Robust Quadratic Stabilization for a Class of Discrete-time Nonlinear Uncertain Systems: A Genetic Algorithm Approach

نویسندگان

  • SAMIR NEJIM
  • NAWEL TEJ
  • NACEUR BENHADJ BRAIEK
  • Zhiqiang Zuo
  • Jinzhi Wang
چکیده

We present in this paper a new approach, to check the stability robustness of discrete-time systems under nonlinear perturbations. The systems are composed of a linear constant part perturbed by an additive nonlinearity. The unique information about the nonlinearity is that it satisfies a quadratic constraint. Our objective is to design a state feedback control law that maximizes the bound on the nonlinearity which the system can tolerate without destroying its stability. All results are obtained within the framework of a Genetic Algorithm (GA). The effectiveness of the method is illustrated through an example. Keywords: genetic algorithms, stability, field of stability, robustness measure, uncertain systems, LMI.

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تاریخ انتشار 2007