Zhongsheng Hou
Papers
11
Total Citations
303
H-Index
7
About
Zhongsheng Hou is a leading figure in data-driven control and resilient automation, whose work bridges the gap between theoretical rigor and real-world robotics. His core research spans model-free adaptive control (MFAC), iterative learning control, and cyber-physical security for nonlinear multi-agent systems. Hou’s most influential contributions address control under communication constraints: he pioneered event-triggered and resilient MFAC strategies that maintain stability over fading channels and under periodic denial-of-service (DoS) attacks—work that has garnered over 220 citations from his top papers alone. His 2021 articles on event-triggered MFAILC and resilient control under DoS attacks are widely referenced for their novel integration of fading-channel models with data-driven methods. Beyond theory, Hou has demonstrated practical impact by applying MFAC to polishing robots, NAO humanoids, bionic robotic fish, and wheeled vehicles, achieving energy savings and robust tracking despite uncertain parameters, time delays, and data dropout. His recent fixed-time consensus and bipartite control schemes for multi-robot systems further showcase his ability to solve complex coordination problems under adversarial conditions. Hou’s work is essential reading for researchers in intelligent control, robotics, and secure networked systems.
Research Focus
Key Achievements
Top Papers
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- 4Model-free adaptive MIMO control algorithm application in polishing robot12 citations · 2017
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