Increased power demand, poor transmission infrastructure, and uncertain renewable
generation cause congestion in the power network. Traditionally network congestion is …

To alleviate the adverse effects of heterogeneous vehicular platoon (HVP) with uncertain
dynamics, a distributed data-driven model predictive control (DDMPC) strategy is proposed …

The increasing autonomy and connectivity in cyber-physical systems (CPS) come with new
security vulnerabilities that are easily exploitable by malicious attackers to spoof a system to …

This article proposes an approach for line power flow regulation through a robust
guaranteed cost output feedback controller to mitigate the congestion in power systems …

While many research efforts on Cyber-Physical System (CPS) security are devoted to attack
detection, how to respond to the detected attacks receives little attention. Attack response is …

Cyber-physical systems (CPSs) leverage computations to operate physical objects in real-
world environments, and increasingly more CPS-based applications have been designed …

Traditionally, the problem of congestion arising in power system networks due to various
contingencies and varying renewable generation is addressed by optimal power flow-based …

The penetration rate of automated vehicles (AVs) may remain unsaturated for a long time,
resulting in the coexistence of AVs and human-driven vehicles (HDVs). The non-ideal …

For nonlinear cyber physical systems (CPS) with additional disturbances and system
constraint, a resilient self-triggered model predictive control (RST-MPC) strategy is …

We address the problem of attack signal estimation in industrial control systems that are
subjected to actuator false data injection attack (FDIA) and where the sensor measurements …