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In this paper, we study connections between the classical model-basedapproach to nonlinear system theory, where systems are represented byequations, and the nonlinear behavioral approach, where systems are defined assets of trajectories. In particular, we focus on equivalent representations ofthe systems in the two frameworks for the problem of simulating a futurenonlinear system trajectory starting from a given set of noisy data. The goalalso includes extending some existing results from the deterministic to thestochastic setting.

Simulation of Nonlinear Systems Trajectories: between Models and Behaviors