国产欧美精品一区二区,中文字幕专区在线亚洲,国产精品美女网站在线观看,艾秋果冻传媒2021精品,在线免费一区二区,久久久久久青草大香综合精品,日韩美aaa特级毛片,欧美成人精品午夜免费影视

In order to address the problem of decreased control effectiveness of Unmanned Surface Vessel(USV) due to environmental disturbances such as wind, waves, and currents in course control, an Improved Model-Free Adaptive Control (IMFAC) algorithm incorporating Bacterial Foraging Optimistic(BFO) algorithm is presented. Firstly, the application issues of Partial Form Dynamic Linearization-Model Free Adaptive Control(PFDL-MFAC) in course control of USV are analyzed. A virtual output is designed to meet the assumption conditions of IMFAC, and a model free adaptive course controller based on partial format dynamic linearization method is established. In view of the parameter initial value selection range problem of PFDL-MFAC, an improved bacterial foraging algorithm is designed to pre-regulate the parameter initial values, ensuring rapid convergence of the algorithm. Finally, the effectiveness of the designed algorithm is verified through semi-physical simulation experiments. The results show that, under simulated interference from sea-state level 3, compared with the large steady-state errors resulting from traditional algorithms in 30° stepwise course control and ±30° square course control of USV, the IMFAC algorithm can steadily approach zero error after about 10 seconds of adjustment, achieving adaptive course control of unmanned vessels.