In this article, the command filter based adaptive event-triggered control problem for multiple-input and multiple-output multiple time-delay stochastic nonlinear systems is considered. First, a state observer is constructed to estimate the unmeasured states of systems. Then, in the framework of backstepping design, the command filtered and event-triggered techniques are employed to avoid the problem of "explosion of complexity" and save the communication resources, respectively. Meanwhile, by utilizing the command filters, a novel variable separation method is constructed to address the algebraic-loop problem, which caused by the nonstrict-feedback item. The boundedness of the whole signals in systems can be remained, and the given desired trajectories can be followed by the system outputs. Finally, a numerical example is shown to demonstrate the effectiveness of the proposed control method.
This paper proposes a dynamic event‐triggered mechanism based command filtered adaptive neural network (NN) tracking control scheme for strong interconnected stochastic nonlinear systems with time‐varying output constraints. By designing a state observer, the unmeasured states of the systems can be estimated. The NNs are utilized to handle the unknown intermediate functions. In the controller design process, the asymmetric time‐varying barrier Lyapunov functions are used to guarantee that the systems outputs do not violate the constraint regions. By integrating the command filter with variable separation technique, the controller design process is more simple, and the problem of algebraic‐loop can be solved which caused by interconnected functions. According to the Lyapunov stability theory, it can be ensured that all signals of the systems are bounded in probability. Finally, the availability of the developed control scheme can be showed by the simulation example.
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