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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]

Airships, as the significant UAV, have a need for greater autonomy in their new missions. Therefore, airship flight control systems require precise dynamic modeling, taking into account the effect of flexibility and the interaction with aerodynamic forces. This research effort develops an efficient modeling of the autonomous flexible airship. The formalisation used is based on the Lagrange method. The resulting model includes the rigid body motion, the elastic deformation, and the coupling between them. Based on the precise flexible dynamic model, a novel backstepping nonlinear controller with integral action is proposed for motion control systems. The resulting feedback controller is able to adapt to actuator performance limitations, such as limitations in magnitude and rate of change of rudder, than conventional backstepping controller without integral action. With the deformation considered, the presented controller could resist the flexible uncertainty effect, and the system’s trajectory tracking ability is significantly improved. The approach guarantees exponential stability of a compensated tracking error in the sense of Lyapunov.

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]

This paper addresses the finite-time three-dimensional path-following control problem for underactuated autonomous airship with error constraints and uncertainties. First, a five degrees-of-freedom path-following error model in the Serret-Frenet coordinate frame is established. By applying the finite-time stability theory, a virtual guidance-based finite-time adaptive neural backstepping path-following control approach is proposed. Barrier Lyapunov functions (BLFs) are introduced to deal with attitude error constraints. Neural networks (NNs) are presented to compensate for the uncertainties. To prevent the "explosion of complexity" in the design of the backstepping method, a finite-time convergent differentiator (FTCD) is introduced to estimate the time derivatives of virtual control signals. Stability analysis showed that all closed-loop signals are uniformly ultimately bounded, the constrained requirements on the airship attitude errors are never violated, and the path-following errors converge to a small neighborhood of the origin in a finite time. At last, simulation studies are provided to demonstrate the effectiveness of the proposed control approach. [ABSTRACT FROM AUTHOR]