The stabilisation problem of linear, time-invariant, large-scale, composite systems with delays in the interconnections without any additional assumption on system structure are considered. It is shown basically that ...
The stabilisation problem of linear, time-invariant, large-scale, composite systems with delays in the interconnections without any additional assumption on system structure are considered. It is shown basically that time-delays in the interconnections do not create additional difficulties. The main results presented demonstrate that stabilisation control by the local memoryless state feedback for this class of systems is always possible.
This paper considers the problem of globally asymptotic stabilization of multi-input multi-output bilinear systems with undamped natural response. It firstly presents a simple sufficient condition for construction of ...
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ISBN:
(纸本)0780343948
This paper considers the problem of globally asymptotic stabilization of multi-input multi-output bilinear systems with undamped natural response. It firstly presents a simple sufficient condition for construction of a static state feedback controller. Then under an additional condition on system detectability, two output dynamic feedback controllers with saturation bounded control are constructed. The globally asymptotic stability of the closed loop systems using these controllers are established by using Lyapunov stability approach.
The paper addresses the problem of design of a robust controller for a class of nonlinear uncertain systems to guarantee the prescribed decay rate of exponential stability. The bounded deterministic uncertainties are ...
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ISBN:
(纸本)9783952426906
The paper addresses the problem of design of a robust controller for a class of nonlinear uncertain systems to guarantee the prescribed decay rate of exponential stability. The bounded deterministic uncertainties are considered both in a studied system and its input part. The proposed approach does not employ matching conditions.
The paper addresses the problem of robust decentralized control design which guarantee exponential stability of uncertain linear complex systems with output feedback. No matching conditions are demanded for modelling ...
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The paper addresses the problem of robust decentralized control design which guarantee exponential stability of uncertain linear complex systems with output feedback. No matching conditions are demanded for modelling the uncertain system, where the uncertainties, which are possibly nonlinear, may appear in the subsystems as well as in the interconnections.
The paper presents an application-oriented robust decentralized control design technique based upon the sufficient condition for robust stability (SCRS) of systems under decentralized control (DC) which is fulfilled u...
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The paper presents an application-oriented robust decentralized control design technique based upon the sufficient condition for robust stability (SCRS) of systems under decentralized control (DC) which is fulfilled using parameter tuning of fixed-structure local controllers. Graphical interpretation of the SCRS provides two useful stability criteria used to test stability of the overall system as well as stability of subsystems. Theoretical results are illustrated in a case study.
As an alternative to the defuzzification a new computation method of fuzzy logic controller output is presented. In connection with this method an other procedure is proposed, which allowes to substitute also for fuzz...
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As an alternative to the defuzzification a new computation method of fuzzy logic controller output is presented. In connection with this method an other procedure is proposed, which allowes to substitute also for fuzzification. It uses the same knowledge base in the form of a rule-table like the fuzzy logic controller, but without using the fuzzy logic. The proposed algorithm is simple and the results which where verified in simulation and in the real-time control as well are the same like with fuzzy logic controllers.
The aim of the work is to present the state-of-the-art in this filed of adaptive control. Some development trends based especially on the general stability theory are analyzed. The characteristics of basic model refer...
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The aim of the work is to present the state-of-the-art in this filed of adaptive control. Some development trends based especially on the general stability theory are analyzed. The characteristics of basic model reference adaptive control (MRAC) structures and algorithms are given in order to provide an insight into the development of the theory and to indicate the possibilities of their practical application. As the paper makes only a survey of the subject area, the stability proofs of the presented algorithms are omitted. The plant to be controlled is assumed to be described by a linear model.
In this paper an application of the H ∞ -optimal position control of a hydraulic drive is presented. The treatment of model uncertainties in the field of robust control is demonstrated and an analysis for the two mos...
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In this paper an application of the H ∞ -optimal position control of a hydraulic drive is presented. The treatment of model uncertainties in the field of robust control is demonstrated and an analysis for the two most important kinds of uncertainties is presented. Main goal is to portray the relation between the weighting functions and the performance and robustness of the controlled system. On the basis of this detailed analysis, a set of simple tuning rules for the appropriate selection of the weighting functions is derived. A software package for the analysis of the plant and the selection of the weighting functions has been developed and successfully applied to a hydraulic drive.
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...
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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.
This paper presents a model-based approach to fault detection of dynamic systems, which is robust to unmodeled dynamics. A “Quasi-ARMAX model᾿ is first proposed for describing nonlinear systems by incorporating a gro...
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This paper presents a model-based approach to fault detection of dynamic systems, which is robust to unmodeled dynamics. A “Quasi-ARMAX model᾿ is first proposed for describing nonlinear systems by incorporating a group of certain nonlinear structures into a linear ARMAX structure. The model can be used for a best linear approximation of the system, as well as for the estimation of resulting unmodeled dynamics, by a hierarchical implementation of recursive identification. Then robust fault detection is performed based on thresholding approach using Kullback discrimination information as fault detection index, in which the estimated unmodeled dynamics is incorporated.
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