A Neurodynamics-based Dynamic Surface Control Algorithm for Tracking Control of Dynamic Positioning Vehicles

In this paper, a neurodynamics-based dynamic surface control (DSC) algorithm is proposed, which is applied in tracking control of dynamic positioning (DP) vehicles. To avoid velocity jumps in the traditional DSC, we use the smooth continuous and bounded output characteristics of neural dynamic model to construct an intermediate virtue variable. And an appropriate Lyapunov function is introduced to get the tracking control law, which can guarantee global asymptotical stability of the control effect. Not only will this solve the problem of velocity jumps, but also can avoid generating excessive force and moment and meet the thrust constraints of DP vehicles propeller. The simulation results prove the superiority and effectiveness of the proposed algorithm.