IoT-Based Electric Vehicle State Estimation and Control Algorithms Under Cyber Attacks

Abstract

In order to provide intelligent services, the Internet-of-Things (IoT) facilitates millions of smart devices to be enabled with network connectivity to sense, collect, process, and exchange information. Based on the communication infrastructure, the IoT can allow cyber-physical devices, such as an electric vehicle, to sense, monitor, and control from the remote control center in real time. Unfortunately, the traditional communication infrastructure is vulnerable to cyber attacks, so it is a challenging task for the IoT to explore these applications. In order to overcome the problem, this article proposes an algorithm for monitoring and controlling the electric vehicle using the IoT communication network considering false data-injection attacks. First, the driverless electric vehicle with onboard vision system is represented by a state-space framework. As the electric vehicle and monitoring control center are far away, the IoT-embedded smart sensors and actuators are used to measure and control the system states. The vehicle sensing information is transmitted to the control center over an unreliable communication channel where attacks happen. Based on the mean square error principle, the optimal state estimation algorithm is derived to know and visualize the vehicle states. In order to regulate the vehicle states, the optimal control algorithm is designed based on the semidefinite programming approach. The simulation results show that the proposed algorithms are able to properly estimate and regulate the vehicle states within a short period of time.