Adaptive fuzzy pole placement for stabilization of non-linear systems
نویسنده
چکیده
A new approach is proposed for the pole placement of non-linear systems using the state feedback and fuzzy system. We use a new online fuzzy training method in order to identify and obtain a fuzzy model for an unknown non-linear system using only the system input and output. Then we linearize this identified model at each sampling time to have an approximate linear time-varying system. In order to stabilize the linear system obtained, we first choose the desired time-invariant closed-loop matrix, and then a time-varying state feedback is used. The behavior of the closed-loop non-linear system is regarded as a linear time-invariant (LTI) system. Therefore, the advantage of the proposed method is the global asymptotical exponential stability of unknown non-linear systems. Due to the high speed convergence of the proposed adaptive fuzzy training method, the closed-loop system is robust against uncertainty in system parameters. Finally, a comparison is made with the boundary layer sliding mode control (SMC).
منابع مشابه
Adaptive fuzzy pole placement for stabilization of non-linear systems
A new approach for pole placement of nonlinear systems using state feedback and fuzzy system is proposed. We use a new online fuzzy training method to identify and to obtain a fuzzy model for the unknown nonlinear system using only the system input and output. Then, we linearized this identified model at each sampling time to have an approximate linear time varying system. In order to stabilize...
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