Jinkai Feng
Papers
1
Total Citations
23
H-Index
1
About
Jinkai Feng is a researcher in robotics and intelligent control systems, with a focus on improving the stability and precision of autonomous balancing robots. His major contribution lies in the development of the CFHBA-PID algorithm, a novel dual-loop PID attitude control method that integrates a complementary factor with the Honey Badger Algorithm (HBA) for optimal parameter tuning. This work directly addresses a critical limitation in traditional PID controllers—the difficulty of manual parameter tuning—by leveraging metaheuristic optimization to enhance robot balance and responsiveness. Feng’s approach mitigates the problem of premature convergence seen in earlier metaheuristic algorithms, offering a more robust and adaptive solution for real-time control. With 23 citations, his 2022 paper has already gained attention in the field of mechatronics and control engineering. Feng’s research is particularly relevant for students and engineers working on two-wheeled self-balancing robots, drone stabilization, or any application requiring precise attitude control. His work exemplifies the synergy between bio-inspired optimization and classical control theory, paving the way for more intelligent and autonomous robotic systems.
Research Focus
Key Achievements
Top Papers
- 1