Performance Enhancement of Liquid Level Control System Using PSO-Optimized Fuzzy PID Controller in MATLAB/ Simulink

Abstract

Liquid level management is a crucial but difficult task in industrial process control because liquid storage systems are characterized by their nonlinear dynamics, parameter uncertainties and exogenous disturbances. Normal Proportional–integral–derivative (PID) controllers usually encounter complications with nonlinear processes, contributing to an extensive settling time, overshoot and tracking accuracy. This paper demonstrates the design and tuning of a Fuzzy PID controller using particle swarm optimization (PSO) for build-up performance enhancement of MATLAB/Simulink based nonlinearly connected liquid-level control system. This method exploits the flexibility of fuzzy logic, leveraging to an automated determination of the best parameters controller by means of a PSO algorithm that utilizes global optimization techniques. Nonlinear mathematical model of the liquid-level system is developed, and traditional PID, fuzzy PID and PSO-optimized fuzzy PID were implemented in all mentioned cases under same working conditions. The performance of the controllers was evaluated based on overall time-domain characteristics and standard metrics like rise time, settling time, overshoot (OS), steady state error and Integral Error Criteria: IAE [21], ISE[22],ITAE[24],RMSE. Simulation results also show that the Fuzzy PID controller is excellent in dynamic performance with optimization of PSO. Experimental results show that it can achieve faster response time, less overshoot, better steady-state accuracy, smaller control signal variation and improved robustness against uncertainties in parameters as well as external disturbances. The results indicate that the fuzzy logic and Particle Swarm Optimization combination is an effective, reliable intelligent control strategy for nonlinear liquid level systems with practical applications in advanced industrial process control.