Realization of Positive Linear Systems

AbstractPositive linear systems are frequently used as mathematical models in research areas like biology and economics. The problem of classifying all minimal realizations of these systems is treated in this paper. Extensive use is made of the theory of polyhedral cones. Sufficient and necessary conditions for the existence of a positive realization are given, but the problem of minimality leads to the factorization problem for positive matrices. Ideas and results are given to come towards a solution of this factorization problem

Data-driven and Model-based Verification: a Bayesian Identification Approach

This work develops a measurement-driven and model-based formal verification approach, applicable to systems with partly unknown dynamics. We provide a principled method, grounded on reachability analysis and on Bayesian inference, to compute the confidence that a physical system driven by external inputs and accessed under noisy measurements, verifies a temporal logic property. A case study is discussed, where we investigate the bounded- and unbounded-time safety of a partly unknown linear time invariant system

Observer-based correct-by-design controller synthesis

Current state-of-the-art correct-by-design controllers are designed for full-state measurable systems. This work first extends the applicability of correct-by-design controllers to partially observable LTI systems. Leveraging 2nd order bounds we give a design method that has a quantifiable robustness to probabilistic disturbances on state transitions and on output measurements. In a case study from smart buildings we evaluate the new output-based correct-by-design controller on a physical system with limited sensor information