Papers

11

Total Citations

56

H-Index

5

About

Changzhi Sun is a pioneering researcher at the intersection of chaos theory, fuzzy control, and underwater robotics. His work centers on solving complex optimization and control problems in autonomous mobile robots and deepwater robotic systems, with a particular focus on thruster motor design and motion planning in dynamic, unstructured environments. Sun’s major contributions include developing globally convergent chaotic optimization algorithms that leverage the ergodicity and randomness of chaotic motion to avoid local optima—a critical advance for nonlinear constraint problems. He also introduced fuzzy control methods to tame chaotic behavior in brushless DC thruster motors, enhancing the stability and reliability of deepwater robots. His most cited paper (10 citations) proposes a fuzzy-controlled time-delayed feedback method for chaos suppression, while his 2004 work on chaotic optimization for underwater motor design (9 citations) demonstrates global convergence. Sun’s innovative hybrid approaches, such as combining chaotic optimization with Taboo search and Alopex algorithms, have improved solution accuracy and convergence speed. His research on path planning complexity using Lyapunov exponents and power spectra analysis has advanced autonomous navigation in dynamic environments, making him a key figure in chaos-based robotics optimization.

Research Focus

Key Achievements

5
H-Index
11
Papers
56
Total Citations
5
Avg Citations/Paper
🏆 Most Cited Paper
Controlling Chaos for BLDC Thruster Motor in Deepwater Robot Based on Fuzzy Control
10 citations · 2007
📈 Most Prolific Year: 2004 (4 Papers)
🤝 Key Collaborators: 13
🏛 Institutions: Shenyang University, Shenyang University of Technology

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
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