Kanendra Naidu

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About

Kanendra Naidu is a researcher advancing the field of rehabilitation robotics, with a focused expertise in intelligent control systems for upper limb exoskeletons. His primary research areas include meta-heuristic optimization, PID controller tuning, and model predictive control for robotic rehabilitation systems. Naidu’s most impactful work, "Optimized Proportional-Integral-Derivative Controller for Upper Limb Rehabilitation Robot" (2019), has garnered 59 citations, demonstrating its significance in the field. In this study, he proposed a nature-inspired optimization technique to tune a PID controller for the RAX-1, a two-degree-of-freedom robotic arm exoskeleton, enhancing its performance in therapeutic exercises. His subsequent works extend this approach, including a firefly-optimized PID controller for a three-degree-of-freedom system (2019, 4 citations) and a model predictive control strategy for rehabilitation robots under disturbed conditions (2019, 5 citations). These contributions address the growing demand for effective neural disorder rehabilitation by improving robot precision and adaptability. Naidu’s work is notable for integrating bio-inspired algorithms with robotic control, offering practical solutions for patient recovery. His research continues to influence the development of smarter, more responsive rehabilitation technologies.