An online optimal linear state feedback controller based on MLS approximations and a novel straightforward PSO algorithm
Mohammad Javad Mahmoodabadi, Mahdis Bisheban · Transactions of the Institute of Measurement and Control · 2014
Selection of control parameters is an important issue in the field of control design. This selection depends on the initial condition of the systems. On the other hand, controller parameters should be adjusted under all initial conditions to reach the optimal performance. To overcome this problem, in this paper, an online optimal linear state feedback control is introduced. Firstly, a straightforward particle swarm optimization is used to optimize the state feedback control parameters under some certain initial conditions. Then, in order to adapt the optimal controller to different initial conditions, the moving least squares approximation is used. The proposed technique is applied to an inverted pendulum system. The feasibility and efficiency of the proposed controller are assessed in simulation results.