Diego Regruto

Learn More
In this note, we present a two-stage procedure for deriving parameters bounds in Hammerstein models when the output measurement errors are bounded. First, using steady-state input–output data, parameters of the nonlinear part are tightly bounded. Then, for a given input transient sequence we evaluate tight bounds on the unmeasurable inner signal which,(More)
In this paper, a vehicle dynamic control (VDC) system for tracking the desired vehicle behavior is developed. A 2-DOF control structure is proposed to prevent vehicle skidding during critical maneuvers through the application of differential braking between the right and left wheels in order to control yaw motion. The feedforward filter is a reference(More)
In this technical note, the set membership error-in-variables identification problem is considered, that is the identification of linear dynamic systems when both output and input measurements are corrupted by bounded noise. A new approach for the computation of parameter uncertainty intervals is presented. First, the identification problem is formulated in(More)
In this note we present a two-stage procedure for deriving parameters bounds of linear systems with input backlash when the output measurement errors are bounded. First, using steady-state input-output data, parameters of the nonlinear dynamic block are tightly bounded. Then, given a suitable PRBS input sequence we evaluate tight bounds on the unmeasurable(More)
In this paper we consider the identification of linear systems, a priori known to be stable, from input-output data corrupted by bounded noise. By taking explicitly into account a priori information on system stability, a formal definition of the feasible parameter set for stable linear system is provided. On the basis of a detailed analysis of the(More)
In this paper the identification of SISO linear parameter varying (LPV) models when both the output and the time-varying parameter measurements are affected by bounded noise is considered. First, the problem is formulated in terms of Error-in-variables (EIV) identification in presence of bounded noise. Then, a polytopic outer approximation of the feasible(More)
In this paper we present a procedure for the evaluation of bounds on the parameters of Hammerstein systems, fromoutputmeasurements affected by bounded errors. The identification problem is formulated in terms of polynomial optimization, and relaxation techniques, based on linear matrix inequalities, are proposed to evaluate parameter bounds by means of(More)
In this technical note we present a procedure for the identification of Hammerstein systems from measurements affected by bounded noise. First, we show that computation of tight parameter bounds requires the solution to nonconvex optimization problems where the number of decision variables increases with the length of the experimental data sequence. Then,(More)