Experimental validation of optimized fast terminal sliding mode control for level system.

Area of Science:

• Process Control
• Control Systems Engineering
• Optimization Techniques

Background:

• Level control systems are critical in industrial processes.
• Conventional Sliding Mode Control (SMC) has limitations in performance and convergence speed.
• Optimization methods can enhance controller parameter tuning.

Purpose of the Study:

• To apply a Fast Terminal Sliding Mode Control (FTSMC) combined with an optimization method for a single-input single-output (SISO) level control system.
• To optimize FTSMC parameters using the Non-dominated Sorted Genetic Algorithm-II (NSGA-II).
• To comparatively analyze the performance of NSGA-II tuned FTSMC against conventional SMC and FTSMC.

Main Methods:

• Implementation of FTSMC and NSGA-II for parameter optimization.
• Comparative analysis using MATLAB/Simulink simulations.
• Evaluation of performance indices: Integral Absolute Error (IAE), Integral Square Error (ISE), and integration of weighted errors.
• Real-time experimentation for robustness testing.
• Stability analysis using Lyapunov stability criteria.

Main Results:

• NSGA-II tuned FTSMC significantly outperforms conventional SMC and FTSMC.
• The optimized controller ensures error convergence to zero in finite-time.
• Demonstrated superior setpoint tracking and disturbance rejection capabilities.
• Robustness validated through real-time experimental results.

Conclusions:

• The NSGA-II tuned FTSMC provides a highly effective and robust solution for SISO level control.
• Finite-time convergence and improved disturbance rejection are key advantages.
• This approach offers enhanced performance over traditional control methods for process control applications.