Fractional order control of conducting polymer artificial muscles

This paper proposes a fractional order PID (FOPID) controller to improve the positioning ability of conducting polymer actuators (CPAs), a novel class of smart material based actuators. In the controller design process, the performance requirements and constraints which are crucial in precise positioning of CPAs such as fast settling time, low steady-state error, overshoot and control voltage are considered. In order to obtain the optimal controller parameters, cuckoo search (CS) and particle swarm optimization (PSO) meta-heuristic search methods which utilize a fractional order model of the CPA and a specifically defined fitness function, are used. Both of the algorithms are compared in terms of convergence rate and success of converging to an optimal solution. In order to test the performance of the FOPID controller, a PID controller is also tuned with both algorithms and all controllers are implemented experimentally on the CPA. The results show that the FOPID controller tuned with CSA has provided less overshoot, settling and rise-time than that tuned with PSO. The performance of the PID control is slightly worse than the FOPID controllers in terms of transient and steady-state response. Although both search algorithms have satisfied the control input constraint in FOPID and PID controllers, CSA tuned PID controller has required smallest control signal.