Title :
NN-backstepping for diving control of an underactuated AUV
Author :
Wang, Hong-jian ; Chen, Zi-yin ; Jia, He-ming ; Chen, Xing-hua
Author_Institution :
Coll. of Autom., Harbin Eng. Univ., Harbin, China
Abstract :
This paper develops a path following controller for an AUV in vertical plane. With the given tracking error expressed in Serret-Frenet frame, a backstepping method based on feedback gain is adopted rather than directly nonlinear cancellation or feedback linearization. An adaptive neural network (NN) compensator is introduced due to the dynamics of AUV are highly nonlinear and the hydrodynamic coefficients are difficult to be accurately estimated at priori. The network weights adaptation law is derived from the Lyapunov stability analysis, and the resulting nonlinear feedback control scheme can guarantee that all the signals in the closed loop system are uniformly ultimately bounded (UUB). The simulation results demonstrate the effectiveness of proposed method with INFANTE AUV model.
Keywords :
Lyapunov methods; adaptive control; autonomous underwater vehicles; closed loop systems; compensation; feedback; linearisation techniques; neurocontrollers; nonlinear control systems; robot dynamics; stability; INFANTE AUV model; Lyapunov stability analysis; Serret-Frenet frame; adaptive neural network compensator; autonomous underwater vehicle; backstepping; closed loop system; diving control; feedback linearization; hydrodynamic coefficient; network weights adaptation law; nonlinear cancellation; underactuated AUV; Adaptation models; Backstepping; Lyapunov methods; Mathematical model; Surges; Vectors; Vehicle dynamics; adaptive control; autonomous underwater vehicle; back stepping; neural network; path following;
Conference_Titel :
OCEANS 2011
Conference_Location :
Waikoloa, HI
Print_ISBN :
978-1-4577-1427-6