随机拉格朗日系统的预设时间实际跟踪控制OA

In this paper,the prescribed-time practical tracking problem for a class of stochastic Lagrangian systems is investigated.The inherent nonlinearity,coupling,and stochastic noice increase the difficulty of controller design.To overcome the unbounded issue of prescribed-time control gain,a novel bounded prescribed-time adjust-ment function is introduced.Subsequently,by using a transformation,a tunning vector-form prescribed-time controller is designed,ensuring that all signals of the closed-loop system remain bounded in probability.The fourth-order moment of the tracking error can be adjusted to achieve any preset accuracy with the prescribed time via parameter tunning,and the tracking performance is independent of initial conditions.Finally,simulation verifica-tion is carried out on a nonlinear benchmark system in a stochastic vibration environment.The results confirm the effectiveness of the proposed control strategy.