A Model Predictive Control Strategy Under Partial State Availability for Resilience and Maintenance Operations of Cyber-Physical Systems

In this article, we address a constrained regulation problem for networked control systems where the plants are modeled by polytopic linear descriptions, the state vector is partially available via output measurements, and the communication medium is unreliable. A control architecture is then proposed by considering a state-estimation-based robust model predictive control (MPC) strategy, designed to be resilient to regulation challenges while also preventing communication breakdowns when the convergence to the target is not practicable. Specifically, a deconvolution state observer is used for reconstruction purposes, and it is integrated with set-theoretic receding horizon principles to conceive a framework that meets both resilience and communication maintenance requirements.