Zhifei Chen
Papers
6
Total Citations
27
H-Index
3
About
Zhifei Chen is a pioneering researcher in the field of chaotic optimization and its application to underwater robotics. His work focuses on leveraging the ergodicity, randomicity, and regularity of chaotic motion to solve complex nonlinear constraint optimization problems, particularly in the design and control of thruster motors for deepwater robots. Chen’s major contributions include the development of globally convergent chaotic optimization algorithms and hybrid methods that combine chaotic theory with Taboo search and Alopex algorithms, significantly enhancing convergence speed and solution accuracy. His research on controlling chaotic behavior in thruster motor systems, using techniques like Lyapunov exponent analysis and adaptive control, directly addresses stability and reliability challenges in deepwater ocean robots. With over 25 citations across his most-cited papers, Chen’s work has laid a foundation for robust motor optimization and motion planning in autonomous underwater vehicles. Notably, his 2004 paper on chaotic optimization for underwater robot motor optimization remains a key reference in the field, demonstrating the practical impact of chaos theory on real-world engineering design.
Research Focus
Key Achievements
Top Papers
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- 4Optimal design of thruster motor for underwater robot3 citations · 2004
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