Particle Swarm-assisted state feedback control: From pole selection to state estimation

This paper presents automatic tools to optimize pole locations in state feedback control to satisfy performance specifications such as rise time, settling time, overshoot, and steady state error. Through the use of Particle Swarm Optimization (PSO), the advantages of such time-domain based controllers over frequency-domain controllers such as the Proportional-Integral-Derivative (PID) control is demonstrated, particularly for Multi-Input Multi-Output (MIMO) systems with a large number of states. A proof of concept problem involving the stabilization of a helicopter under the Rationalized Helicopter Model is presented and the results of the PSO auto-tuning, including the simultaneous design of a state observer and feedback controller, are supported by illustrative computer simulations.