Enhancing Mobile Robot Speed Control: PID Controller Optimization with Bio-Inspired Algorithms

Abstract

This research study presents an investigation into the optimization of PID controllers using bio-inspired algorithms for controlling the speed of mobile robots. The study begins by identifying a mathematical model that accurately represents the dynamics of the DC motor used in robots. Three different tuning methods, namely Ziegler-Nichols (ZN), Flower Pollination Algorithm (FPA), and Fish Swarm Optimization (FSO) are then utilized to design the PID controllers. The primary objective is to enhance the speed control performance of mobile robots. To evaluate the effectiveness of the optimization methods, the set speed is given to each of the three controllers, and their performance is compared. The results demonstrate that the optimization techniques outperform the conventional ZN method in achieving the desired speed control. Among the two bio-inspired algorithms, FPA yields exceptional outcomes in terms of time characteristics. The comparison of time characteristics serves as a benchmark for evaluating the performance of the controllers. It reveals that bio-inspired optimization methods, especially FPA, significantly improve the speed control of mobile robots. The time characteristics, such as rise time, settling time, overshoot, peak time, and peak value, illustrate the superior performance achieved through the optimization process.