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About

Haowei Wen is a control theorist and roboticist whose research focuses on advanced adaptive and robust control strategies for complex mechanical systems, particularly robot manipulators and mobile manipulators. His most influential work addresses the challenging problem of trajectory tracking under uncertainties and disturbances. Wen’s highest-cited paper (2019, 11 citations) introduces a novel immersion and invariance (I&I) adaptive controller with a dynamic scaling factor, specifically designed to handle inertia uncertainties in robot manipulators—a significant step toward more reliable and high-performance robotic motion. He further advanced the field by developing a RISE-based adaptive tracking controller for Euler–Lagrange systems (2022, 6 citations), effectively managing matched disturbances. Most recently, Wen tackled the difficult problem of output feedback tracking for nonholonomic wheeled mobile manipulators under full-output constraints (2023, 2 citations), transforming the kinematic model into a chained form to enable constraint satisfaction without full state measurement. Through these contributions, Wen is building a systematic framework for safe, precise, and disturbance-resistant control of next-generation robotic systems, with clear implications for industrial automation and autonomous mobile manipulation.