Suboptimal Fuzzy Control for Memristive Chaotic Systems
This paper addresses the suboptimal control for memristive systems. Considering the state-dependent properties of the memristor, a fuzzy model employing parallel distributed compensation (PDC) is formulated to linearize the complicated memristive system with only two subsystems. A linear quadratic cost function is considered to measure the control performance of the systems. The obtained results are formulated by a minimization problem with linear matrix inequalities (LMIs) constraints. By minimizing the upper bound of the quadratic cost function, a unique control gain is derived. Meanwhile, the asymptotical stability of the systems is also guaranteed. Simulation results illustrate the effectiveness of the results in this paper.