Tuning of fractional order PID controller using the animated oat optimization technique for capacitor balancing in packed U cell multilevel inverter

Abstract In a Packed U Cell Multilevel Inverter, by optimizing the fractional order PID controller can improve performance by minimizing rise time, settling time, and steady-state error for capacitor balancing. Therefore, the Animated Oat Optimization Algorithm was used to optimize gain parameters of Fractional-order PID controllers for capacitor balancing. Based on the natural dispersal and hygroscopic motion of oat seeds, the Animated Oat Optimization algorithm provides a powerful global search capability and robust convergence behaviour. Animated Oat Optimization based Fractional order PID controllers are compared to conventional PID, Fractional order PID, Particle Swarm Optimization based Fractional order PID, etc, under identical operating conditions to validate their effectiveness. Some key transient performance measures are analyzed, including rise time, settling time, peak overshoot, steady-state error, and total harmonic distortion of the inverter output voltage. Additionally, control precision and system efficiency are evaluated using standard performance indices such as Integral Square Error, Integral Absolute Error, Integral Time Absolute Error, and Integral Time Square Error. Compared with other control techniques, the proposed Animated Oat Optimization based Fractional order PID controller achieves superior performance, with faster transient response, reduced steady-state error, and minimal total harmonic distortion, thereby improving capacitor voltage balancing and power quality in Packed U Cell Multilevel Inverter-based renewable energy systems. Also, the proposed Animated Oat Optimization based Fractional order PID controller is superior in terms of the convergence curve, as its value of the objective function reduces by 0.027 than the fitness value of Particle swarm optimization based Fractional order PID controller, which is 0.047.