A.Sathish Kumar

Papers

Total Citations

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About

A.Sathish Kumar is a researcher whose work centers on the intersection of robotics, control systems, and intelligent optimization. His primary contributions lie in enhancing the precision and stability of robot manipulators, particularly through the innovative integration of neural networks with advanced control algorithms. In his most notable study, "Control of Robot Manipulator Error Using FPDI–IQGA in Neural Network" (2016), Kumar introduced a hybrid approach combining fractional-order proportional-derivative-integral (FPDI) control with an improved quantum genetic algorithm (IQGA). This method significantly reduces trajectory tracking errors in robotic arms, addressing a critical challenge in automation and industrial robotics. Although his citation count remains modest—with this key paper garnering three citations—his work demonstrates a focused effort to bridge theoretical control methods with practical robotic applications. Kumar’s research is particularly relevant for students and engineers exploring adaptive control, evolutionary optimization, and neural network-based error compensation in mechatronic systems. His contributions offer a foundation for further advancements in precise robotic manipulation, especially in environments requiring high accuracy and real-time adaptability.