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American control Conference (ACC)

作者： P. Balle D. Juricic A. Rakar S. Ernst Institute of Automatic Control Laboratory of Control Engineering and Process Automation Technical University of Darmstadt Darmstadt Germany Department of Computer Automation and Control Jozef Stefan Institute Ljubljana Slovenia

Deals with identification of nonlinear processes and model-based fault detection/isolation (FDI). The applicability of the proposed methods is illustrated on a three-tank laboratory setup. The process identification is based on the local linear model tree (LOLIMOT) algorithm and leads to local linear models. The parameters of the local models are used for generation of structured residual equations, similar to the well-known parity space approach. This enables detection and isolation of five different sensor faults of the three-tank process, continously over all ranges of operation.

关键词： Fault diagnosis Fault detection Automatic control Power system modeling Valves Laboratories DC motors automation Neural networks Benchmark testing

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A neural network controls the galvannealing process

A neural network controls the galvannealing process

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Conference Record of the IEEE Industry Applications Society Annual Meeting (IAS)

作者： C. Schiefer F.X. Rubenzucker H.P. Jorgl H. Aberl Laboratory for Intelligent Control Methods for Process Technologies Institute for Machine and Process Automation Vienna University슠of슠Technology Vienna Austria Electrical Engineering and Process Control Research and DevelopmentDepartment TAW Voest-Alpine Industrieanlagenbau GmbH Linz Austria

High quality galvanized steel strip is a need of today's manufacturers of various products. In particular, in the top quality section steel strips for the automotive, building and consumer goods industries only those steel producers will be successful who are applying state-of-the-art process technologies. For this reason, VOEST-ALPINE Industrieanlagenbau mbH (VAI) and VOEST-ALPINE Stahl Linz developed a new galvannealing control system to optimize this metallurgical process. As the latest improvement of the galvannealing control strategy, a neural network controller has been developed by VAI in Cooperation with the Vienna University of Technology Christian Doppler Laboratory for Intelligent control Methods for process Technologies. The paper describes the galvannealing process as far as it is necessary for the understanding of the controller functions, the controller structure and its essential functions. Furthermore, the neural network structure used and its integration into the controller system are explained. A discussion of simulation and practical operating results shows the improvements achieved by using a neural network controller in comparison to the conventional controller.

关键词： Neural networks process control Steel Strips electrical equipment industry Manufacturing industries Metals industry control systems Galvanizing Automotive engineering

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Kinematic analysis of artificial biped locomotion systems

Kinematic analysis of artificial biped locomotion systems

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IEEE International Conference on Intelligent engineering Systems (INES)

作者： F.M. Silva J.A. Tenreiro Machado Department of Control and Automation Modern University Portugal Department of Electrical and Computer Engineering Faculty of Engineering University of Porto DEEC Portugal

This paper presents the kinematic study of robotic biped locomotion systems. The main purpose is to determine the kinematic characteristics and the system performance during walking. For that objective, the prescribed motion of the biped is completely characterised in terms of five locomotion variables: step length, hip height, maximum hip ripple, maximum foot clearance and link lengths. In this work, we propose three methods to quantitatively measure the performance of the walking robot: locomobility measure, perturbation analysis, and low pass frequency response. These performance measures are discussed and compared in determining the robustness and effectiveness of the resulting locomotion.

关键词： Kinematics Legged locomotion Hip Frequency measurement Robots System performance Foot Performance analysis Frequency response Robustness

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Nonlinear predictive control based on the extraction of step-response models from Takagi-Sugeno fuzzy systems

Nonlinear predictive control based on the extraction of step...

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American control Conference (ACC)

作者： M. Fischer M. Schmidt K.K. Kavsek-Biasizzo Institute of Automatic Control Laboratory of Control Systems and Process Automation Technical University of Darmstadt Darmstadt Germany Faculty of Electrical Engineering University of Ljubljana Ljubljana Slovenia

This paper deals with nonlinear predictive control based on higher order Takagi-Sugeno fuzzy systems which can also be interpreted as generalized radial basis function networks. We investigate how the fuzzy models can be linked to a special type of model based predictive control algorithm, namely the dynamic matrix control (DMC). Previously, purely linear step response models were used for long-range prediction. Here, the method is extended to nonlinear processes. Therefore, various step responses for different operating points are extracted from the fuzzy model. For performance evaluation, a heat exchanger is identified by means of the local linear model tree algorithm and controlled by the modified DMC.

关键词： Predictive control Predictive models Takagi-Sugeno model Fuzzy systems Automatic control Laboratories Radial basis function networks Fuzzy control control system synthesis Nonlinear control systems

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Modelling and Parameter Identification of Discontinuous Wiener Systems

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IFAC Proceedings Volumes 1997年第21期30卷 49-54页

作者： Jozef Vörös Slovak Technical University Faculty of Electrical Engineering and Information Technology Department of Automation and Control Ilkovicova 3 812 19 Bratislava Slovakia

The paper deals with the decomposition of block-oriented nonlinear dynamic systems having discontinuous asymmetric nonlinearities and with their identification using the Wiener model. Multiple application of a simple decomposition technique provides a special form of Wiener model with the minimum number of parameters. Putting some parameters of the proposed model to zero, models for the block-oriented nonlinear dynamic systems with pure preload nonlinearities, dead zone or two-segment piecewise-linear asymmetric nonlinearities are obtained. To demonstrate the feasibility of the identification method, more illustrative examples are included.

关键词： Nonlinear system identification discontinuous nonlinearities Wiener model

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Design of Hybrid control Systems Based on the Robust Pole Region Assignment Approach

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IFAC Proceedings Volumes 1997年第21期30卷 25-30页

作者： M. Budinský Š. Kozák M. Žalman Department of Control and Automation Faculty of Electrical Engineering and Information Technology Slovak Technical University Ilkovičova 3 812 19 Bratislava Slovak Republic

The paper deals with the robust synthesis and analysis of control systems with a hybrid structure which consists of a sampled continuous process and a discrete control algorithm. A method for the design of digital controllers for processes with uncertain physical plant parameters is presented. The Robust Pole Region Assignment and the Algebraic Approach to the Output Feedback Based Pole Placement in the discrete domain are applied. The paper proposes also a new robust stability/performance criterion for hybrid systems with interval parametric uncertainties. An application example is included.

关键词： Robust control Digital control Algebraic Systems Theory Diophantine equations Robust Pole Region Assignment Approach Hybrid control Structure

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Knowledge extraction from artificial neural network models

Knowledge extraction from artificial neural network models

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IEEE International Conference on Systems, Man and Cybernetics

作者： Z. Boger H. Guterman Intelligent Process Control Systems Beersheba Israel Department of Electrical and Computer Engineering Ben-Gurion University of the Negev Beersheba Israel

The paper describes the development and application of several techniques for knowledge extraction from trained ANN models, such as the identification of redundant inputs and hidden neurons, derivation of causal relationships between inputs and outputs, and analysis of the hidden neuron behavior in classification ANNs. An example of the application of these techniques is given of the faulty LED display benchmark. References of the application of these techniques are given of diverse large scale ANN models of industrial processes.

关键词： Artificial neural networks Neurons Large-scale systems Power system modeling Industrial training Predictive models Data mining Electronic mail Industrial relations Industrial plants

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Dynamic Positioning of Floating Vessels Postoptimal Analysis

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IFAC Proceedings Volumes 1997年第22期30卷 183-186页

作者： S. Mandžuka Z. Vukić Control Engineering Department Brodarski institute d.o.o. Av. V. Holjevca 20 10000 Zagreb CROATIA Department of Control and Computer Engineering in Automation University of Zagreb Faculty of Electrical Engineering and Computing Unska 3 10000 Zagreb CROATIA

A procedure for the postoptimal analysis of dynamic positioning control system of floating vessels is proposed. The control system design is based on the optimal constrained covariance control (OC 3 ). Using the OC 3 technique, the disadvantages of the classical LQG optimal control technique are avoided. The presented numerical example illustrates the properties of the new approach.

关键词： Positioning system LQG control Optimization problems

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Robustness Properties of Extended Horizon Nonlinear Predictive control Strategies Applied for the Hammerstein Model

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IFAC Proceedings Volumes 1997年第16期30卷 321-325页

作者： Robert Haber Ruth Bars Zoltán Czipríán Department of Process Engineering Laboratory of Process Control Cologne Institute of Technology D-50679 Köln Betzdorfer Str. 2 Germany Department of Automation Technical University of Budapest H-1111 Budapest Goldmann Gy. tér 3 Hungary

Predictive control algorithms are promising also in the case of nonlinear systems. Two versions of extended horizon predictive control algorithms are given here for the nonlinear simple Hammerstein model. A quadratic cost function is minimized, which considers the quadratic deviation of the reference signal and the output signal predicted in a future point and also the squares of the control increments. The system model is transformed to a predictive incremental form. Two versions of suboptimal extended horizon control algorithms are given with different assumptions for the control signal during the control horizon. Robustness properties of these algorithms are considered in case of plant-model mismatch through some simulation examples.

关键词： Predictive control nonlinear control control algorithms suboptimal control robustness Hammerstein model

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control of multiple modular DC-to-DC power converters in conventional and dynamic sliding surfaces

Control of multiple modular DC-to-DC power converters in con...

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American control Conference (ACC)

作者： Yu.B. Shtessel O.A. Raznopolov L.A. Ozerov Department of Electrical and Computer Engineering University of Alabama Huntsville Huntsville AL USA Department of Automation and Remote Control Chelyabinsk Technical University Chelyabinsk Russia

Autonomous systems of electric power supply consisting of one common primary source of electric power supply and a set of multiple modular switched-controlled secondary sources of electric power supply (DC-to-DC power converters) are considered. The problem of the stabilization of the voltages transformed by the multiple modular switched-controlled secondary sources of electric supply is formulated and solved in conventional and dynamic local sliding surfaces. The robust decoupled linear desired behavior of the stabilization errors of the transformed voltages is guaranteed in local sliding modes. The desired quality of the voltage stabilization is achieved in dynamic sliding surfaces without measurement or estimation of disturbances (load currents).

关键词： DC-DC power converters Power supplies Sliding mode control Switching converters Voltage control Automatic control Robust control Batteries Robustness Current measurement

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