Gilberto Pin

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In this paper, the robust state feedback stabilization of uncertain discrete-time constrained nonlinear systems in which the loop is closed through a packet-based communication network is addressed. In order to cope with model uncertainty, time-varying transmission delays, and packet dropouts (typically affecting the performances of networked control(More)
In this note, a robust model predictive control scheme for constrained discrete-time nonlinear systems affected by bounded disturbances and state-dependent uncertainties is presented. In order to guarantee the robust satisfaction of the state constraints, restricted constraint sets are introduced in the optimization problem, by exploiting the(More)
The present paper is concerned with the robust state feedback stabilization of uncertain discrete-time constrained nonlinear systems in which the loop is closed through a packet-based communication network. In order to cope with model uncertainty, time-varying transmission delays and packet dropouts which typically affect networked control systems, a robust(More)
In this paper, an Enhanced Phase-Locked Loop (EPLL) architecture is proposed to deal with the problem of estimating the amplitude, the frequency and the phase of a sinusoidal signal from a noisy measurement. The EPLL scheme is chacterized by an error filter and a phase-feedforward term that are embedded in the estimation algorithm for improved noise(More)
This paper is concerned with the robust rejection of harmonic disturbances with unknown frequency and amplitude affecting uncertain linear system. The developed control scheme combines the properties of adaptive feedforward cancellation (AFC) techniques with the phase and frequency detection capabilities provided by a nonlinear frequency estimation(More)
In this note a globally stable methodology is proposed to estimate the frequency, phase, and amplitude of a sinusoidal signal affected by additive structured and bounded unstructured disturbances. The structured disturbances belong to the class of time-polynomial signals incorporating both bias and drift phenomena. Stability and robustness results are given(More)
In this work, a robust method to estimate sinusoidal signals of unknown frequency, amplitude and phase is described. The stability properties of the devised estimation method under perturbed condition are studied by Input-to-State Stability (ISS) analysis. Compared to averaging approaches, the ISS-Lyapunov theory allows to study the stability for any value(More)
This paper is concerned with the robust receding horizon control of constrained discrete-time nonlinear systems affected by model uncertainty. A class of uncertainties entailing norm-bounded additive state dependent and non-state-dependent uncertainties is considered. In order to robustly enforce the constraints, a technique based on constraints tightening(More)
This work deals with a novel theoretical framework, based on the algebra of Volterra linear integral operators, aimed at designing non-asymptotic state observers for continuous-time SISO linear systems. We show that the design of observers with finite-time convergence of the estimation error can be carried out by appropriately choosing the kernels of(More)
The paper deals with an adaptive observer methodology for estimating the parameters of an unknown sinusoidal signal from a measurement perturbed by structured and unstructured uncertainties. The proposed technique makes it possible to handle measurement signals affected by structured uncertainties like, for example, bias and drifts which are typically(More)