Abstraction-Based Parameter Synthesis for Multiaffine Systems

ion-Based Parameter Synthesis for Multiaffine Systems Sergiy Bogomolov1(B), Christian Schilling, Ezio Bartocci, Gregory Batt, Hui Kong, and Radu Grosu 1 IST Austria, Klosterneuburg, Austria [email protected] 2 University of Freiburg, Freiburg im Breisgau, Germany 3 Vienna University of Technology, Vienna, Austria 4 INRIA Paris-Rocquencourt, Paris, France Abstract. Multiaffine hybrid automata (MHA) represent a powerful formalism to model complex dynamical systems. This formalism is particularly suited for the representation of biological systems which often exhibit highly non-linear behavior. In this paper, we consider the problem of parameter identification for MHA. We present an abstraction of MHA based on linear hybrid automata, which can be analyzed by the SpaceEx model checker. This abstraction enables a precise handling of time-dependent properties. We demonstrate the potential of our approach on a model of a genetic regulatory network and a myocyte model. Multiaffine hybrid automata (MHA) represent a powerful formalism to model complex dynamical systems. This formalism is particularly suited for the representation of biological systems which often exhibit highly non-linear behavior. In this paper, we consider the problem of parameter identification for MHA. We present an abstraction of MHA based on linear hybrid automata, which can be analyzed by the SpaceEx model checker. This abstraction enables a precise handling of time-dependent properties. We demonstrate the potential of our approach on a model of a genetic regulatory network and a myocyte model.