A switch controller design for the acrobot using neural network and genetic algorithm
Sam Chau Duong, Hiroshi Kinjo, Eiho Uezato, Tetsuhiko Yamamoto · 2008
This paper presents an intelligent control method for the Acrobot with applications of neural network (NN) and genetic algorithm (GA). A switch controller is proposed where a neurocontroller (NC) optimized by GA is used for the swing-up stage and a linear quadratic regulator (LQR) is applied to the balancing stage. In order to analyze the characteristics of the proposed control system, we investigate the performance of the controller with different swing-up timing constraints. Simulation results show that the method has advantages in that it can provide smooth control process and allow us to flexibly define the swing-up time in advance.