned by Affinity Propagation Clustering algorithm. Fourier space basis function is considered as the concequent set of the 3D fuzzy rule, and its parameters are learned by the gradient descent algorithm. The proposed modeling method is successful applied to a simulated parabolic rod reactor system. In comparison with other modeling methods, the simulation results validate the superiority of the proposed modeling method.

关键词： Fuzzy modeling 3D fuzzy system Affinity Propagation Clustering distributed parameter system

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On approximation and implementation of transformation based feedback laws for distributed parameter systems

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IFAC-PapersOnLine 2017年第1期50卷 6786-6792页

作者： Woittennek F. Riesmeier M. Ecklebe S. Institute of Automation and Control Engineering University of Health Sciences Medical Informatics and Technology Hall in Tirol 6060 Austria Institute of Control Theory Technische Universität Dresden Dresden 01069 Germany

This paper presents an approach for the efficient numerical implementation of transformation based state feedback laws for linear distributed parameter systems. The control laws considered may originate from backstepping or flatness-based design methods. They are, therefore, directly based on the underlying distributed parameter systems. In general, they are given as unbounded functionals on the infinite-dimensional state-space. By approximating a carefully chosen bounded part, the implementation of these feedback-operators can be considerably simplified. This is achieved by approximating the state in appropriate finite-dimensional sub-spaces of the state-space. The choice of these sub-spaces as well as the controller implementation are discussed for both, a particular motivating example specific and the general case. For the implementation and validation of the obtained approximated controllers the python-based software toolbox PyInduct is introduced. © 2017

关键词： backstepping distributed parameter system feedback control flatness hyperbolic system late lumping parabolic system state feedback

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Robust sampled-data control of a class of distributed parameter systems using mobile actuator-sensor networks 11

Robust sampled-data control of a class of distributed parame...

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11th World Congress on Intelligent Control and Automation

作者： Qian, Xueming Cui, Baotong Jiangnan Univ Sch Internet Things 1800 Lihu Rd Wuxi Jiangsu Peoples R China

ISBN: (纸本)9781479958252

This paper study the sampled-data control problem of a class of distributed parameter systems. A novel sampled-data control scheme is presented using mobile actuator-sensor networks. By utilizing a Lyapunov functional which depend on spatial parameter, a controller combine to decentralized static output feedback control scheme and the point measurement of the mobile sensor is designed to derive several sufficient criteria ensuring the distributed parameter systems to be globally asymptotically stable. The criteria are given in the form of linear operator inequalities and the velocity law of each mobile actuator/sensor. It is also shown that static sampled-data control of distributed parameter systems is just a special case of our main results. A numerical simulations illustrate the effectiveness of the proposed control scheme in enhancing system performance.

关键词： distributed parameter system Sampled-data control Mobile sensor Mobile actuator

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Decentralized sliding mode controller for interconnected distributed parameter systems with time delays

Decentralized sliding mode controller for interconnected dis...

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UKACC International Conference on Control 98

作者： Xie, ZD Xie, SL Liu, YQ S China Univ Technol Guangzhou Peoples R China

ISBN: (纸本)085296708X

In the paper, the decentralized sliding mode controller design problem for interconnected distributed parameter systems with time delays is discussed by M-matrix theory, Lp-estimation and Lyapunov methods. Firstly, the sliding manifold so that the sliding mode motion equation is asymptotically stable in Sobolve space W-1,W-2 is designed;Secondly, the completely decentralized sliding mode controller so that the system realized motion of the sliding modes is designed. Finally, the estimation of time T for system's solution arrived on sliding manifold is given.

关键词： decentralized control sliding mode time delay distributed parameter system

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Output feedback stabilization for distributed parameter systems based on mobile sensor-actuator networks with random measurement delays 33

Output feedback stabilization for distributed parameter syst...

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33rd Chinese Control and Decision Conference (CCDC)

作者： Zhang, Jianzhong Lv, Guili Li, Xiaoqian Jiang, Zhengxian Taishan Univ Sch Math & Stat Tai An 271000 Shandong Peoples R China Jiangnan Univ Sch Sci Wuxi 214122 Jiangsu Peoples R China

ISBN: (纸本)9781665440899

This paper considers the problem of output feedback stabilization for a class of distributed parameter system. By using the abstract evolution equation of the distributed parameter system, a kind of output feedback control law is designed which is executed by mobile sensor and actuator networks with random measurement delays. Then, sufficient conditions are obtained to stabilize the state of the system by the Lyapunov stability arguments. Meanwhile, control forces to guide the operations of mobile agents are presented which show that the agents' trajectories are greatly affected by the probabilities of the random measurement delays. Finally, the MATLAB simulations verify the correctness and effectiveness of the proposed method.

关键词： distributed parameter system output feedback mobile sensor-actuator network random measurement delay

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Iterative Learning Control for distributed parameter systems Based on Actuator-Sensor Network 7

Iterative Learning Control for Distributed Parameter Systems...

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7th International Conference on Information Science and Technology (ICIST)

作者： Zhang, Jianxiang Cui, Baotong Lou, Xuyang Jiangnan Univ Sch IoT Engn Wuxi 214122 Peoples R China

ISBN: (纸本)9781509054015

The iterative learning control technique is generalized to distributed parameter systems based on actuator-sensor network. Firstly, an open-loop D-type and a closed-loop D-type ILC schemes are presented for a class of distributed parameter system with single sensor-actuator respectively. Then, we derive sufficient conditions for tracking error convergence. Secondly, we consider distributed parameter systems with multiple sensors-actuators and obtain the convergence of tracking error under an open-closed-loop D-type ILC scheme. The numerical simulation results illustrate the effectiveness of the proposed ILC schemes.

关键词： iterative learning control distributed parameter system actuator-sensor network

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