A neural-network-based dynamic surface design strategy against sensor and actuator deception attacks is presented to design a delay-independent adaptive resilient control scheme of uncertain nonlinear time-delay cyberphysical systems in the lower triangular form. It is assumed that all nonlinearities, time-varying delays, and sensor and actuator attacks are unknown. In the concerned problem, since the state information measured by sensors is compromised by additional attack signals, the exact state variables are not available for feedback. Thus, a memoryless adaptive resilient control design using compromised state variables is developed by employing the neural-network-based function approximation technique and designing the attack compensator. The resulting control scheme ensures the robust stabilization in the presence of unknown deception attacks and time-varying delays. It is shown from the Lyapunov stability analysis that all closed-loop signals are uniformly ultimately bounded and the stabilization errors converge to an adjustable neighborhood of the origin.

This paper investigates a distributed connectivity-preserving and collision-avoiding formation tracking problem of networked uncertain underactuated surface vessels (USVs) with heterogeneous limited communication ranges. All nonlinearities in the dynamic model are assumed to be completely unknown. Compared with the existing formation tracking results for USVs, our primary contribution is to develop a new nonlinearly transformed formation error for achieving the initial connectivity preservation, the collision avoidance, and the distributed formation tracking without switching the desired formation pattern and using any additional potential functions. In other words, these three objectives can be achieved by using only one transformed formation error surface. The local tracker design strategy using the nonlinearly transformed error is established under the direct graph topology, where the adaptive function approximation technique and the auxiliary variables are employed to compensate for uncertain nonlinearities and to deal with the underactuated problem of USVs, respectively. Finally, the Lyapunov stability analysis and simulations are performed to verify the effectiveness of the proposed theoretic result.

This study proposes an adaptive approximation‐based control approach for non‐linear pure‐feedback systems in the presence of full state constraints. Completely non‐affine non‐linear functions are considered and assumed to be unknown. The dynamic surface design based on integral barrier Lyapunov functionals is provided to achieve both the desired tracking performance and the constraints satisfaction, in consideration of the full‐state‐constrained non‐affine non‐linearities. In this design procedure, simple sufficient conditions for choosing control gains, which can be checked off‐line, are established to guarantee the feasibility of the controller. The function approximation technique is employed to estimate unknown non‐linearities induced from the controller design procedure where the adaptive laws using the projection operator are designed to ensure the boundedness of the function approximators in the feasibility conditions. It is shown that all the signals in the closed‐loop system are uniformly ultimately bounded and the tracking error converges to an adjustable neighbourhood of the origin while all state variables always remain in the constrained state space.

An approximation‐based adaptive fault‐tolerant (AFT) control problem is investigated for strict‐feedback non‐linear systems with unknown time‐delayed non‐linear faults. The error surfaces restricted by prescribed performance bounds are employed to guarantee the transient performance at the moment when faults with unknown occurrence time and magnitude occur. Based on the surfaces, we design a memoryless AFT control system where the function approximation technique using neural networks is applied to adaptively approximate unknown non‐linear effects and changes in model dynamics because of the time‐delayed faults. It is shown from Lyapunov stability theorem that the tracking error of the proposed control system is preserved within the prescribed performance bound and converges to an adjustable neighbourhood of the origin regardless of unknown time‐delayed non‐linear faults.