Electric Motor Control Using Hybrid Technique for Robotic Application

Abstract

In this paper, the performance of electric motor control is explored by the hybrid method of fuzzy PID and adaptive impedance control with similar considerations to a robotic application. The analysis uses a secondary approach of data analysis to measure control accuracy, energy efficiency and system responsiveness based on empirical observations of the literature. It is seen that fuzzy PID control can provide speed regulation above 30 per cent better with an optimised technique of metaheuristic algorithms, and adaptive impedance control can provide dynamic torque control and error reduction. There were also integrated energy management models which helped to cut cost of energy and ensure stability in operations. Digital twins and simulation systems increased the pace of performance verification and control under varying conditions. All these strategies in combination proved higher efficiency, less overshoot, and better adaptability in the systems of robots. The research presents the utility of the hybrid control architecture in contemporary robotics with linear, interpolatory, and intelligent solutions in energy-aware and precision-guided applications.