Quan Xiao

Sichuan University, Guangxi University of Science and Technology

Papers

Total Citations

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About

Quan Xiao’s research focuses on intelligent control systems for mobile and bio-inspired robots, with key contributions in fault-tolerant control, fuzzy logic, and optimal learning-based control. Their most cited work, “Fault-Tolerant Control of Trajectory Tracking for Mobile Robot” (2021, 3 citations), addresses a critical challenge in robotics—actuator faults—by designing a robust controller that mitigates performance degradation in two-wheeled mobile robots, enhancing reliability in real-world applications. This work is foundational for autonomous systems operating under uncertainty. In earlier research, Xiao explored point-to-point control for biomimetic robot-fish using fuzzy logic (2011, 2 citations), demonstrating how heuristic rules can achieve precise navigation in underwater environments, a stepping stone for bio-inspired robotics. Most recently, their 2025 paper on critic-only self-learning optimal control for continuum robots integrates extended state observers to handle unknown disturbances, advancing adaptive control theory for flexible manipulators. Though citation counts are modest, Xiao’s work bridges practical fault tolerance and theoretical optimal control, reflecting a sustained commitment to improving robot autonomy and resilience. Their trajectory from fuzzy control to learning-based methods showcases a deepening expertise in intelligent systems, making their research valuable for students and engineers tackling real-world robotic challenges.