By Qing Gao
This thesis presents a scientific and quintessential resolution to an open challenge about the universality of dynamic fuzzy controllers. It offers a few novel rules and ways to varied matters together with common functionality approximation, common fuzzy types, common fuzzy stabilization controllers, and common fuzzy indispensable sliding mode controllers. The proposed regulate layout standards might be with ease proven utilizing the MATLAB toolbox. additionally, the thesis presents a brand new, easy-to-use kind of fuzzy variable constitution keep watch over. Emphasis is given to the purpose that, within the context of deterministic/stochastic structures more often than not, the authors are in truth discussing non-affine nonlinear platforms utilizing a category of generalized T-S fuzzy versions, which supply substantial capability in quite a lot of applications.
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Hespanha, J. P. (2005). Stabilization of nonlinear systems with limited information feedback. IEEE Transactions on Automatic Control, 50(6), 910–915. 3. , & Isidori, A. (2010). Robust asymptotic stabilization of nonlinear systems with non-hyperbolic zero dynamics. IEEE Transactions on Automatic Control, 55(4), 907–921. 4. Qu, Z. (1998). Robust control of nonlinear uncertain systems. New York: Wiley-Interscience. 5. Hahn, W. (1968). Stability of motion. Berlin: Springer. 6. Khalil, H. K. (2002).
Z N )z i . 6) i=1 Then one has the following result on the universal function approximation capability of the generalized T–S fuzzy models. 8) and where x¯ = [x1 , . . , xn , u 1 , . . , u m ]T ∈ m+n . 22 2 Universal Fuzzy Models and Universal Fuzzy Controllers … Proof Let f (x, u) = [ f 1 (x, u), . . , f n (x, u)]T , then f (x, u) = [ f (x1 , . . , xn , u) − f (0, x2 , . . , xn , u)] + [ f (0, x2 , . . , xn , u) − f (0, 0, x3 , . . , xn , u)] + · · · + [ f (0, . . , 0, xn , u) − f (0, .
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