Due to the complexity of neural networks the problem of large computation requirements on computational devices where the network is trained or evaluated and slow network evaluation/training response can appear. The p...
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Two novel linear matrix inequality (LMI)-based procedures to receive stabilizing robust output feedback gain are presented. one of them being modification of previous results of (Oliveira et al..1999). The proposed ro...
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The problem of robust output feedback stabilization is studied. The new robust stability LMI condition including guaranteed cost and the respective simple control design procedure is developed. Though the proposed con...
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The problem of robust output feedback stabilization is studied. The new robust stability LMI condition including guaranteed cost and the respective simple control design procedure is developed. Though the proposed condition is sufficient, it is supposed not to be overly conservative. To reduce the conservatism parameter-dependent Lyapunov function is employed and an extra degree of freedom is included by using previous results of (Oliveira et al., 1999) and introducing other additional slack matrix and scalar parameters. The example is given to analyse and compare the obtained results with other ones.
A new type of knowledge adaptive control based on the closed-loop response recognition is proposed. This approach tries to mimic the behaviour of an expert, who has a lot of experience with the particular controlled s...
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The paper addresses the design of a robust output feedback controller for SISO systems using extremal transfer functions and the classical control theory approach. It focuses on robust stabilization of uncertain plant...
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An analysis of the transportation systems used in the flexible manufacturing systems is introduced in the paper. Based on the analysis a class of the transportation systems is delimited, whose modeling and control is ...
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controller design approach is described, which is based on genetic algorithms. The approach uses an optimisation procedure, where the cost function to be minimised consists of the closed-loop system simulation and a p...
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Discrete event systems (DES) describe the behavior of a plant as it evolves over time in accordance with the abrupt and asynchronous occurrence of events. Such systems are encountered in a variety of fields, for examp...
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An adaptive fuzzy controller is designed using a collection of fuzzy IF-THEN rules. Parameters of membership functions characterizing the linguistic terms in the fuzzy IF-THEN rules are changing according to some adap...
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Due to the complexity of neural networks the problem of large computation requirements on computational devices where the network is trained or evaluated and slow network evaluation/training response can appear. The p...
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Due to the complexity of neural networks the problem of large computation requirements on computational devices where the network is trained or evaluated and slow network evaluation/training response can appear. The problem is more evident when networks are compared to the conventional algorithms that run with low response time. In general this problem is being solved using by more powerful computational device or parallel systems. This paper deals with a neural network optimized for run on the real time controlsystem to obtain real time responses comparable to the conventional algorithms. Special effort is made for solving of the problem of optimal network structure with reflection to preserve or aproove original network qualities (approximation and generalization capability).
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