Papers by Marco Bergamasco
Proceedings of the 19th IFAC World Congress, 2014
5th Symposium on System Structure and Control, 2013
16th IFAC Symposium on System Identification, 2012
Abstract Accurate dynamic modelling of helicopter aeromechanics is becoming increasingly importan... more Abstract Accurate dynamic modelling of helicopter aeromechanics is becoming increasingly important, as progressively stringent requirements are being imposed on rotorcraft control systems. System identification plays an important role as an effective approach to the problem of deriving or fine tuning mathematical models for purposes such as handling qualities assessment and control system design. In this paper the problem of deriving continuous-time models for the dynamics of a small-scale quadrotor helicopter is considered. More precisely, the ...
Lecture Notes in Control and Information Sciences, 2013
Abstract The current state-of-the-art in the fields of control-oriented LPV modelling and LPV sys... more Abstract The current state-of-the-art in the fields of control-oriented LPV modelling and LPV system identification is surveyed and the potential synergies between the two research areas are highlighted and discussed. Indeed, a number of methods and tools for the development of LPV models from nonlinear systems and for the identification of black-box LPV models from input/output data have been derived, in a rather independent way, in different research communities. The relative merits of analytical and experimental ...
2012 IEEE 51st IEEE Conference on Decision and Control (CDC), 2012
Abstract The dynamics of a spacecraft equipped with magnetic actuators operating under a static a... more Abstract The dynamics of a spacecraft equipped with magnetic actuators operating under a static attitude and rate feedback control law designed using averaging theory is considered and the asymptotic behaviour of the closed-loop system as a function of the averaging scaling parameter is analysed, using bifurcation methods.
52nd IEEE Conference on Decision and Control, 2013
ABSTRACT This paper deals with the problem of model identification in continuous-time using subsp... more ABSTRACT This paper deals with the problem of model identification in continuous-time using subspace techniques. More precisely, a recently presented continuous-time predictor-based subspace identification algorithm which relies on a system transformation using the Laguerre basis is considered and a bootstrap-based approach to the problem of quantifying the variance error associated with the identified models is proposed.
Advances in Aerospace Guidance, Navigation and Control, 2013
IET Control Theory & Applications, 2013
ABSTRACT In this study, the authors present an overview of closed-loop subspace identification me... more ABSTRACT In this study, the authors present an overview of closed-loop subspace identification methods found in the recent literature. Since a significant number of algorithms has appeared over the last decade, the authors highlight some of the key algorithms that can be shown to have a common origin in autoregressive modelling. Many of the algorithms found in the literature are variants on the algorithms that are discussed here. In this study, the aim is to give a clear overview of some of the more successful methods presented throughout the last decade. Furthermore, the authors retrace these methods to a common origin and show how they differ. The methods are compared both on the basis of simulation examples and real data. Although the main focus in the literature has been on the identification of discrete-time models, identification of continuous-time models is also of practical interest. Hence, the authors also provide an overview of the continuous-time formulation of the identification framework.
2013 American Control Conference, 2013
Traditional active noise control (ANC) methods are based on adaptive filtering algorithms designe... more Traditional active noise control (ANC) methods are based on adaptive filtering algorithms designed to minimize the noise variance. The convergence of such algorithms may be jeopardized in the presence of non-Gaussian noise signals, characterized by a marked impulsiveness (and infinite secondorder moments), such as are frequently encountered in realworld acoustic settings. ANC methods have been recently extended to deal with such signals, modifying the weight update of the adaptive filter so that out-of-range samples are discarded or discounted. These methods require precise a priori knowledge of the impulsive characteristics of the noise and are generally not suitable for signals where such characteristics are timevarying. This work introduces an algorithm, based on an adaptive box-plot approach for outlier detection, which does not rely on any a priori information and yields uniformly high attenuation performance in all conditions tested in simulation.
Il presente lavoro di tesi si occupa della determinazione d'assetto e di orbita e del controllo d... more Il presente lavoro di tesi si occupa della determinazione d'assetto e di orbita e del controllo d'assetto di un satellite utilizzando la misura del campo magnetico terrestre. Parte del lavoro è stato svolto presso la società NGC Aerospace Ltd, situata in Sherbooke, Canada, specializzata nella simulazione e nel controllo di satelliti ed impegnata in diversi progetti per conto dell'Agenzia Spaziale Europea (ESA), tra cui il progetto Proba 2.
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Experiment design plays a fundamental role in the practice of model identification. This is speci... more Experiment design plays a fundamental role in the practice of model identification. This is specially true in the case of MIMO systems, for which the large number of degrees of freedom available in the setup of experiments calls for careful planning in order to ensure the best possible excitation for the system while meeting the relevant operational requirements during experiments (such as, e.g., flight test constraints in aircraft and rotorcraft model identification). In this paper the problem of defining optimal input sequences for MIMO model identification is considered. The proposed method builds on previous results and allows the optimisation of suitable scalar functions of the Fisher information matrix by means of a computationally sound procedure for the design of both step-wise and multi-cyclic MIMO inputs. The design procedure is evaluated by designing MIMO experiments to estimate the parameters of a physical model for a rotorcraft platform.
Journal of Sound and Vibration, Jan 1, 2011
Active noise control (ANC) is a methodology for attenuating noise based on adaptive signal proces... more Active noise control (ANC) is a methodology for attenuating noise based on adaptive signal processing algorithms. ANC is well assessed for the attenuation of Gaussian noise, but the rejection of non-Gaussian impulsive noise signals represents a much more critical task, that may even impair algorithm convergence. To overcome this problem the adaptive filter weight update process must be modified by discarding or discounting samples associated with impulsive noise. This can be done either by modeling the impulsive noise with a non-Gaussian distribution such as the Symmetric α-stable (SαS) distribution, or by applying outlier detection method. With both approaches the accuracy in the noise description appears to be crucial for effective noise reduction. This paper proposes two novel ANC algorithms for the attenuation of impulsive noise both for invariant and timevarying noise distributions. The first one is based on the on-line estimation of an SαS model of the noise probabilistic description. The second relies on a simple on-line recursive procedure that reliably estimates amplitude thresholds for outlier detection. Both methods compare favorably with competitor approaches, while maintaining a sufficiently low algorithm complexity. Several examples are * Corresponding author, voice (
World Congress, Jan 1, 2011
IEEE CDC, Jan 1, 2011
This paper deals with the problem of model identification in continuous-time using subspace techn... more This paper deals with the problem of model identification in continuous-time using subspace techniques. More precisely, a recently presented continuous-time predictorbased subspace identification algorithm which relies on a system transformation using the Laguerre basis is considered and a recursive counterpart is developed.
International Journal of …, Jan 1, 2010
This article deals with the problem of optimal static output feedback control of linear periodic ... more This article deals with the problem of optimal static output feedback control of linear periodic systems in continuous time, for which a continuous-time approach, which allows to deal with both stable and unstable open loop systems, is presented. The proposed approach is tested on the problem of designing attitude control laws for a Low-Earth Orbit (LEO) satellite on the basis of feedback from a triaxial magnetometer and a set of highprecision gyros. Simulation results are used to demonstrate the feasibility of the proposed strategy and to evaluate its performance.
Decision and Control (CDC), Jan 1, 2010
Abstract Active noise control (ANC) algorithms are generally designed to obtain the attenuation o... more Abstract Active noise control (ANC) algorithms are generally designed to obtain the attenuation of gaussian noise signals using suitable adaptive signal processing algorithms. The rejection of non-gaussian impulsive noise signals represents a much more critical task, with respect to which standard ANC algorithms generally fail to provide a satisfactory solution, due to convergence and instability problems. This paper proposes a novel ANC algorithm for the attenuation of impulsive noise, based on the online estimation of an ...
Decision and Control (CDC), Jan 1, 2010
This paper deals with the problem of continuoustime model identification and presents a subspace-... more This paper deals with the problem of continuoustime model identification and presents a subspace-based algorithm capable of dealing with data generated by systems operating in closed-loop. The algorithm is developed by reformulating the identification problem from the continuous-time model to an equivalent one to which discrete-time subspace identification techniques can be applied. More precisely, the considered approach corresponds to the projection of the input-output data onto an orthonormal basis, defined in terms of Laguerre filters. In this framework, the PBSID subspace identification algorithm, originally developed in the case of discrete-time systems, can be reformulated for the continuoustime case. Simulation results are used to illustrate the achievable performance of the proposed approach with respect to existing methods available in the literature.
Control Theory & Applications, IET, Jan 1, 2011
This study deals with the problem of continuous-time model identification and presents two subspa... more This study deals with the problem of continuous-time model identification and presents two subspace-based algorithms capable of dealing with data generated by systems operating in closed loop. The algorithms are developed by reformulating the identification problem from the continuous-time model to equivalent ones to which discrete-time subspace identification techniques can be applied. More precisely, two approaches are considered, the former leading to the so-called all-pass domain by using a bank of Laguerre filters applied to the input -output data and the latter corresponding to the projection of the input -output data onto an orthonormal basis, again defined in terms of Laguerre filters. In both frameworks, the Predictor-Based Subspace Identification, originally developed in the case of discrete-time systems, can be reformulated for the continuous-time case. Simulation results are used to illustrate the achievable performance of the proposed approaches with respect to existing methods available in the literature.
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Papers by Marco Bergamasco