Speed control of PMSM using a fuzzy logic controller with deformed MFS tuned by a novel hybrid meta-heuristic algorithm

The goal of this study is to design a very robust and efficient standard fuzzy logic controller (FC) with tuned and deformed membership functions (FC-TMFS) using a new hybrid algorithm for speed control of the permanent magnet synchronous motor. The proposed algorithm is a partial combination of three algorithms, which are sewing trainee-based optimization (STBO), particle swarm optimization (PSO), and symbiotic organism search (SOS). To demonstrate the superiority of the proposed algorithm (ST-PS-SO), FC-TMFS optimal parameters obtained using ST-PS-SO were compared to the optimal parameters achieved when using STBO, PSO, and SOS. In terms of the system performance, and the fitness of the global optimum parameters, ST-PS-SO convincingly out-competed all other algorithms. In addition to that, through MATLAB/SIMULINK simulation, ST-PSO-SOS-based FC-TMFS was compared to the classical proportional–integral (PI), and PI–derivative (PID) controllers, as well as the conventional FC with symmetric and untuned MFS, based on the results of speed tracking, torque induction, and robustness test, FC-TMFS convincingly outperformed all other controllers in every aspect by a very significant margin. Finally, processor-in-loop (PIL) implementation was also performed to validate and prove the importance and functionality of the designed FC-TMFS, as well as the capability of the proposed hybrid algorithm.