Tuning PID Controllers Based on Hybrid Arithmetic Optimization Algorithm and Artificial Gorilla Troop Optimization for Micro-Robotics Systems

Micro particles have the potentials to be used for many medical purposes in-side human body such as drug delivery and other operations. This paper attempts provide a thorough comparison between five meta-heuristic search algorithms: Arithmetic optimization algorithm (AOA), Artificial Gorilla troop’s (GTO), Seagull (SOA), Parasitism-predation Algorithm (PPA), hybrid AOA GTO (HAOAGTO). These approaches were calculate PID controller optimal indicators with application of different functions, including Integral Absolute Error (IAE), Time Multiplied by Square (ITSE), multiplied square (ISTES), (ISE), ( (ISTSE), (ITAE). Every method controlling was presented in MATLAB Simulink numerical model. It is observed that PPA technique achieves highest values best fitness value simulation results among control approaches, while HAOAGTO approach reduces function compared techniques used. The indicate all ISTES choice optimizing parameters.