A challenging paradigm in the design of modern engineered systems are cyber–physical systems. Cyber–physical systems are complex, heterogeneous, spatially distributed systems where physical processes interact with distributed computing units through non-ideal communication networks. Key features of cyber–physical systems are heterogeneity and complexity. Indeed, while physical processes are generally described by continuous and/or hybrid processes, computing units are generally described by finite state machines or other more sophisticated models of computation. To complicate things, communication infrastructures, conveying information in sub–systems of cyber–physical systems, are characterized by a number of non–idealities that are needed to be considered towards a robust control design of such systems. The paradigm of symbolic models is promising of being appropriate in coping with the inherent heterogeneity of cyber–physical systems. Symbolic models are abstract descriptions of control systems where any state corresponds to an aggregate of continuous states and any control label to an aggregate of control inputs. Since symbolic models are of the same nature of the mathematical models of the computing units, they offer a sound approach for solving control problems in which software and hardware interact with the physical world. Furthermore by using symbolic models, one can address a wealth of novel specifications that are difficult to enforce by means of conventional control design methods. Examples of such specifications include logic specifications expressed in linear temporal logic or automata. In this talk I will give an overview of my research in this area and show an approach based on symbolic models for the control design of cyber-physical systems.
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