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About

Yuqi Zhu is a rising researcher in advanced robotics and nonlinear control systems, with a focus on adaptive and optimal control for complex robotic platforms. Their major contributions lie in developing robust, disturbance-rejection frameworks for both magnetic wheeled mobile robots and cable-driven continuum robots—soft, flexible systems ideal for confined spaces in manufacturing and electrical industries. Zhu’s most cited work, "Robust tracking control for magnetic wheeled mobile robots using adaptive dynamic programming" (2021, 30 citations), demonstrates a pioneering approach to self-learning optimal control under unknown disturbances. A subsequent study on a novel disturbance-rejection control framework for continuum robots (2022, 12 citations) introduced improved state parameterizations to tackle the inherent nonlinear dynamics and infinite degrees of freedom of these systems. More recently, Zhu has advanced adaptive safety-critical compensation control for nonlinear jump systems (2025, 3 citations) and extended state observer-based critic-only optimal control for continuum robots (2025, 1 citation), pushing the boundaries of autonomous, safe operation in uncertain environments. Their work is notable for integrating adaptive dynamic programming with real-world robotic applications, offering practical solutions for high-precision, resilient control.