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In this article, nonlinear systems are described by T-S fuzzy models, by which controlling nonlinear systems is converted into controlling a series of partial linear systems. In order to control every partial linear system, an optimal control scheme is proposed and thus the problem of controlling nonlinear systems is resolved. The ability of the proposed control method in stabilizing the unstable...
In this paper, an adaptive intelligent tracking control (AITC) system employs an output recurrent cerebellar model articulation controller (ORCMAC) is developed for uncertain nonlinear system. In the AITC design, the Taylor linearization technique is employed to increase the learning ability of ORCMAC and the on-line adaptive laws are derived based on the Lyapunov stability analysis and the Hinfin...
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