Online optimal decoupled sliding mode control based on moving least squares and particle swarm optimization

Regulation and tracking of system states to the desired points or trajectories are two common tasks in the field of control engineering. For optimum performance of a controller, the appropriate selection of its parameters is of utmost importance. Furthermore, when the initial conditions of the system change, the controller with the previous parameters would be not optimum in the new conditions. To overcome these obstacles, in this paper, an online optimal Decoupled Sliding Mode Control (DSMC) approach is introduced. Firstly, to determine the optimum parameters of DSMC, an improved Particle Swarm Optimization (PSO) algorithm is applied. Next, to adapt the optimal controller to any initial condition, the Moving Least Squares (MLS) approximation is utilized. Finally, the proposed online optimal DSMC is successfully applied to a ball and beam system. The comparative studies are provided to verify the effectiveness of the proposed control scheme.