This paper presents an adaptive nonlinear controller for diving control of an autonomous underwater vehicle (AUV). So far, diving dynamics of an AUV has often been derived under various assumptions on the motion of the vehicle. Typically, the pitch angle of AUV has been assumed to be small in the diving plane. However, these kinds of assumptions may induce large modeling errors and further may cause severe problems in many practical applications. In this paper, through a certain simple modification, we break the above restricting condition on the vehicle's pitch angle in diving motion so that the vehicle could take free pitch motion. Proposed adaptive nonlinear controller is designed by using a traditional backstepping method. Finally, certain numerical studies are presented to illustrate the effectiveness of proposed control scheme, and some practical features of the control law are also discussed.

Design of an adaptive nonlinear controller for depth control of an utonomous underwater vehicle

In this paper, an overview of Autonomous Underwater Vehicles (AUV) is presented whichdescribes the development and verification ofsix degree of freedom, non-linear simulation model. A nonlinear model of AUV is obtained throughkinematics and dynamics equations which are linearized about an operating point to get alinearized horizontal plane model.The system is modelled using INFANTE AUV hydrodynamic parameters that are controlled by path following control using MATLAB. The paper is concerned with depth control of AUV using Model Predictive Control without considering disturbances with the design of control laws that force a vehicle to reach and maintain a fixed position in vertical plane. The depth and pitch angle control of body fixed z-axis to a fixed point using MPC toolbox of MATLAB is shown in the paper. The paper summarizes the controller design steps, describes a technique for its practical implementation, and presents experimental results obtained with the INFANTE AUV using MATLAB.

Neha Aggarwal

Papers

Depth Control of Autonomous Vehicle using MPC