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About

Xingjia Li is a leading researcher in robotics and control systems, with a primary focus on the modeling, identification, and advanced control of robot manipulators. His work addresses critical challenges in robotic precision and robustness, particularly under uncertain and nonlinear conditions. Li’s most impactful contribution is the development of an improved chaotic sparrow search algorithm for parameter identification of robot manipulators with unknown payloads, a paper that has garnered 62 citations and provides a powerful tool for real-time system calibration. He has also advanced the field through innovative modeling techniques, such as Blind-Kriging-based natural frequency modeling for industrial robots (15 citations), and robust control strategies, including a hierarchical multiloop model predictive control (MPC) scheme enhanced by a nonlinear disturbance observer (8 citations). His work on the optimal design of LPV-MPC controllers using transient search optimization (6 citations) further demonstrates his commitment to pushing the boundaries of robot control performance. Li’s research is instrumental in enabling safer, more accurate, and more adaptive robotic systems for industrial applications.