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This paper presents a novel approach to control general nonlinear systems based on Takagi-Sugeno (T-S) fuzzy dynamic models. It is first shown that a general nonlinear system can be approximated by a generalized T-S fuzzy model to any degree of accuracy on any compact set. It is then shown that the stabilization problem of the general nonlinear system can be solved as a robust stabilization problem...
A novel approach to control of general nonlinear system based on T-S fuzzy model is presented in this paper. Firstly, it is shown that a general nonlinear system can be approximated by a generalized T-S fuzzy model to arbitrary degree of accuracy on any compact set. And the basic idea of the proposed approach is to stabilize the general nonlinear system by solving a robust stabilization problem of...
This paper proposes an incremental construction learning algorithm for identification of T-S fuzzy Systems. The mechanism of the algorithm is that it is an error-reducing driven learning method. Beginning with a simplest T-S fuzzy system, the algorithm develops the system structure by adding more fuzzy terms and rules to reduce the model errors in a dasiagreedypsila way. The main features of the proposed...
This paper investigates the stabilization of conventional nonlinear systems by fuzzy control approach. Firstly, it is shown that the class of nonlinear systems whose stabilization problem can be solved by the fuzzy control approach available today based on T-S fuzzy control models is affine nonlinear systems as this is the only class of nonlinear systems which can be approximated to any degree of...
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