Papers
1
Total Citations
9
H-Index
1
About
Min Zhang is a researcher specializing in robotics, control systems, and optimization, with a particular focus on advancing the performance and reliability of robotic manipulators. His most notable work centers on the development of sophisticated control strategies that address real-world engineering challenges such as dead zones, actuator saturation, and uncertain system dynamics — factors that significantly complicate the modeling and control of robotic systems. In his landmark 2024 paper, Zhang proposed a Nonlinear Active Disturbance Rejection Control (NADRC) framework integrated with a Particle Swarm Optimization (PSO)-based global optimization strategy, offering a robust and adaptive solution for precise trajectory tracking in robotic manipulators. This contribution has already garnered 9 citations, reflecting its timely relevance and practical significance within the control engineering community. By combining advanced nonlinear control theory with metaheuristic optimization, Zhang bridges the gap between theoretical rigor and real-world applicability. His work holds strong implications for industrial automation, intelligent manufacturing, and autonomous robotics, making him an emerging voice in the field of intelligent control systems whose contributions are increasingly valued by both researchers and engineers alike.
Research Focus
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Top Papers
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