Hao Liang

University of Chinese Academy of Sciences, China University of Petroleum, East China

Papers

Total Citations

H-Index

About

Hao Liang is a control systems engineer whose research focuses on the robust and adaptive control of robotic manipulators, particularly in the presence of uncertainty and non-smooth dynamics. His most cited work, "Robust composite nonlinear feedback control for uncertain robot manipulators" (2020, 12 citations), introduces a novel composite nonlinear feedback (CNF) design that integrates robust control with classical computed torque methods, significantly improving tracking performance under uncertainty. Liang further advances the field with a non-smooth robust control strategy (2015, 3 citations) that leverages decimal power rules in Lyapunov redesign to achieve faster convergence and higher precision than conventional approaches. His work on terminal converging adaptive control for 6-degree-of-freedom parallel robots (2017, 2 citations) addresses the critical challenge of bounded control inputs, combining non-smooth feedback with bounded functions to ensure stability and performance. Though his citation counts are modest, Liang’s contributions are foundational for practitioners seeking practical, high-performance solutions for complex robotic systems. His research is especially valuable for applications requiring precise, fast, and robust control in uncertain environments, making him a key figure in the development of next-generation robotic manipulator control.