Wenqi Liu

Papers

Total Citations

H-Index

About

Wenqi Liu is a rising researcher in the field of advanced control systems for robotic manipulators, with a primary focus on enhancing system robustness and security. Liu’s work centers on developing adaptive, fault-tolerant control strategies that address critical challenges in uncertain and hostile environments. Their major contributions include pioneering the use of nonsingular fast terminal sliding mode control (NFTSMC) integrated with adaptive estimators and fuzzy wavelet neural networks. This approach ensures finite-time convergence, high precision, and resilience against cyber-physical threats, such as false data injection (FDI) attacks and actuator failures. Liu’s most cited paper, “Adaptive estimator-based nonsingular fast terminal sliding mode control of robotic manipulator systems under FDI attacks and actuator failure” (2024, 10 citations), demonstrates a novel method for maintaining stability and performance under simultaneous cyber and hardware faults. A second influential work (2024, 5 citations) further refines this technique by incorporating adaptive fuzzy wavelet neural networks to handle system uncertainties without prior knowledge. Though early in their career, Liu’s research has already garnered attention for its practical relevance in secure automation and robotics, offering a promising path toward safer, more reliable autonomous systems in manufacturing and defense.