Implementation of Bio-Inspired Algorithms in Designing Optimized PID Controller for Dc-Dc Converters for Enhanced Performance

Abstract

This thesis represents an investigative analysis on the closed-loop stability of the Cuk converter and Zeta converter by implementing Bio-Inspired Algorithms (BIA) for designing an optimized PID controller. The applicability and compatibility of four bioinspired algorithms such as Firefly Algorithm (FA), Particle Swarm Optimization (PSO), Artificial Bee Colony (ABC), and Genetic Algorithm (GA) are analyzed in optimizing the control mechanism of the power converters. The improvement of performance parameters is observed and the outcomes are compared with the help of various fitness functions. The thesis emphasizes two higher-order power converters (fourth-order) and the advantages of higher-order converters lie in terms of further lowering ripple currents, simplifying Electromagnetic Compatibility (EMC) filtering, and avoiding current spikes due to resistive losses. The converters are designed through the State Space Averaging (SSA) technique for providing a promising feedback control fashion and evaluating the transfer functions. BioInspired Algorithm (BIA) is an artificial intelligence-based optimization tool catering to non-linear problems. The mentioned BIAs are based on swarm intelligence, functioning according to the custom followed by swarm creatures. Swarm intelligence guarantees better exploitation of data which concentrates the search method within the vicinities of optimal solutions and simultaneously assists the procedure to escape from the confinement of the local minima materializing successful exploration of the search space. Hence, the algorithms are evaluated for better performances in the system through different fitness functions (IAE, ITAE, ISE, and ITSE) and performance parameters like percentage of overshoot, rise time, settling time, and peak amplitude. MATLAB is used to carry out the simulations for both converters. After analyzing the performances for the case of the Cuk converter, it is observed that the percentage of overshoot FA-PID (IAE) provides a lower value than PSO-PID, GA-PID, and ABC-PID for each of the error functions. For rise time and settling time, the values of ABC-PID (IAE) are better but overshoot is high. Then comparing among the BIA-based PID controller for Zeta converter, we obtained that FAPID (ISE) is the most optimized controller where the value of overshoot is minimum. Moreover, the rise time and settling time for the Zeta converter also have the lowest value for FA-PID (ISE) than other optimized controllers. Hence, better optimization was provided for both converters in this investigative study by the FA-based PID controller.