Command‐Filter‐Based Adaptive Tracking Control of Uncertain Stochastic Nonlinear Systems With Multiple Constraints

ABSTRACT An adaptive preset performance tracking control scheme is proposed for a class of uncertain strict feedback stochastic nonlinear systems with full state constraints and input dead zones. A new coordinate transformation and obstacle Lyapunov function are adopted to solve the problem of full state constraints and preset performance. The nonlinearity of the input dead zone is solved by splitting the dead zone nonlinear term into a linear term and a bounded disturbance term. A fuzzy logic system is used to approximate the unknown function in the system. A command filter is introduced to solve the “differential explosion” problem, and a compensation signal is used to compensate for the filtering error. An adaptive command filter controller is designed using the adaptive backstepping method and stochastic stability theory, which can ensure that all the closed‐loop signals are ultimately bounded with semiglobal consistency in terms of the probability of quarter moments of an appropriate compact set. Meanwhile, the tracking error satisfies the predefined performance and converges to a small neighborhood close to zero. Simulation results show the effectiveness of the method.