عنوان مقاله [English]
نویسندگان [English]چکیده [English]
This work addresses an autonomous underwater vehicle (AUV) for applying nonlinear control that be efficient for both perfect operation of under-actuated AUV and tracking guarantees. For this purpose, controller is capable of intelligent estimation of uncertainties and ocean current disturbance rejection. We proposed adaptive radial basis function neural network (RBF NN) controller in both heading and diving to approximate unknown nonlinear dynamics. Moreover, the problem of designing an adaptive RBF NN controller was augmented with sliding mode robust term to improve trajectory tracking and regulation in presence of uncertainties. Due to under-actuated mechanism of REMUS and lack of direct actuator effect, combination of RBF NN and sliding mode robust term is applied to compensate the system’s gravity/buoyancy force and guarantee appropriate motion in Z direction. Furthermore, stability proof of proposed control scheme was shown with lyapunov theory. Furthermore, the control, design and simulation results are provided without any simplification of the entire system. Although the design approach of this paper is implemented on REMUS this point of view can be applied on any AUV using the same technique.