Liang-Huan Ying
Papers
1
Total Citations
3
H-Index
1
About
Liang-Huan Ying is a researcher specializing in fault-tolerant control systems, with a particular focus on wheeled mobile robots (WMRs) and advanced estimation techniques. Their key research areas include model predictive control (MPC), intermediate estimator design, and real-time fault compensation for autonomous systems. Ying's most-cited work, "Fault-tolerant Tracking Control for Mobile Robots Based on the Framework of Intermediate Estimator and MPC" (2023), addresses a critical challenge in robotics: maintaining precise trajectory tracking when actuator faults—such as those caused by component aging or misoperation—degrade system performance. By integrating an intermediate estimator with MPC, Ying developed a robust framework that simultaneously estimates faults and adjusts control inputs, ensuring stable and accurate robot motion even under degraded conditions. This contribution has garnered early citations, reflecting its relevance to the growing field of resilient autonomous systems. Ying's work is notable for bridging theoretical estimation methods with practical control applications, offering a scalable solution for safety-critical robotics. Their research holds promise for advancing reliable automation in manufacturing, logistics, and service robotics, where uninterrupted operation is paramount.
Research Focus
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Top Papers
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