Robust Control of Manned Submersible Vehicle With Nonlinear MPC and Disturbance Observer

Abstract

This letter focuses on the trajectory tracking of 7000 m JIAO-LONG manned submersible vehicle (MSV) with disturbances. The robust controller is realized by a composite control law, where an analytical nonlinear model predictive control (MPC) component is proposed to meet the requirements on tracking performance, and a feedforward control component is developed to reject the external disturbance and model uncertainty on the basis of a disturbance observer (DOB). Furthermore, the stability of the MSV system is analyzed, and representative simulation results are also given. The most significant feature of the designed MPC controller is that an explicit control law can be obtained for the MSV system, which alleviates the computational burden largely.Introduction: JIAOLONG is the first deep-ocean MSV independently devised and developed by China. The designed maximal depth is 7000 m, which was the deepest submersible all over the world. The MSV can serve in 99.8% of the world's ocean area, which is of great importance for the exploration of deep-ocean resources [1] and [2].The MSV system works in a complex challenging environment, where the MSV frequently receives external disturbances and parameter perturbations [3]. Owing to the complexity of deep-ocean environment, the nonlinearity of MSV, and the difficulty to acquire precise system parameters and external disturbances, the robust controller design of MSV is a quite challenging issue [4] and [5]. Furthermore, trajectory tracking is an important task for autonomous vehicles. There are some recent research results on the trajectory tracking of unmanned surface vehicle (USV) [6], [7] and MSV [8] with disturbances and uncertainties.As we know, MPC framework calculates the control law with an on-line optimization problem, which can be used to address the tracking task of autonomous vehicles [9] and [10]. However, the on-line optimization problem in conventional MPC greatly increases the computational burden of the on-board computer, which may lead to the deterioration of real-time capability of control systems. Reference [11] proposes an explicit nonlinear MPC method with analytical solution, which eliminates the calculation of on-line optimization. Hence, it is desirable to develop the controller of MSV with explicit MPC to reduce the computational burden largely.As previous mentioned, the MSV will encounter multiple disturbances in challenging underwater environments, including external disturbance, model uncertainty, etc. Reference [12] proposes a disturbance observer-based control (DOBC) method, which estimates and then compensates the lumped disturbance of nonlinear systems effec-tively. The DOBC and related methods have been intensively investigated in recent two decades [13]-[16]..