Xueliang Wang

Papers

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About

Xueliang Wang is a leading researcher in the control and automation of complex nonlinear systems, with a primary focus on switched systems, event-triggered control, and adaptive neural-network tracking. His most cited work, "Event-Triggered Adaptive Tracking With Guaranteed Transient Performance for Switched Nonlinear Systems Under Asynchronous Switching" (2022, 25 citations), introduces a novel mode-dependent event-triggered communication mechanism (MDETCM) that dramatically reduces communication resource consumption while ensuring robust transient performance. This contribution addresses a critical challenge in modern control systems: balancing efficiency with reliability under asynchronous switching conditions. Wang’s research is pivotal for applications in cyber-physical systems, robotics, and industrial automation, where resource constraints and performance guarantees are paramount. By integrating neural networks with event-triggered strategies, he has advanced the theoretical foundations of adaptive control, offering practical solutions for real-world systems. His work is widely recognized for its innovation and impact, making him a key figure in the next generation of control engineering.