Finite-time event-triggered sliding mode predictive control of unmanned underwater vehicles without velocity measurements

In this paper, a novel dual closed-loop trajectory tracking method based on model predictive control (MPC) and sliding mode control (SMC) is proposed for unmanned underwater vehicle (UUV) in three-dimensional underwater environment. On the basis of characteristics of MPC rolling optimization, the trajectory tracking problem is converted to the optimization problem of the outer loop kinematic controller to obtain the desired velocity for the inner loop, and the solution frequency is reduced through the event triggering mechanism. With the constraints of desired velocity, a finite time velocity observer which can handle unknown velocity constraints is designed. Concurrently, a dynamic controller based on recursive integral sliding mode surface is presented to eliminate the reaching phase improve the convergence rate. In addition, to eliminate overestimation of the upper bound of disturbance, a nested adaptive law is developed to design switching control law according to disturbance change. Finally, comparative simulations are conducted to illustrate the feasibility and superiority of the proposed control scheme.