Abstract
This study examines a computational technique used to design a novel feedback control law based on an expansion strategy of the Attraction Domain (DA) for a class of nonlinear switched systems. It is supposed that the state space is distributed into numerous regions without any intersections and modelled by polynomial inequalities. The main concept involves the maximization of the DA for local subsystems surrounding particular operational points. It was demonstrated that the DA can be ascertained by joining a Genetic Algorithmic method (GA) as an enhanced optimisation approach with the LMI method for a specified Lyapunov function. The feedback controller can then be constructed in order to ensure a global stability by using the Multiple Lyapunov function sets via switching signals. The effectiveness of this evolved strategy is eventually confirmed via a simulation examination by means of the benchmark Van der Pol oscillator.