Peiliang Wang

Weifang People's Hospital, Huzhou University

Papers

Total Citations

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About

Peiliang Wang’s research centers on advanced control systems and soft sensing for complex industrial processes, with a focus on improving precision in dynamic environments. In his highly cited 2018 work, he introduced an improved line-of-sight (LOS) guidance law for robot tracking of moving targets, integrating an optimal information fusion Kalman filter to mitigate sensor noise and enhance trajectory accuracy—a contribution that has garnered 11 citations and practical relevance in autonomous navigation. Earlier, in 2014, Wang developed a soft sensor for multiphase and multimode processes using Gaussian mixture regression, enabling more reliable state estimation in non-linear, time-varying industrial systems. This work, with 6 citations, addresses critical challenges in process monitoring and control. Wang’s achievements demonstrate a keen ability to bridge theoretical advances with real-world applications, particularly in robotics and manufacturing. His research not only advances algorithmic robustness but also offers tangible solutions for improving system performance under uncertainty, making his work a valuable reference for students and engineers in control theory and industrial automation.