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About

Yi Zhang is a prominent researcher specializing in advanced control systems for electrohydraulic and robotic systems. His work sits at the intersection of nonlinear control theory, adaptive neural networks, and mechatronics, with a particular focus on solving real-world challenges in electrohydraulic actuator control. Zhang's most influential contribution, "Backstepping Control of Electro-Hydraulic System Based on Extended-State-Observer" (2016, 255 citations), introduced a powerful output position feedback control framework combining extended-state observers with backstepping techniques to manage unknown disturbances and nonlinearities — a persistent challenge in hydraulic control engineering. Building on this foundation, his 2018 paper on neural adaptive backstepping control for robotic manipulators (197 citations) advanced the field further by incorporating prescribed performance constraints, ensuring both dynamic and steady-state tracking precision in electrohydraulically driven robotic arms. His 2017 work on state-constrained control under parametric uncertainty adds additional depth to his portfolio, addressing practical stability concerns in single-rod actuator systems. With early contributions in human-machine exoskeleton systems dating back to 2008, Zhang has demonstrated a sustained and evolving research trajectory. His cumulative citation impact underscores his significant influence on modern robust control methodologies for complex electromechanical systems.