Abstract
This paper addresses an approximation-based adaptive event-triggered control problem against unknown injection data in full state measurements and an actuator of systems with unknown strict-feedback nonlinearities. It is assumed that full state variables measured for state-feedback control are corrupted by unknown injection data that denote cyber attacks or fault signals, and all system nonlinearities are unknown. Owing to the corrupted state feedback information, error surfaces using exactly measured state variables become unknown during the recursive control design procedure for strict-feedback nonlinear systems. Thus, they cannot be used to implement the adaptive event-triggered controller. To address this problem, an approximation-based adaptive recursive event-triggered control design using the corrupted state variables is established to ensure that error surfaces using exactly measured state variables converge to an adjustable neighborhood of the origin in the Lyapunov sense. The adaptive controller and its event-triggering law using corrupted states are designed under uncertain injection data where the adaptive injection data compensators using the neural networks are constructed to deal with the unknown injection data effects. The stability of the closed-loop systems and the exclusion of Zeno behavior are analyzed.
Highlights
The development of information and communication technology has stimulated the tight interaction of control systems and cyber components [1], [2]
The objective of this paper is to propose a remedy for difficulties (D1) and (D2), that is, to establish an adaptive resilient event-triggered control design strategy using corrupted full state measurements for uncertain nonlinear strict-feedback systems with unknown injection data in full
A recursive resilient eventtriggered control design strategy using the corrupted state variables is established in the presence of unknown injection data in full state measurements and an actuator; (ii) Assumption 3 is reasonable for ensuring the controllability of the system (1) with injection data in full state measurements [23]. This implies the existence of a nominal solution for Problem 1; (iii) Contrary to the existing recursive designs [10]–[15] against output measurement faults, this paper considers full state variables corrupted by unknown injection data (i.e, xi,a = xi + κi,s(t, xi) in (1)) and the adaptive event-triggered control problem using the corrupted state variables
Summary
The development of information and communication technology has stimulated the tight interaction of control systems and cyber components [1], [2]. The sources of the injection data in the resilient control studies are largely divided into two categories: (i) measurement. The sensor faults influence the measurement information for the feedback control. Many studies have addressed the resilient control problems of linear and nonlinear systems with measurement faults [3]–[6]. Some limited studies have appeared for the recursive control design of lower-triangular nonlinear systems with measurement faults where backstepping [7] and dynamic surface designs [8], [9] have been used to construct the resilient control systems. In [12], an output-feedback stabilizer design problem using a dual-domination approach was addressed for lower-triangular nonlinear systems with unknown measurement sensitivity. In [13], an adaptive
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