Peiyong Duan
Papers
4
Total Citations
168
H-Index
4
About
Dr. Peiyong Duan is a leading researcher whose work bridges intelligent manufacturing, nonlinear control systems, and robotic perception. His most impactful contribution addresses the notoriously complex flexible job shop scheduling problem (FJSP) in steelmaking systems. In his highly cited 2023 paper (83 citations), Duan introduced a bi-population balancing multi-objective evolutionary algorithm that simultaneously optimizes energy consumption and transportation logistics under fuzzy processing times—a practical breakthrough for industrial efficiency. In nonlinear control theory, Duan developed an adaptive neural control scheme using a novel nonlinear mapping method (54 citations) to handle time-varying full-state constraints in nonstrict feedback systems, enabling safer operation of constrained robotic platforms. He further advanced event-triggered adaptive control for flexible robotic manipulators, reducing computational load while maintaining tracking precision. In computer vision, Duan’s work on probabilistic Siamese visual tracking (11 citations) leverages conditional variational autoencoders to improve tracking robustness in challenging environments, directly supporting human-robot interaction. Across these domains, Duan’s research demonstrates a consistent focus on real-world applicability—from factory floors to autonomous systems—making him a key figure in modern control and optimization.
Research Focus
Key Achievements
Top Papers
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