A cyber-resilient control framework with adaptive model predictive control (AMPC) for securing energy systems in smart buildings

With smart buildings becoming increasingly reliant on cyber-physical systems to optimize energy efficiency and maintain occupant comfort, the growing risk of cyber-attacks poses significant threats to operational integrity. Despite the increasing deployment of advanced technologies in Building Automation Systems (BASs), a substantial gap remains in developing and deploying real-time mitigation strategies to defend against these vulnerabilities. This paper proposes a novel cyber-resilient control framework that integrates the Adaptive Model Predictive Control (AMPC) to enhance energy resilience of smart buildings. The framework aims to maintain acceptable levels of energy system performance under cyber-attacks by dynamically reconfiguring the control objectives and constraints of nominal MPC into AMPC based on cyber-attack detection outcomes to ensure system continuity. The feasibility and effectiveness of the proposed framework were demonstrated through a Hardware-in-the-Loop (HIL) experiment under a Denial-of-Service attack scenario, specifically a device reinitialization attack on a Variable Air Volume (VAV) terminal box. Results showed that the cyber-resilient control framework reduced temperature violations (i.e., unmet degree hours) by 76.3%, with a control mitigation response time within one minute, although it resulted in an 11.4% increase in power consumption. These findings underscore the potential of the proposed cyber-resilient framework to mitigate the impact of cyber-attacks, ensuring resilient operation and security for energy systems in smart buildings.