MODELLING AND CONTROL OF 3 DOF ROBOTIC SYSTEM AND DC-DC CONVERTERS

Abstract

This research presents a comprehensive investigation into the implementation and comparative analysis of various control strategies applied to two different yet control- sensitive systems: a 3-degree-of-freedom (3-DOF) haptic device and DC-DC converters specifically buck, boost, and SEPIC topologies used in renewable energy applications. Despite their different domains, both systems require robust control solutions to achieve precision, stability, and dynamic performance under varying conditions. For the haptic device, accurate position control and smooth user interaction are critical, particularly in applications such as surgical simulation, virtual reality, and remote manipulation. In this study, Proportional-Integral (PI) and Proportional- Integral-Derivative (PID) controllers are employed to regulate the position of the end- effector. These classical control strategies are evaluated for their effectiveness in tracking performance, settling time, and stability in the presence of mechanical nonlinearities and dynamic changes. Simulation results validate the applicability of these controllers in achieving stable and responsive behaviour. In contrast, the DC-DC converters utilized in renewable energy systems require control strategies capable of managing nonlinear behaviour, maintaining output voltage regulation, and reducing transient effects under variable input and load conditions. To address these requirements, this work applies PID, Fuzzy Logic controller (FLC) and Adaptive Neuro-Fuzzy Inference System (ANFIS) controllers. Each controller is assessed based on its ability to improve performance and ensure efficient power conversion across different operating conditions. The comparative analysis reveals that while classical controllers such as PI and PID provide acceptable performance in both systems, intelligent control techniques particularly Fuzzy Logic and ANFIS offer superior adaptability, learning capability, and robustness for the nonlinear and time-varying nature of power electronic converters. The study concludes that selecting an appropriate control strategy based on system dynamics, control objectives, and performance criteria is crucial for enhancing system efficiency, reliability, and responsiveness in both haptic and renewable energy domains.