Optimal Speed and Position Controller for PMDC Motor Based GWO Algorithm

The Grey Wolf Optimizations GWO Algorithm, is the newer technique to optimize the uncertain optimization problems by autotuning parameters. GWO algorithm is very useful due to its ease of implementation, direct results, robustness, and low computation cost. However, any application involving control systems can also use proportional integral derivative (PID) controllers. Numerous researchers use a variety of techniques, including fuzzy logic, particle swarm optimization, evolutionary algorithms, and others, to attempt to determine the ideal values of P, I, and D. Nonetheless, the primary goal of this work is to determine how well the intelligent algorithm GWO performs while autotuning the PID controller for a permanent magnet direct current (PMDC) motor. The GWO algorithm was selected as an optimization method, and the standard PID's settings were adjusted using integral time absolute error (ITAE). The results proved that GWO as an autotuning PID Controller is better compared to classical PID controller in terms of high performance of the motor’s speed, and good response with steady -state error equal to zero moreover it can be used to obtain optimal position tracking by using PMDC for many applications