Design a Robust Optimal Proportional-Integral-Derivative Controller for CE152 Magnetic Levitation System Using Bee Colony Algorithm

Abstract

One of the most popular methods for giving feedback to the control loop in industrial control systems is the proportional-integral-derivative (PID) controller. The tuning of the PID controller, however, is currently being researched by engineers. In this research, a robust PID controller is proposed for the CE152 magnetic levitation system. Magnetic levitation, commonly referred to as maglev, is a technology that uses magnetic fields to levitate an object, such as a vehicle or train, above a track. By using magnetic forces to counteract gravitational and inertial forces, maglev systems can achieve frictionless movement and potentially higher speeds compared to conventional wheeled transportation. In this research, the robust PID controller is involved by computing all stabilized PID controller gains for the affine linear characteristic polynomial in the presence of uncertain parameters using the parameter space approach and the edge theorem. The results of the parameter space approach are ranges of PID gains (𝐾 𝑃 , 𝐾 𝐷 , 𝐾 𝐼 ). Here, the optimal PID gains were chosen by the Artificial Bee Colony optimization algorithm to get optimal performance for CE152 magnetic levitation. The research defines a specific performance index function that quantifies the system's time-domain step response criteria (small overshoot percentage with significant minimization of both settling and rising times). This index function is inversely proportional to the desired performance criteria, aiming to optimize the system's performance. MATLAB simulations are used to validate and demonstrate the efficiency of the proposed graphical method for enhancing stability in the maglev system.