Output Constraint Control Of Unmanned Surface Vehicle With Stochastic Disturbances And Unknown Dynamics

Unmanned surface vehicle(USV)is widely used in petroleum exploration,fault detection,fixed-point cruise,and marine rescue,due to its characteristics of good maneuverability,low cost,and operating in extreme environments.An USV is always affected by stochastic disturbances such as wind,waves,and currents in the complex and harsh ocean environment.If the effects of stochastic disturbances are not considered in designing tracking controller,the USV performance will be deteriorated and the prescribed trajectory tracking task cannot be performed.Meanwhile,when an USV operates on the sea surface with reefs or in narrow waterways,we must ensure that the constraint requirement on the output tracking error is not violated and there will be no accidents of an USV hitting rocks or colliding with the waterway.Based on the backstepping method and Lyapunov stability theory,this thesis studies the trajectory tracking control of the USV with output constraint requirements under stochastic disturbances.By using It(?) formula,transverse function,radial basis function(RBF)neural networks(NNs),and tangent barrier Lyapunov function(BLF),a trajectory tracking controller is designed to force the system output to track the desired trajectory and guarantee the output constraint requirements will not be violated,so the USV can drive stably and safely.The second chapter studies the output constraint control problem of the fully-actuated USV under stochastic disturbances.Firstly,considering the characteristics of stochastic disturbances induced by waves,wind,and ocean currents,It(?) formula is used to transform the USV model into the stochastic system model.Secondly,we introduce the quartic Lyapunov function to deal with the second-order differential term in the differential operator.Thirdly,the tangent barrier Lyapunov function is used to deal with the output tracking error constraints.Fourthly,the tracking controller is designed by combining the Lyapunov stability theory with backstepping method.Finally,to deal with unmodeled dynamic uncertainties,we employ RBF approximators to estimate uncertain dynamics.Subsequently,based on RBF approximators,we design an adaptive controller to force the system output to track the desired trajectory and ensure the boundness of output tracking errors in the sense of probability.Numerical simulation results show that the proposed controller not only ensures the output tracking error converges into a small set around zero,but also guarantees the constraint requirements on output tracking error will not be violated in the sense of probability in presence of unmodeled dynamic uncertainties and stochastic disturbances.The third chapter studies the output constraint control problem of the underactuated USV under stochastic disturbances.In practical applications,the USV usually has no independent actuator in the sway motion.Since the underactuated system has three degrees of freedom to be controlled and only two independent control inputs,it is a more challenging problem to design a trajectory tracking controller for fully actuated USV.Firstly,to tackle the difficulties caused by underactuation and nonzero off-diagonal terms in the system matrix,we develop a transverse function control approach to introduce an additional control input in backstepping procedure.Secondly,a tan-type barrier Lyapunov function is introduced to guarantee the satisfaction of the prescribed tracking error constraints.Based on backstepping procedure and Lyapunov synthesis,a feedback control law is proposed to guarantee the transient and steady performance of tracking errors.Finally,considering uncertain dynamics in the USV system,we use RBF NNs to estimate it.Simulation results illustrate the effectiveness of the proposed tracking control.