Performance Optimization of PID Controllers in Flow-Rate Control Systems Using Hybrid Algorithm Model (Genetic Algorithm - Grey Wolf Optimizer)

This paper introduces a novel Proportional-Integral-Derivative (PID) controller through hybrid metaheuristic algorithms to control the closed loop flow rate control system. A hybrid G.A - G.W.O algorithm is developed to achieve optimal control performance for the system using strengths of both the algorithms. The system along with the optimized PID controller are modeled in MATLAB and integrated the parameters of real hardware system incorporating the characteristics of flow rate control system and dynamic variables like process delays. External disturbances as inputs are also considered while modeling to replicate the practical operating conditions for the system. It serves as a practical foundation for developing advanced flow control systems in industries such as water treatment, chemical processing, and HVAC systems. The paper also compares PID controller tuning for the given system using optimization techniques, such as Genetic Algorithm (G.A) and Grey Wolf Optimization (G.W.O), and hybrid G.A - G.W.O algorithm to achieve optimal control performance for the system. Performance metrics such as rise time, settling time, and, overshoot are evaluated to ensure robust working of the PID controller for the given system.