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The combination of connectivity and automation allows connected and autonomous vehicles (CAVs) to operate autonomously using advanced on-board sensors while communicating with each other via vehicle-to-vehicle (V2V) technology to enhance safety, efficiency, and mobility. One of the most promising features of CAVs is cooperative adaptive cruise control (CACC). This system extends the capabilities of conventional adaptive cruise control (ACC) by facilitating the exchange of critical parameters among vehicles to enhance safety, traffic flow, and efficiency. However, increased connectivity introduces new vulnerabilities, making CACC susceptible to cyber-attacks, including false data injection (FDI) attacks, which can compromise vehicle safety. To address this challenge, we propose a secure observer-based control design leveraging Lyapunov stability analysis, which is capable of mitigating the adverse impact of FDI attacks and ensuring system safety. This approach uniquely addresses system security without relying on a known lead vehicle model. The developed approach is validated through simulation results, demonstrating its effectiveness. 

Cooperative adaptive cruise control (CACC) is one of the main features of connected and autonomous vehicles (CAVs), which uses connectivity to improve the efficiency of adaptive cruise control (ACC). The addition of reliable communication systems to ACC reduces fuel consumption, maximizes road capacity, and ensures traffic safety. However, the performance, stability, and safety of CACC could be affected by the transmission of outdated data caused by communication delays. This paper proposes a Lyapunov-based nonlinear controller to mitigate the impact of time-varying delays in the communication channel of CACC. This paper uses Lyapunov–Krasovskii functionals in the stability analysis to ensure semi-global uniformly ultimately bounded tracking. The efficaciousness of the proposed CACC algorithm is demonstrated in simulation and through experimental implementation. 

In a centralized Networked Control System (NCS), agents share local data with the central processing unit that generates control commands for agents. The control center in an NCS receives information from the agents through a communication network and produces control commands for agents. Despite all of the advantages of an NCS, such as reduced design cost and simplicity, the integration of networked connectivity can expose the NCS to adversarial attacks, such as false data injection (FDI). In this paper, a novel control approach will be developed to mitigate the FDI attack’s effect and guarantee the control objective in a networked system of permanent magnet linear motors. To achieve this, a non-singular terminal sliding mode control will be designed using an observer to ensure the tracking objective. The extended state observer will estimate the state of the system and estimate the FDI attack in real time. The control center will produce a control signal which is robust to the FDI attack and any disturbance. A Lyapunov-based stability analysis will be used to prove the stability of the observer-based controller. A three-agent permanent magnet linear motor network is selected for the simulation to show the effectiveness of the proposed scheme.