Time-optimal control based on hybrid genetic algorithm

This paper studies the solving of time optimal control problems by using a hybrid genetic algorithm (HGA). HGA is a kind of GA in which the position displacement idea of the Particle Swarm Optimization (PSO) is applied to change the mutation operation rule and fix the next generation of chromosomes by recording the history optimal value of each chromosome and the optimal value of population. This method can be applied to solve mathematical optimization problems. To realize it in solving constrained time optimal control problems, one construct the fitness function by including the constraints in the objective function as penalty terms. Finally a numerical simulation for the problem of linear damped oscillator shows the effectiveness of the proposed method.