Robust Wireless Networked Control Systems Using Genetic Algorithm-Optimized PID Controllers

Wireless Networked Control Systems (WNCS) play a crucial role in modern automation, offering flexibility and scalability but facing challenges such as packet loss, time-varying delays, and measurement noise. Conventional fixed-parameter PID controllers often struggle to maintain performance under such uncertainties. This study presents a Genetic Algorithm (GA)-based approach for optimizing PID parameters to enhance the robustness and reliability of WNCS. The proposed GA-optimized PID controller is systematically evaluated against a classical PID under nominal conditions, packet loss scenarios (10%, 30%, 50%), plant perturbations, and noisy measurements. Performance is assessed using overshoot, settling time, Integral of Squared Error (ISE), and Integral of Time-weighted Absolute Error (ITAE). Simulation results demonstrate that the GA-optimized PID significantly improves transient response and error metrics, maintaining stable tracking even under severe network disturbances. These findings highlight the potential of evolutionary optimization in strengthening the resilience of WNCS for industrial and cyber-physical applications.