Adaptive Event-Triggered Voltage Control of Distribution Network Subject to Actuator Attacks Using Neural Network-Based Sliding Mode Control Approach

Abstract

This paper studies an adaptive event-triggered sliding mode control (AET-SMC) strategy for a distribution network voltage control (DN-VC) system subject to actuator attacks. In the network environment, a distribution network voltage deviation model under actuator attack is established. In order to save network resources in the DN-VC system, an adaptive event-triggered scheme (AETS) is designed. Considering the network-induced delay, the closed-loop system is transformed into an event-based delay system. Considering the network attack, the sliding mode control (SMC) method is used to offset the influence of the actuator attack. In order to eliminate the buffeting phenomenon, neural network (NN) technology is used to estimate the attack signal and obtain the sliding mode controller with better performance. The stability and stabilization criteria of the DN-VC system are obtained by using the Lyapunov–Krasovskii method and a linear inequality operation. Finally, numerical examples are used to verify the effectiveness of the method.