摘要：AbstractA non-parametric technique for modeling of systems with unknown nonlinear Lipschitz dynamics is presented. The key idea is to successively utilize measurements to approximate thegraphof the state-update function of the system dynamics using envelopes described by quadratic constraints. The proposed approach is then used for computing outer approximations of the state-update function using convex optimization. We highlight the efficacy of the proposed approach via a detailed numerical example.
关键词：KeywordsDiscrete-time systemsNonparametric MethodsConvex OptimizationRecursive IdentificationAutonomous Systems
