GUARANTEED NONLINEAR STATE ESTIMATION FOR CONTINUOUS-TIME DYNAMICAL MODELS FROM DISCRETE-TIME MEASUREMENTS

Abstract This paper is about bounded-error state estimation for models described by a continuous-time state equation from discrete-time measurements. A guaranteed solution to this problem is proposed, based on Muller's theorems and interval analysis. This technique allows, at any time instant, the characterization of the set of all state vectors that are consistent with the error bounds, measurements and model structure. Joint state and parameter estimation is also possible. The resulting methodology is illustrated on the estimation of the state of a compartmental model.

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