Designing a cascaded exponential PID controller via starfish optimizer for DC motor and liquid level systems.

Area of Science:

• Control Systems Engineering
• Optimization Algorithms
• Nonlinear Dynamics

Background:

• Conventional PID controllers struggle with nonlinear systems.
• Existing fractional-order PID designs have limitations in adaptability and robustness.
• Optimizing controller parameters is crucial for enhancing system performance.

Purpose of the Study:

• To propose a novel cascaded exponential proportional-integral-derivative (exp-PID) controller.
• To tune the exp-PID controller using the starfish optimization algorithm (SFOA).
• To enhance the transient and steady-state performance of nonlinear dynamic systems.

Main Methods:

• Designing an exp-PID controller with nonlinear modulation in proportional and derivative components.
• Employing the starfish optimization algorithm (SFOA) for controller tuning.
• Validating the controller on a DC motor speed control system and a three-tank liquid-level process.

Main Results:

• The SFOA-based exp-PID controller demonstrated superior performance on benchmark systems.
• DC motor system achieved zero overshoot with rapid rise and settling times.
• Three-tank system showed minimal overshoot and a negligible steady-state error.
• Comparative analysis confirmed superior convergence, stability, and accuracy against other algorithms.

Conclusions:

• The proposed SFOA-based exp-PID controller offers enhanced adaptability, robustness, and precision for nonlinear systems.
• The controller design provides smoother control action and superior damping characteristics.
• Statistical evaluations confirm the robustness and consistent performance of the proposed method.