Papers
4
Total Citations
109
H-Index
4
About
Ye Cao is a leading researcher in the field of robotics control, specializing in fault-tolerant systems, cooperative manipulation, and energy-efficient automation. Her work addresses critical challenges in robot manipulators, particularly for dual-arm systems, where she has pioneered adaptive and neuro-adaptive control strategies that ensure precise trajectory tracking even under actuator failures and position-velocity constraints. Notably, her 2018 paper on adaptive PID-like fault-tolerant control for robot manipulators, with 53 citations, introduced a novel parameter estimation error method that achieves high performance with low-cost control—a breakthrough for practical industrial applications. She has also advanced prescribed-time tracking control without velocity measurement (24 citations) and developed parallel deep reinforcement learning for energy-efficient trajectory planning (23 citations), showcasing her interdisciplinary approach. Her 2024 work on optimal torque allocation for dual-arm robots (9 citations) further demonstrates her impact in cooperative control. With over 100 total citations, Cao’s research bridges theoretical rigor and real-world robotics, making her a key figure in modern automation and a valuable resource for students and engineers seeking robust, intelligent control solutions.
Research Focus
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