Comparative analysis of spiral dynamic algorithm and artificial bee colony optimization for position control of flexible link manipulators - Nor Maniha, Abdul Ghani; Nizaruddin, M. Nasir; Azrul Azim, Abdullah Hashim (International Information and Engineering Technology Association, 2024)
Evolutionary algorithms have significantly advanced robotics by enabling the creation of efficient and intelligent robotic systems. This study aims to evaluate the effectiveness of two optimization algorithms, artificial bee colony (ABC) and spiral dynamic algorithm (SDA), in controlling the position of a flexible-link manipulator. By integrating the ABC algorithm into the manipulator's control system, the goal is to enhance its ability to plan paths and optimize trajectories. Additionally, the spiral dynamics algorithm, which draws on principles from complex adaptive systems and human values, provides a framework for modelling system evolution. The study hypothesizes that combining these two algorithms will improve the flexible link manipulator's adaptability and flexibility in dynamic environments and varied task conditions. The results support this hypothesis, demonstrate that the combined ABC and spiral dynamics approach outperforms conventional methods in several key performance metrics, including PID parameter tuning, overshoot, rise time, settling time, and steady-state error. In industry application such a motoring machinery, it is crucial to achieve these metrics at best, which kept the overshoot below 10%, settling time and rise time within a second. Interestingly, the manipulator's behaviours using the spiral dynamics algorithm for PID controller tuning were superior to those using alternative methods. Specifically, the spiral dynamics approach yielded the lowest overshoot at 5.83%, compared to 16.64% with the heuristic method and 8.82% with the ABC method. The SDA has the fastest rise time and settling time which is 0.03267 s and 0.18445 s respectively. Overall, the simulation results indicate that employing these algorithms for PID parameter optimization effectively enhances the manipulator's transient response and minimizes steady-state error, offering promising implications for real-world robotic applications.