Improved Performance of PMSM using Tunicate Swarm optimization

Humans are moving towards a pollution-free environment, Electrical vehicles (EV) could help to achieve this since one of the major contributors to pollution is Conventional vehicles. Increasing the performance of EV's will promote the use of EVs in human civilization. For any electrical machine, performance depends on Time Domain parameters. By optimizing the time domain parameter, the performance increases drastically. With a simple optimized PID controller, the motor could achieve performance similar to other controllers like the Fuzzy logic system. In many papers, PID is tuned using Particle swarm optimization (PSO). Recently, a new biological metaheuristic technique is determined that is Tunicate swarm Algorithm (TSA). This method is better than many biological metaheuristic techniques. In this paper, the TSA is implemented to the PID controller for the Permanent Magnet Synchronous Motor (PMSM) operation thereby improving the Speed response and comparing with the existing PSO and conventional PID controller.