Multi-objective optimal control with safety as a priority.

This work develops a lexicographic approach to multi-objective optimal control on models for cyber-physical systems, encompassing in particular stochasticity, limited access to model variables (partial observations), and possibly hybrid (continuous and discrete) dynamics (with the finite state POMDP framework as a known special instance). The technique is showcased in two new case studies in the area of building automation systems. Technically, the main achievements of this work are: The application of the lexicographic framework to multi-objective optimization including quantitative probabilistic safety requirements, thus leading to a principled and scalable integration of correct-by-design synthesis for safety and optimal synthesis for performance; the novel extension of the lexicographic framework to partially-observed stochastic models with continuous (possibly hybrid) dynamics; the emphasis on computational aspects, including the use of compact and approximate representations of value functions combined with the quantification of error bounds on model abstractions.