Dynamic event-triggered neural adaptive preassigned fast finite-time tracking control for stochastic nonaffine structure nonlinear systems

摘要

The issue of dynamic event-triggered preassigned fast finite-time tracking control for nonaffine stochastic nonlinear systems is investigated in this paper. In the control design process, mean value theorem is employed to transform the nonaffine structure of discussed systems into a strict-feedback case. By utilizing neural networks and dynamic event triggering control (DETC) strategy, the questions of unknown nonlinearities and communication burden are settled. With the barrier Lyapunov functions (BLFs) and backstepping technology in hand, a novel DETC fast finite-time adaptive controller is developed, which ensures not only that all signals of the closed-loop systems are bounded, but also that the tracking error as well as other whole state errors is constrained to the preassigned finite-time performance function. Finally, two simulation experiments are conducted to verify the feasibility and effectiveness of the presented control strategy.& COPY; 2023 Elsevier B.V.

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