Biomimetics, Год журнала: 2025, Номер 10(5), С. 266 - 266

Опубликована: Апрель 26, 2025

In this paper, an Improved Manta Ray Foraging Optimization (IMRFO) algorithm is proposed to address the challenge of parameter tuning in traditional PID controllers for artillery stabilization systems. The introduces chaotic mapping optimize initial population, enhancing global search capability; additionally, a sigmoid function and Lévy flight-based dynamic adjustment strategy regulate selection factor step size, improving both convergence speed optimization accuracy. Comparative experiments using five benchmark test functions demonstrate that IMRFO outperforms commonly used heuristic algorithms four cases. validated through co-simulation physical platform experiments. Experimental results show approach significantly improves control accuracy response speed, offering effective solution optimizing complex nonlinear By introducing self-tuning system parameters, work provides new intelligence adaptability modern control.

Язык: Английский