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7th World Congress on Intelligent Control and Automation

作者： Qi, Chenkun Li, Han-Xiong City Univ Hong Kong Dept Mfg Eng & Eng Management Hong Kong Hong Kong Peoples R China

ISBN: (纸本)9781424421138

The distributed parameter system modeling from the input and output data is investigated. The spatio-temporal output of the system is measured at a finite number of spatial locations, while the input is assumed to be a finite-dimensional temporal variable. Firstly, Karhunen-Loeve (KL) decomposition is used for the time/space separation and the dimension reduction. Subsequently the spatio-temporal output is expanded in terms of a low dimensional Karhunen-Loeve spatial basis functions. Finally its temporal dynamic model is learned from the temporal coefficients by using least squares support vector machines (LS-SVM). The simulations are presented to show the effectiveness of this spatio-temporal modeling method.

关键词： distributed parameter system spatio-temporal modeling Karhunen-Loeve decomposition least squares support vector machines

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Decentralized Direct Adaptive Fuzzy-Neural Control of an Anaerobic Digestion Bioprocess Plant

Decentralized Direct Adaptive Fuzzy-Neural Control of an Ana...

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4th International IEEE Conference Intelligent systems

作者： Baruch, Ieroham S. Galvan-Guerra, Rosalba CINVESTAV IPN Dept Automat Control Mexico City 07360 DF Mexico

ISBN: (纸本)9781424417391

The paper proposed to use Fuzzy-Neural Multi-Model (FNMM) identification and control system for decentralized control of distributed parameter anaerobic wastewater treatment digestion bioprocess, carried out in a fixed bed and a recirculation tank The distributed parameter analytical model of the digestion bioprocess is reduced to a lumped system using the orthogonal collocation method, applied in three collocation points (plus the recirculation tank), which are used as centers of the membership functions of the fuzzyfied space variable of the plant. The states of the proposed FNMM identifier are implemented by a direct feedback-feedforward hierarchical FNMM controller. The comparative graphical simulation results of the digestion anaerobic system control, obtained via learning, exhibited a good convergence, and precise reference tracking outperforming the optimal control.

关键词： Anaerobic digestion bioprocess plant decentralized identification and control direct hierarchical fuzzy-neural multi-model control system distributed parameter system

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Variable structure control for uncertainty stochastic distributed parameter system

Variable structure control for uncertainty stochastic distri...

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8th International Conference on Control, Automation, Robotics and Vision (ICARCV 2004)

作者： Bao, JD Deng, FQ Luo, Q Zhao, BR S China Univ Technol Coll Automat Sci & Engn Guangzhou 510640 Peoples R China

ISBN: (纸本)0780386531

The variable structure control problem of a class of stochastic distributed parameter system with uncertainty is discussed. Variable structure dynamic equation is established by employing nonlinear transformation. The stability character has been analyzed. Based on previous conclusion, the variable structure regulator is designed for the system.

关键词： randomicity distributed parameter system variable structure control

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Stabilization of Multidimensional Wave Equations under Non-Collocated Controls and Observations

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IFAC Proceedings Volumes 2008年第2期41卷 11328-11333页

作者： Zhi-Chao Shao Bao-Zhu Guo Cui-Zhen Yao School of Computational and Applied Mathematics University of the Witwatersrand Wits 2050 Johannesburg South Africa Academy of Mathematics and Systems Science Academia Sinica Beijing 100080 P.R. China Department of Applied Mathematics Beijing Institute of Technology Beijing 100081 P.R. China

The objective of this paper is to deal with the stabilization of multi-dimensional wave equations under non-collocated control and observation with the following cases: a) internal distributed control and boundary observation; b) boundary control and internal distributed observation; c) locally internal distributed control and boundary observation.

关键词： distributed parameter system Exponentially stable Observers Non-collocated control and observation Wave equations

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A three-dimensional fuzzy control methodology for a class of distributed parameter systems

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IEEE TRANSACTIONS ON FUZZY systemS 2007年第3期15卷 470-481页

作者： Li, Han-Xiong Zhang, Xian-Xia Li, Shao-Yuan City Univ Hong Kong Dept Mfg Engn & Engn Management Hong Kong Hong Kong Peoples R China Shanghai Jiao Tong Univ Inst Automat Shanghai 200030 Peoples R China

The traditional fuzzy set is two-dimensional (2-D) with one dimension for the universe of discourse of the variable and the other for its membership degree. This 2-D fuzzy set is not able to handle the spatial information. The traditional fuzzy logic controller (FLD) developed from this 2-D fuzzy set should not be able to control the distributed parameter system that has the tempo-spatial nature. A three-dimensional (3-D) fuzzy set is defined to be made of a traditional fuzzy set and an extra dimension for spatial information. Based on concept of the 3-D fuzzy set, a new fuzzy control methodology is proposed to control the distributed parameter system. Similar to the traditional FLC, it still consists of fuzzification, rule inference, and defuzzification operations. Different to the traditional FLC, it uses multiple sensors to provide 3-D fuzzy inputs and possesses the inference mechanism with 3-D nature that can fuse these inputs into a so called "spatial membership function." Thus, a simple 2-D rule base can still be used for two obvious advantages. One is that rules will not increase as sensors increase for the spatial measurement;the other is that computation of this 3-D fuzzy inference can be significantly reduced for real world applications. Using only a few more sensors, the proposed FLC is able to process the distributed parameter system with little complexity increased from the traditional FLC. The 3-D FLC is successfully applied to a catalytic packed-bed reactor and compared with the traditional FLC. The results demonstrate its effectiveness to the nonlinear unknown distributed parameter process and its potential to a wide range of engineering applications.

关键词： distributed parameter system fuzzy logic controller fuzzy set three-dimensional fuzzy set

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Interval-valued fuzzy logic control for a class of distributed parameter systems

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INTERNATIONAL JOURNAL OF UNCERTAINTY FUZZINESS AND KNOWLEDGE-BASED systemS 2007年第4期15卷 457-481页

作者： Zhang, Xian-Xia Li, Shao-Yuan Li, Han-Xiong Shanghai Jiao Tong Univ Dept Automat Shanghai 200240 Peoples R China Cent S Univ Hunan Peoples R China City Univ Hong Kong Dept Mfg Engn & Engn Management Hong Kong Hong Kong Peoples R China

An interval-valued fuzzy logic controller (1-V FLC is presented to control a class of nonlinear distributed parameter systems. The proposed FLC is inspired by human operators' knowledge or expert experience to control a distributed parameter process from the point of view of overall space domain. Based on spatial fuzzy set, the I-V FLC employs a centralized rule base over the space domain. Using spatial membership degree fusion operation, the I-V FLC can compress spatial input information into interval-valued fuzzy sets and then execute an interval-valued rule inference mechanism;thereby the I-V FLC has the capability to process spatial information over the space domain. Compared with traditional FLCs, the I-V FLC can improve its control performance due to its increased ability to express and process spatial information. The I-V FLC is successfully applied to a catalytic packed-bed reactor and compared with the traditional FLCs. The results demonstrate its effectiveness to control the unknown nonlinear distributed parameter process.

关键词： interval-valued fuzzy set fuzzy logic controller distributed parameter system fuzzy control

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Neural Predictive Control Strategies for Continuous Bioreactor systems

Neural Predictive Control Strategies for Continuous Bioreact...

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The 12th Asian Pacific Confederation of Chemical Engineering Congress

作者： Wei Wu San-Yin Ding Department of Chemical and Materials Engineering,National Yunlin University of Science and Technology,Douliou,Yunlin 64002,Taiwan

A bioreactor system governed by the population balance equation(PBE)is denoted as the distributed parameter systems which are comprised of first-order partial differential equations (PDEs)coupled with ordinary differential equations(ODEs).Through time and space discreti- zation the explicit formulation of finitedifference model is *** effects of unknown

关键词： distributed parameter system feedforward neural network model predictive control dynamic dynamic backpropagation

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PROFILE CONTROL IN distributed parameter systemS USING LEXICOGRAPHIC OPTIMIZATION BASED MPC

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IFAC Proceedings Volumes 2007年第5期40卷 111-116页

作者： Nitin Padhiyar Sharad Bhartiya Department of Chemical Engineering Indian Institute of Technology Bombay Mumbai-400 076 India

We have studied control of spatial property in distributed parameter systems using a lexicographic optimization based MPC formulation to prioritize the different sections of the profile. We demonstrate using a hypothetical plug flow reactor that the proposed method has significant benefits when the target profile as a whole is unachievable but parts of which can be satisfied. We have also applied the proposed control strategy for property profile control in a continuous pulp digester of industrial size, which represents a large scale distributed parameter system.

关键词： distributed parameter system process control Kalman filters model based control pulp digester

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Cantilevered plate Rayleigh-Ritz trial function selection for von Karman's plate equations

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JOURNAL OF AIRCRAFT 2007年第2期44卷 654-661页

作者： Attar, Peter J. USAF Computat Sci Branch Wright Patterson AFB OH 45433 USA

The accuracy and convergence characteristics of the classical Rayleigh-Ritz solution of the nonlinear von Kariman plate equations are studied with respect to the types of cantilever plate in-plane trial functions used in the solution. The static deflection of the cantilever plate is computed for an applied static gravity loading. Four different in-plane trial function types are studied. In each of these cases the same out-of-plane trial functions are used. It is found that in two of the four cases good convergence and accuracy are achieved when compared to the solution from a nonlinear finite element model. The degree of satisfaction of the problem natural boundary conditions is also examined, and it is shown that for the two cases that show inadequate convergence characteristics this satisfaction is poor. It is noted in particular that for these two cases at points on the problems' free boundaries, the in-plane trial functions satisfy, either exactly or approximately, the linear in-plane natural boundary conditions. At these points the addition of inplane degrees of freedom to the solution will not contribute to the satisfaction of the nonlinear natural boundary condition. Thus for these two cases the convergence is poor as more in-plane trial functions are added to the solution. The change in the statically loaded plate natural frequencies are also computed. Similar to the static deflection results, convergence to the nonlinear finite element solution Is slow when in-plane trial functions are used that approximately satisfy the linear in-plane boundary conditions.

关键词： Finite Element Modeling Cantilever Plate Theory Membrane Stress Rayleigh Ritz Method Angle of Attack Supersonic Flow Elastic Modulus distributed parameter system Structural Mechanics

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Control and modeling of temperature distribution in a tubular polymerization process

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COMPUTERS & CHEMICAL ENGINEERING 2007年第11期31卷 1516-1524页

作者： Cao, Liulin Li, Dazi Zhang, Chunyu Wu, Haiyan Beijing Univ Chem Technol Dept Automat Beijing 100029 Peoples R China

Temperature distribution along tubular reactors reveals the process of a polymerization reaction, so that it can be used as an indicator to monitor polymer molecular weight distribution. In this study, model of temperature distribution in a tubular polymerization reaction was developed using a B-spline neural network in conjunction with a linear recurrent neural network for the control purpose. This provides a new method for modeling distributed parameter system. Both dynamic and static neural network were applied to resolve the modeling of distribution function from a high dimensional data set. The dynamic neural network describes the time relationship of distribution function and the manipulated variables, whereas the static neural network describes the algebraic relationship of temperature distribution and position in tubular reactor. Using the error set of the expected and the measured temperature distribution as control indexes, optimal control sequence based on the distribution model can be derived. An adaptive control strategy was investigated under conditions with un-measurable noises and disturbances. An extended integral square error (EISE) control index was proposed, which introduces the real-time model error into the control strategy. This provides a feedback channel for the control, and therefore largely enhances the robustness and anti-disturbance performance of the control method. Simulation results demonstrate the effectiveness of the proposed method. (c) 2007 Elsevier Ltd. All rights reserved.

关键词： polymerization tubular reactor distributed parameter system B-spline neural network optimal control

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