Giuseppe Franzè

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Optimal H∞ deconvolution filters robust fault detection of uncertain polytopic linear systems subject to unknown input disturbance are described. The filter must be capable to satisfy two sets of H∞ constraints: the first is a disturbance attenuation and decoupling requirement whereas the second expresses the capability of the filter to enhance the fault(More)
A novel robust predictive control algorithm for input-saturated uncertain linear discrete-time systems with structured norm-bounded uncertainties is presented. The solution is based on the minimization, at each time instant, of a LMI convex optimization problem obtained by a recursive use of the S-procedure. The general case of N free moves is presented.(More)
The paper addresses the obstacle avoidance motion planning problem for ground vehicles operating in uncertain environments. By resorting to set-theoretic ideas, a receding horizon control algorithm is proposed for robots modelled by linear time-invariant (LTI) systems subject to input and state constraints and disturbance effects. Sequences of inner(More)
Vandermonde matrices, defined by Vij = xi−1 j , xj ∈ C, are still a topical subject in matrix theory and numerical analysis. The interest arises as they occur in applications, for example in polynomial and exponential interpolation, and because they are ill-conditioned, at least for positive or symmetric real nodes [4]. The special structure of V allows us(More)
We propose a novel receding horizon strategy for Networked Control Systems described by uncertain polytopic linear plants subject to time-varying delays and data-losses. We make use of sequences of pre-computed inner approximations of the one-step ahead state prediction sets on-line exploited as target sets for state predictions. The present approach is(More)