基于模糊控制的潛器沉浮控制方法

　　針對(duì)水下潛器實(shí)際工作的需求和水下沉浮運(yùn)動(dòng)特征，提出一種基于自適應(yīng)模糊控制的水下潛器自主沉浮控制方法。該方法從優(yōu)化隸屬函數(shù)入手，采用多層前向神經(jīng)網(wǎng)絡(luò)的誤差反向傳播(EBP)算法對(duì)它的參數(shù)進(jìn)行在線修正，并采用Delta-Bar-Delta學(xué)習(xí)規(guī)則對(duì)學(xué)習(xí)速率進(jìn)行在線調(diào)整，使EBP算法具有較快的收斂速度，同時(shí)避免了局部極小值問(wèn)題。仿真實(shí)驗(yàn)表明，對(duì)于水下潛器自主沉浮運(yùn)動(dòng)的不能精確建摸、干擾嚴(yán)重的非線性與時(shí)變情況，這種自適應(yīng)模糊控制是一種較好的控制方式。

　　Abstract:

　　As for actual operation requirement and characteristics of ups and downs movement of underwater submersible vehicle， an independent ups and downs control method based on adaptive fuzzy control was advanced. In this method， on optimization of membership function， EBP algorithm of multiple layers forward neural network was used to correct parameters of membership function， and learning rule of Delta-Bar-Delta was used to adjust learning speed， which mended convergence speed of EBP algorithm， and the problem of sectional minimum was avoided at the same time. Simulation experiments show that independent ups and downs movement of underwater submersible vehicle could not be modeled precisely， and disturbance had characteristics of serious nonlinear and time change， which could be improved by this adaptive fuzzy control method.