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Pole Placement controller Design Based on Fuzzy Process Model

IFAC Proceedings Volumes 2000年第28期33卷 219-224页

作者： Robert Cupec Nedjeljko Perić Ivan Petrović Department of Control and Computer Engineering in Automation Faculty of Electrical Engineering and Computing university of Zagreb Unska 3 10000 Zagreb Croatia

An explicit self-tuning controller based on the Takagi-Sugeno fuzzy model of the process is proposed. The fuzzy model is represented as a linear regression model whose parameters are functions of some of the process variables. Such a model can be considered as a linear time-varying model whose parameter values are known at every moment. The pole placement design procedure modified for time-varying systems is applied to obtain the polynomial controller parameters that provide the desired closed-loop poles. The proposed algorithm is very simple, and thus suitable for on-line controller design in adaptive control systems.

关键词： fuzzy control fuzzy modeling adaptive control

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Model structure selection for nonlinear system identification using feedforward neural networks

Model structure selection for nonlinear system identificatio...

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International Joint Conference on Neural Networks (IJCNN)

作者： I. Petrovic M. Baotic N. Peric Faculty of Electrical Engineering and Computing Department of Control and Computer Engineering in Automation University of Zagreb Zagreb Croatia

The majority of nonlinear models based on neural networks are of the black-box structure. A nonlinear system can be nonlinear in many different ways, thus the nonlinear black-box model structure must be very flexible. This means that it must have many parameters. A model offering many parameters usually creates problems, and the variance contribution to the error might be high. For a particular identification problem, only a subset of the parameters may be necessary, and the main topic in nonlinear system identification is how to select a model structure that describes the system dynamics with the minimum number of parameters. This paper discusses nonlinear input-output models that are suitable for implementation of feedforward neural networks. The proposed model structures were tested and compared using the identification procedure of a pH process. The results indicated that a simplest model structure can satisfactorily represent the investigated process.

关键词： Nonlinear systems Neural networks Feedforward neural networks Nonlinear dynamical systems control engineering computing Computer networks Predictive models Automatic control Nonlinear control systems Automation

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Refinement of fuzzy production rules by neuro-fuzzy networks

Refinement of fuzzy production rules by neuro-fuzzy networks

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IEEE International Conference on Systems, Man and Cybernetics

作者： E.C.C. Tsang Shenshan Qiu D.S. Yeung Department of Computing Hong Kong Polytechnic University Hong Kong China Department of Automatic Control Engineering South China University of Technology Guangzhou China

The knowledge acquisition bottleneck is well-known in the development of fuzzy knowledge based systems (i.e. FKBSs), and knowledge maintenance and refinement are important issues. The paper improves fuzzy production rule (FPR) representation power by exploiting prior knowledge and develops refinement tools which assist in debugging a FKBS's knowledge, thus easing the knowledge acquisition and maintenance bottlenecks. We focus on knowledge refinement where the FKBS's knowledge is debugged or updated in reaction to evidence that the FKBS is faulty or out-of-date. Some of the applied methods are presented. To select a feasible fuzzy rule set for classification, the most difficult task is finding a set of rules pertaining to the specific classification by choosing adaptive knowledge representation parameters such as local and global weights in fuzzy rules. We map the weighted fuzzy rules to a new neural network (five-layer-based knowledge neural network) so the knowledge representation parameters can be refined and fuzzy rule representation power can be improved. The dynamic assigning neuron method, gradient-descent method with penalizing functions and evolving strategy are considered. We show that this refinement method can maintain the accuracy and improve the comprehensibility and representation power of FPRs. Experiments on a special domain indicate that the refinement method and evolving strategy are able to significantly increase an FPR's representation power when compared with standard fuzzy knowledge-based networks.

关键词： Fuzzy neural networks Refining Production Knowledge acquisition Fuzzy sets Knowledge representation Neural networks Fuzzy systems Knowledge based systems Debugging

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Convergence of discrete Hopfield-type neural networks with delay

Convergence of discrete Hopfield-type neural networks with d...

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American control Conference (ACC)

作者： Shenshan Qiu Yongqing Liu T.S. Dillon Renguo Xiao Department of computing Hong Kong Polytechnic University Hong Kong China Department of Automatic Control and Engineering South China University of Technology Guangzhou China

An important property of discrete Hopfield-type neural networks is that it always converges to a stable state when operating in a serial mode and to a cycle of length at most 2 when operating in a full parallel mode. In this paper, convergence theorems of discrete Hopfield-type neural networks with delay are obtained. Under a proper assumption, i.e., which weight matrix is a symmetric matrix, it is proved that any discrete Hopfield-type neural networks with delay will converge to a stable state operating in serial mode, and extends convergence theorems in earlier works. The authors also relate the maximum of bivariate energy function to the stable state of neural networks with delay. In other words, this network can converge to a stable state in only one delay step while the energy function has converged. The correlation between convergence of the energy function and convergence corresponding to the network is also presented.

关键词： Convergence Neural networks Hopfield neural networks Neurons Equations Delay effects Computer networks Computational modeling Sufficient conditions

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Vertex results for parametric shifted H/sub /spl infin// performance of weighted interval plants

Vertex results for parametric shifted H/sub /spl infin// per...

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IEEE Conference on Decision and control

作者： Sen-Jian An Xiheng Hu Branka Vucetic Wanquan Liu School of Electrical &d Information Engineering University of Sydney Australia Department of Automatic Control Beijing Institute of Technology Beijing China School of Computing Curtin University of Technology Australia

This paper considers the parametric shifted H/sub /spl infin// problem of weighted interval plants. A sufficient condition is obtained on weighting function W(s) such that for any interval plant P(s, q, r) the maximal... 详细信息

ISBN: (纸本)0780366387

关键词： Polynomials Transfer functions Robust control Robust stability Sufficient conditions Uncertainty Adaptive control Robustness Frequency Automatic control

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Application of a neural predictive controller in boost converter input current control

Application of a neural predictive controller in boost conve...

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IEEE International Symposium on Intelligent control (ISIC)

作者： I. Petrovic M. Baric A. Magzan N. Peric Fac. of Electr. Eng. Zagreb Univ. Croatia Faculty of Electrical Engineering and Computing Department of Control and Computer Engineering in Automation University of Zagreb Zagreb Croatia College of Electrical Engineering Polytechnics College of Zagreb Zagreb Croatia

The application of a nonlinear predictive controller in the cascade control structure of a boost converter is investigated. The neuro-predictive controller is realized as a nonlinear optimizer, using the Levenberg-Marquardt unconstrained optimization procedure. For the prediction of future process responses, two MLP neural networks are used. One network is used for modeling the converter dynamics and the other for online estimation of the converter's input voltage. This structure ensures good system performance in all operating regions and inherent compensation of ripples in the converter's input current caused by variations of the input voltage. The advantages of the proposed control structure are demonstrated through experimental comparison with a linear GPC with manually adjusted feedforward compensator.

关键词： Current control Voltage control control systems Automatic control Pulse width modulation Switches Rail transportation Current measurement Electric current control Application software

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Adaptive Fuzzy Ship Autopilot for Track-Keeping

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IFAC Proceedings Volumes 2000年第21期33卷 129-134页

作者： Jasmin Velagic Zoran Vukic Edin Omerdic University of Sarajevo Faculty of Electrical Engineering Skenderija 70 BH-71000 Sarajevo Bosnia and Herzegovina fax : (+387 71) 654 972 University of Zagreb Faculty of Electrical Engineering and Computing Department of Control and Computer Engineering in Automation Unska 3 HR-10000 Zagreb Croatia fax : (+385 1) 612 98 09 University of Tuzla Faculty of Electrical and Mechanical Engineering Franjevacka 2 BH-75000 Tuzla Bosnia and Herzegovina

We develop in this paper an adaptive fuzzy gain autopilot for ship track-keeping. This autopilot is composed of Sugeno fuzzy type autopilot in an ordinary feedback loop and adjustable scaling factors mechanism in an additional feedback loop. The adjustment mechanism represents a fuzzy controller that changes scaling factors of the base fuzzy autopilot. The control system for the track-keeping is completely described. For the track-keeping problem, the maneuver of way-point turning and ship guiding through a complex path (trajectory) are presented. The influence of sea current and wave disturbances on track-keeping performance was also considered. We first present simulation results obtained by the Sugeno fuzzy type autopilot. Then, we compare those results with ones obtained by an adaptive fuzzy autopilot.

关键词： Adaptive fuzzy control track-keeping fuzzy gain concept disturbance rejection ship control

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Empirical studies of evolving systems

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Empirical Software engineering 1999年第4期4卷 370-380页

作者： Bennett, K. Burd, E. Kemerer, C. Lehman, M.M. Lee, M. Madachy, R. Mair, C. Sjoberg, D. Slaughter, S. Department of Computer Science University of Durham United Kingdom Katz Graduate School of Business University of Pittsburgh United States Department of Computing Imperial College United Kingdom Department of Informatics and Simulation RMCS Cranfield University United Kingdom Litton Guidance and Control Systems USC Center for Software Engineering United States Design Engineering and Computing University of Bournemouth United Kingdom Department of Informatics University of Oslo Norway Graduate School of Industrial Administrations Carnegie Melon University United States

This paper describes the results of the working group investigating the issues of empirical studies for evolving systems. The groups found that there were many issues that were central to successful evolution and this concluded that this is a very important area within software engineering. Finally nine main areas were selected for consideration. For each of these areas the central issues were identified as well as success factors. In some cases success stories were also described and the critical factors accounting for the success analyzed. In some cases it was later found that a number of areas were so tightly coupled that it was important to discuss them together.

关键词： Software engineering

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Comparative analysis of Mamdani and Sugeno type fuzzy autopilots for ships

Comparative analysis of Mamdani and Sugeno type fuzzy autopi...

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1999 European control Conference, ECC 1999

作者： Vukic, Z. Velagic, J. University of Zagreb Faculty of Electrical Engineering and Computing Department of Control and Computer Engineering in Automation Unska 3 ZagrebHR-10000 Croatia University of Sarajevo Faculty of Electrical Engineering Skenderija 70 SarajevoBH-71000 Bosnia and Herzegovina

ISBN: (纸本)9783952417355

In this paper a comparative analysis of Mamdani and Sugeno type fuzzy autopilots for ships is given. Both autopilots have two inputs: the heading signal and the yaw rate signal, and only one output: command rudder angle. Input variable fuzzification, fuzzy associative memory (FAM) rules, and output set defuzzification are described. The control system for the course-keeping composed of the nonlinear ship, the steering gear servo system, fuzzy autopilot and wave disturbance is described. Both autopilots are compared in three different sailing conditions: without wave disturbance, with wave disturbance and with wave disturbance and wave filtering. The notch filter was used for filtering of second-order wave disturbances. The influence of wave disturbance on course-keeping performance was analyzed. Even though the obtained performance in simulations are very similar, authors prefer Sugeno type fuzzy autopilot, due to less strain of the steering gear servo system and faster and more accurate heading obtained. © 1999 EUCA.

关键词： Ships

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control of autonomous robots using fuzzy logic controllers tuned by genetic algorithms

Control of autonomous robots using fuzzy logic controllers t...

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1999 Congress on Evolutionary Computation, CEC 1999

作者： Arsene, C.T.C. Zalzala, A.M.S. Faculty of Control and Computers University Politechnica of Bucharest Romania Department of Computing and Electrical Engineering Heriot-Watt University Edinburgh EH14 4AS United Kingdom

ISBN: (纸本)0780355369

Truly autonomous vehicles will require both projective planning and reactive components in order to perform robustly. Projective components are needed for long term planning and re-planning where explicit reasoning about future states is required. Reactive components allow the system to always have some action available in real time, and themselves can exhibit robust behaviour, but lack the ability to explicitly reason about future states over a long time period. The paper emphasises creating the projective component but also offer a simple solution for reactive component. A genetic algorithm implements the projective component, which designs automatically a fuzzy logic controller by modifying the position of controller membership functions and the commands given to the robot. For the reactive component, a simple solution was adopted so that if the robot sensors detect new obstacles, the robot will try to move to a previous position. © 1999 IEEE.

关键词： Genetic algorithms

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