Papers
8
Total Citations
100
H-Index
6
About
Shuping He is a leading researcher in intelligent control systems, with a focus on nonlinear dynamics, sliding mode control, and reinforcement learning. His work bridges theoretical advances and real-world robotic applications, from brain-actuated mobile robots to robotic fish. He has pioneered fuzzy-based adaptive optimization for discrete-time nonlinear Markov jump systems, integrating Takagi–Sugeno fuzzy models with off-policy reinforcement learning—a contribution that has earned 45 citations and set a benchmark in adaptive optimal control. He has also developed discrete-time integral terminal sliding mode control for speed tracking in robotic fish, and event-triggered disturbance rejection schemes for brain-computer interface-driven wheeled mobile robots, using salp swarm algorithm optimization. His recent work includes finite-time sliding mode control for multi-agent systems under fuzzy topologies, and a novel high-speed tactile sensor (GelEvent) combining event cameras for dexterous robotic manipulation. With over 100 citations across his most-cited papers, He’s research is shaping next-generation autonomous systems. His achievements include advancing chattering-free finite-time estimation for multi-target enclosing control, demonstrating both theoretical rigor and practical impact in robotics and intelligent control.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4
- 5
- 6GelEvent—A Novel High-Speed Tactile Sensor With Event Camera6 citations · 2025
- 7
- 8