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   adaptive fuzzy pole placement for stabilization of non-linear systems  
   
نویسنده karami-mollaee a.
منبع journal of ai and data mining - 2016 - دوره : 4 - شماره : 2 - صفحه:169 -176
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).
کلیدواژه fuzzy identification ,pole placement ,non-linear control ,switches reluctance motor ,sliding mode control
آدرس shahrood university of technology, department of electrical robotic engineering, ایران
پست الکترونیکی a_k_mollaee@yahoo.com,akarami@shahroodut.ac.ir
 
     
   
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