Enhanced dynamic fuzzy sliding mode controller for autonomous underwater vehicles

The problem of depth control for autonomous underwater vehicles (AUV's) is addressed in this study. So far, control of an AUV is a challenging problem due to the highly non-linear dynamics, uncertain parameters and unpredictable external disturbances. For this reason, high performance depth control system for an AUV usually should have the capacities of learning and adaptation to the time-varying dynamics of the nonlinear model. A newly designed enhanced dynamic fuzzy sliding mode controller (EDFSMC) is proposed to track periodic commands in vertical plane. The tracking performance is improved with help of fuzzy adaptive tuner, which is applied to shift input-output membership functions of fuzzy sliding mode control (FSMC) algorithm. In this novel approach, two supervisory fuzzy systems are employed to vary width of boundary layer and to tune the support of output singleton functions. Due to the first fuzzy supervisory system, piecewise nonlinear sliding surface is designed and the second one is used to adaptively tune and shift support of output membership functions on universe of control with exponential function based gain. The proposed scheme possesses the salient advantages as simple control framework, free from chattering, stable tracking control performance, and robust to uncertainties. By choosing an adequate Lyapunov candidate function, the system's stability is proven. The effectiveness of this design control method is demonstrated by means of numerical simulations. The significant improvement is observed for tracking performance of AUV in vertical plane.