Affiliations: Division of Instrumentation and Control Engineering, Netaji Subhas Institute of Technology (NSIT), University of Delhi, Sec-3, Dwarka, New Delhi, India
Correspondence:
[*]
Corresponding author. Vishal Srivastava, Division of Instrumentation and Control Engineering, Netaji Subhas Institute of Technology (NSIT), University of Delhi, Sec-3, Dwarka, New Delhi-110078, India. Tel.: +91 9971691694; E-mail: [email protected].
Abstract: Ball and beam is a popular benchmark problem in control engineering. Various control strategies have been proposed on ball & beam system in literature, In this paper, hybrid optimization algorithms have been implemented on PID controller to control ball position and beam angle. Hybrid algorithms combine exploration and exploitation ability of individual algorithm and find optimized value of performance index. In this paper, two hybrid algorithms namely PSO-GSA and PSO-GWO are used to tune controller parameters which in turn improve the system performance. Simulation results show effective and efficient improvement in system performance with these hybrid algorithms. To analyze the performance of these algorithms, time domain parameters and mean square error (MSE) has been taken as performance index. A comparative study of these algorithms with that of individual algorithms namely PSO, GWO, GSA has also been done.
Keywords: Ball and beam, particle swarm optimization (PSO), gravitational search algorithm (GSA), grey wolf optimization (GWO), mean square error (MSE), robustness
