Papers
7
Total Citations
457
H-Index
4
About
Xiaoxu Liu is a leading researcher in robust fault estimation and intelligent control for complex dynamical systems, with a particular focus on cyber-physical systems and robotic manipulators. Their seminal work on unknown input observer-based robust fault estimation, published in 2015, has garnered 372 citations and established a foundational framework for simultaneously estimating system states and faults while minimizing the impact of partially-decoupled disturbances—a critical advancement for real-time monitoring and fault-tolerant control. Liu has further extended these techniques to stochastic nonlinear systems with Brownian motions, addressing finite-time fault estimation challenges. In recent years, Liu has pioneered innovative control strategies for robotic systems, including a neuro PID controller for remotely operated robotic manipulators and neural network-based active disturbance rejection control for multi-joint robotic arms. Their research also addresses pressing cybersecurity concerns in industrial cyber-physical systems, developing multigain-switching secure estimation schemes against denial-of-service attacks. With contributions spanning fault diagnosis, nonlinear control, and multi-robot formation planning, Liu’s work has significant implications for industrial automation, remote operation, and resilient system design.
Research Focus
Key Achievements
Top Papers
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- 3A Novel Neuro PID Controller of Remotely Operated Robotic Manipulators16 citations · 2022
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- 5Fuzzy PID Control for Multi-joint Robotic Arm4 citations · 2022
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