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About

Sudarshan K. Valluru is a control systems and robotics researcher whose work bridges bio-inspired optimization, intelligent control, and real-time automation. His most cited work, "Optimization Strategy of Bio-Inspired Metaheuristic Algorithms Tuned PID Controller for PMBDC Actuated Robotic Manipulator" (2020, 20 citations), demonstrates a novel approach to tuning PID controllers for robotic manipulators using multi-objective genetic algorithms (MOGA) and adaptive particle swarm optimization (APSO), significantly improving computational performance and control precision. His earlier foundational study, "Prototype design and analysis of controllers for one dimensional ball and beam system" (2016, 10 citations), tackled the challenging control of an under-actuated, nonlinear, unstable electro-mechanical system—a classic benchmark in control engineering—by designing and analyzing multiple controller types for real-time balancing. Most recently, Valluru introduced the IQ-CRL algorithm (2023), which integrates Q-learning with artificial neural networks to enhance mobile robot navigation and decision-making, addressing key limitations in traditional reinforcement learning. With a focus on practical, bio-inspired, and intelligent control solutions, his work has direct applications in robotics, automation, and mechatronic systems, making him a notable contributor to the field of advanced control engineering.