Yuesheng Liu
Papers
5
Total Citations
23
H-Index
2
About
Yuesheng Liu is an emerging researcher specializing in model predictive control (MPC), mobile robotics, and intelligent control systems, with a growing focus on machine learning-enhanced control strategies and cybersecurity in autonomous systems. His most recognized contribution, "Design of a Model Predictive Trajectory Tracking Controller for Mobile Robot Based on the Event-Triggering Mechanism" (2021, 15 citations), addresses a critical challenge in robotics: reducing the computational and communication burden of MPC optimization through an event-triggering mechanism, making real-time trajectory tracking more practically viable. Building on this foundation, Liu has advanced the field by integrating machine learning with MPC frameworks for adaptive parameter self-tuning, enabling mobile robots to respond more intelligently to dynamic environments. His 2025 work on a basic-residual cooperative model represents a sophisticated step forward, combining static and dynamic feature capture to overcome limitations of single-network prediction models. More recently, his research has expanded into data-driven multi-model predictive control under cyber attacks, reflecting timely awareness of security vulnerabilities in networked control systems. Collectively, Liu's work demonstrates a coherent research trajectory bridging classical control theory with modern data-driven and learning-based methodologies.
Research Focus
Key Achievements
Top Papers
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- 3A Novel Learning-Based MPC Method via Basic-Residual Cooperative Model2 citations · 2025
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