Papers
4
Total Citations
20
H-Index
3
About
Zhenghong Jin is a control systems researcher whose work sits at the intersection of multiagent systems, distributed optimization, and robust control. His research focuses primarily on designing algorithms that enable networks of autonomous agents to coordinate and optimize collectively under real-world constraints, including environmental disturbances, switching communication topologies, and nonlinear dynamics. Jin's most cited contribution, "Multiagent Distributed Source Seeking Under Globally Coupled Constraints" (2024, 8 citations), demonstrates his ability to bridge theoretical optimization with practical deployment, developing algorithms validated through physical experiments. His earlier work on Takagi–Sugeno fuzzy modeling for nonlinear singular systems (2019, 7 citations) reflects a strong foundation in approximation methods for complex dynamical systems. More recently, his investigation of PWM-controlled mobile robots under switching topologies (2023, 4 citations) highlights his commitment to addressing challenges that arise in hardware-constrained, real-world robotic formations. His latest research on momentum-based distributed optimization for heterogeneous multiagent systems (2025) signals a growing interest in nonconvex optimization and timescale separation techniques. Though early in citation accumulation, Jin's body of work represents a coherent and technically rigorous program advancing autonomous multi-robot coordination and intelligent control system design.
Research Focus
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Top Papers
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