Gilberto Pin

This article addresses the output regulation problem for linear systems whose model is not known a priori but are internally stable or have achieved internal stability through feedback. The article provides a perspective that complements classical internal model-based methodologies. The paradigm we follow emphasizes adaptive feedforward control, signifying all those design methodologies that position a model of the signal to be tracked or rejected by a controlled system outside the primary feedback loop responsible for system stabilization.

This work describes and compares two phase-locked-loop (PLL) algorithms aimed at tracking a biased sinusoidal signal with unknown frequency, amplitude, and phase, with inherent robustness to dc offset. The proposed methods endow quadrature PLLs, renowned for their excellent tracking performance, with frequency-adaptation capability, while providing robust global stability certificates. The large-gain global stability, proved by Lyapunov-like arguments borrowed from adaptive control theory, represents a major benefit when compared to the conventional PLLs, whose convergence instead can be proved only locally by small-signal analysis or small-gain assumptions. In this connection, the proposed algorithms represent the first frequency-adaptive and dc-bias rejecting PLL-type architectures with Lyapunov-certified global stability. When used for signal tracking, the proposed methods are shown to outperform the adaptive observer, especially in noisy conditions. Moreover, they provide more accurate frequency estimates than existent frequency-adaptive PLLs, showing enhanced robustness in facing both phase-noise and measurement perturbations.

In this note, the problem of jointly estimating the state and the parameters of continuous-time systems is addressed. Making use of suitably designed Volterra integral operators, the proposed estimator does not need the availability of time-derivatives of the measurable signals and the dependence on the unknown initial conditions is removed. As a result, the estimates converge to the true values in arbitrarily short time in a noise-free scenario. In the presence of bounded measurement and process disturbances, the estimation error is shown to be bounded. The numerical implementation aspects are dealt with and extensive simulation results are provides showing the effectiveness of the estimator.

The paper considers the problem of designing Adaptive Feedforward Control (AFC) systems for uncertain SISO linear systems perturbed by multi-sinusoidal disturbances of known frequencies. The proposed approach removes the longstanding assumption that either the sign of the real part or the imaginary part of the transfer function of a stable plant at the frequency of excitation be known for AFC to be applicable, which is referred to in this paper as an SPR-like condition. Notable features of the solution are that persistence of excitation is not required and stability analysis tools based on averaging are avoided; hence, the requirement of an exponentially stable equilibrium for the closed-loop system is circumvented.

The derivative estimation problem is addressed in this paper by using Volterra integral operators which allow to obtain the estimates of the time derivatives with fast convergence rate. A deadbeat state observer is used to provide the estimates of the derivatives with a given fixed-time convergence. The estimation bias caused by modelling error is characterised herein as well as the ISS property of the estimation error with respect to the measurement perturbation. A number of numerical examples are carried out to show the effectiveness of the proposed differentiator also including comparisons with some existing methods.

This paper presents a novel framework for the problem of target localization based on the range information collected by a single mobile agent. The proposed methodology exploits the algebra of Volterra integral operators to annihilate the influence of initial conditions on the transient phase, thus achieving a deadbeat performance. The robustness properties against additive measurement perturbations are analyzed, and the bias caused by the time discretization is characterized as well. Extensive simulation results and comparisons are provided showing the effectiveness of the proposed technique in coping with both stationary and drifting targets.

Parallel operation of multiple grid-connected power converters through LCL filters is known to have the potential problem of triggering oscillations in the ac mains. Such oscillatory frequencies are not integral multiples of the fundamental frequency and hence form a new source of interharmonics. Early detection of such oscillations is essential for the parallel power converters to move out of the unstable zone. This paper presents an online observer-based algorithm that can perform fast detection of interharmonics within a specified frequency band. The algorithm has been adopted in a specific and reduced form from an integral observer algorithm for detection of fundamental and interharmonic voltage components in the ac mains. A new method based on the kernel signal for fast interharmonic detection is proposed and practically verified. It has been implemented in a digital controller to detect oscillations such as those occurring between two grid-connected power converters. The practical results indicate that the algorithm can locate such frequency within the specific frequency band within 1 mains cycle.