In the ReMiX project, a design methodology for verifiable system architectures in intelligent automation is to be developed. For this purpose, distributed resources are summarized as a shared virtual resource and organized according to the principles of mixed-criticality systems. Mixed-Criticality describes a mapping of functions to resources based on their criticality according to available resource quotas. The distributed resources are merged as a shared virtual resource and organized according to the principles of systems with different criticality. The research results of this project will contribute to increase the system resilience through new design methods for self-organizing communication, computing and control approaches. By integrating security aspects into the design methodology, we aim to extend our development framework to attack-resistant mixed-criticality systems.
 

The solution approach of the ReMix project focuses on modeling and control of resilient and mixed-criticality cyber-physical and hybrid dynamical systems. We consider the resilient behavior of the system illustrated in Fig. 1. The function F(t) presents the system performance measure, and the degradation of F(t) occurs due to functionality failure, attack, or denial of service. Without any actions, the performance of the system will drop to a low degraded steady state. Once the event has been detected, a resilience action can be triggered to optimize the system functionality performance F(t) under the limiting circumstances. Therefore, the proposed solution consists of development methods and algorithms for modeling and scheduling distributed resilient mixed-criticality systems, where the objective is to maximize the system's resilience under different resource degradation scenarios. For this purpose, we design stable embedded control systems when limited communication and computation resources are involved. The codesign of a scheduler and a controller optimizes control inputs and resource allocation in order to ensure control performance, resilience when a denial of service (DoS) attack occurs, and faster feedback control response for more critical tasks. In this project, distributed algorithms for large-scale interconnected mixed-critical systems are developed where control and communication loops are closed automatically to guarantee access to available shared resources based on each subsystem's criticality. Moreover, another solution approach focuses on extending and redesigning the existing sufficient conditions of the ISS of complex networks and applying them to decentralized robust, and adaptive control of networked control systems, and generalizing the existing algorithms of decentralized robust and/or adaptive control for large-scale networks of interconnected nonlinear control systems with uncertainties and external disturbances.