Metaheuristic algorithm based PID controller using MRAC techniques for control of a nonlinear system

Researchers face a formidable task in devising effective control strategies for highly nonlinear systems. Addressing these challenges, we adopt the MIT rule in our study and employ the Model Reference Adaptive Controller (MRAC) approach to optimize solutions for nonlinear processes. The adaptive controller design, based on MRAC, aims to stabilize a process in the face of large parameter variations and external disturbances affecting the closed-loop system. We apply this technique to analyze a set of closed-loop systems, including Non-Reheat Turbine, Brushless DC Motor (BLDC) and Continuous Stirred Tank Reactor (CSTR) related to process industries. The controller parameter tuning technique, based on Artificial Bee Colony (ABC), is applied to achieve optimal controller performance. To demonstrate the effectiveness of the proposed controller, we compare the results with the conventional Proportional–Integral–Derivative (PID) and hybridized control techniques. The simulation is performed in the time domain. The time response of Non-Reheat Turbine, BLDC, and CSTR from the ABC-MRAC-MIT controller has a rise time (0.3967 s, 0.4415 s, 0.0850 s), settling time (1.8160 s,2.772 s, 0.4452 s), maximum overshoot (6.30% 3.40% and 6.9279%) respectively. Simulation results reveal the superior time-response characteristics of the proposed ABC-MRAC-MIT technique compared to other existing methods, enhancing the performance of process models and validating the novelty of this work.