Shichun Yang

Beihang University

Papers

9

Total Citations

564

H-Index

6

About

Shichun Yang is a control systems researcher whose work spans stochastic control theory, fuzzy modeling, and multi-robot coordination. His research has made significant contributions to two interconnected domains: advanced control of complex dynamical systems and distributed formation control for mobile robotic platforms. Yang's most influential work, "Observer-Based Adaptive Sliding Mode Control for Nonlinear Stochastic Markov Jump Systems via T–S Fuzzy Modeling" (2020, 207 citations), demonstrates his expertise in handling real-world uncertainties in control design, combining sliding mode control with fuzzy approximation and observer-based strategies for systems with unmeasurable states and time-varying delays. Complementing this, his Takagi–Sugeno model-based reliable control of descriptor systems with semi-Markov parameters further solidifies his contributions to robust control under probabilistic switching environments. In multi-robot systems, Yang has developed a progressive body of work on distributed formation control for nonholonomic wheeled mobile robots, achieving over 120 and 104 citations respectively for his adaptive neural network and consensus-based formation approaches. His more recent investigations into fixed-time consensus and safety-critical nonlinear model predictive control reflect an evolving focus on real-time, collision-aware robotic deployment. With over 560 cumulative citations, Yang's research continues to shape both theoretical control frameworks and their practical robotic applications.

Research Focus

Key Achievements

6
H-Index
9
Papers
564
Total Citations
63
Avg Citations/Paper
🏆 Most Cited Paper
Observer-Based Adaptive Sliding Mode Control for Nonlinear Stochastic Markov Jump Systems via T–S Fuzzy Modeling: Applications to Robot Arm Model
207 citations · 2020
📈 Most Prolific Year: 2025 (3 Papers)
🤝 Key Collaborators: 23
🏛 Institutions: Beihang University

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
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