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This paper examines a finite-time command-filtered backstepping control proposed for a class of strict-feedback nonlinear systems with input delay and time-varying asymmetric full-state constraints. The existing control method either ignores the effect of input delay or converges asymptotically in infinite time. A command-filtered backstepping design is used to decrease computational burden. A first-order Levant differentiator is employed to replace the command filter for estimating the virtual control signals in finite time. The time-varying asymmetric barrier Lyapunov function (TVABLF) and command-filtered backstepping design are applied to alleviate the significant challenges caused by the backstepping approach and full-state constraints. A novel finite-time delay compensation mechanism is proposed to remove the impact of input delay. The closed-loop signals are proved to be practical bounded. Simulation results are provided to demonstrate the effectiveness of the proposed control scheme. [ABSTRACT FROM AUTHOR]

This paper investigates the problem of event‐triggered adaptive output‐feedback control for multi‐input and multi‐output (MIMO) uncertain nonlinear systems with time‐varying full state constraints. A tangent‐type nonlinear mapping function is proposed to transform the state‐constrained system into a new one free of constraints, such that the time‐varying full state constraints are never violated. Radial basis function neural networks are introduced to compensate for the unknown functions. A state observer is established to estimate the unmeasured states. A suitable event‐triggering rule is presented to determine when to transmit control laws. Through Lyapunov analyses, all closed‐loop signals are proved to be semiglobally uniformly ultimately bounded, and time‐varying full state constraints are never violated. Finally, simulations are presented to evaluate the efficacy of the proposed approach. [ABSTRACT FROM AUTHOR]