arXiv subjects

Alexandre Sanfelici Bazanella

Publications and source records attributed to Alexandre Sanfelici Bazanella.

7 recordsLinked to original sources

arXiv2026

Optimal excitation and measurement patterns for networks with tree topology

In this work we evaluate the excitation and measurement patterns (EMP) for networks with tree topology. We investigate guidelines for the selection of the minimal EMPs, i.e. those with the least number of excited and measured nodes combined, for which the accuracy obtained, in terms of the trace of the asymptotic covariance matrix, is optimal. We introduce the concept of partial information matrix as a means to systematically obtain the information matrix for any dynamic network. For a specific tree class, called cross, we show that the accuracy of a particular module depends on the magnitude of the parameters to be estimated. Furthermore, when all factors are equal, it is best to excite. %we show that for small magnitudes of this parameter, it is best to excite. We extend a topological condition for branches under which the accuracy of a particular module of the network is independent of the other parameters from the tree. We provide a numerical analysis showing that our guidelines could be used as a selection tool for minimal EMPs for tree networks.

physics.soc-ph↗

arXiv2026

The restrictive conditions to solve LTI Systems by Ordinary Differential Equations

Ordinary differential equations (ODE's) are a cornerstone of systems and control theory. Accordingly, they are standard material in undergraduate programs in engineering and there is abundant didactic literature about this topic. Yet, the solution methods and formulas prescribed in this didactic literature are unclear about the assumptions behind their derivation and thus about the limits of their applicability. Specifically, smoothness of the input is rarely discussed, even though it is a critical property to define the character of the solutions and the validity of the methods and formulas prescribed. On the other hand, the relationships with the state space representation (SSR) of linear systems is absent from this same literature and only marginally discussed in more advanced texts. In this paper we detail these gaps left behind in the didactic literature, then we provide a formal delimitation of the boundaries of the standard solutions and methods for linear ODE's. Our analysis relies on some key properties of state space representations, so we establish the formal connections between ODEs and SSR's, defining an equivalence between the two that is absent in the literature and is of conceptual interest by itself.

eess.SY↗

arXiv2026

Improving the GMAW process through current control

A control strategy for the electrical current in GMAW processes is proposed. The control is in closed-loop, designed by formal methods, based on a mathematical model of the electrical behavior of the GMAW process, and implemented in C+ language in a microcontroller. The model consists of a switched equivalent electrical circuit whose parameters are obtained in a data-driven manner. The strategy is tested in numerous experiments with both manual and robot welding, showing improvements in the overall welding process.

eess.SY↗

arXiv2025

Learning about passivity from data

This paper presents a data-driven methodology to estimate the storage function of a passive system. The methodology consists in parametrizing the storage function with a dictionary then running a linear program. Results on a benchmark are presented to illustrate its properties, including its robustness to noise. Various uses of the storage function that do not require knowledge of a model are also discussed.

eess.SY↗

arXiv2022

Nonlinear VRFT with LASSO

Virtual Reference Feedback Tuning (VRFT) is a well known and very successful data-driven control design method. It has been initially conceived for linear plants and this original formulation has been much explored in the literature, besides having already found many practical applications. A nonlinear version of VRFT has been proposed early on, but not much explored later on. In this paper we highlight various issues involved in the application of nonlinear VRFT and propose the inclusion of L1 regularization in its formulation. We illustrate by means of two simple examples the critical role played by two aspects: the L1 regularization and the choice of dictionary used to describe the nonlinearity of the controller.

eess.SY↗

arXiv2020

VRFT with ARX controller model and constrained total least squares

The virtual reference feedback tuning (VRFT) is a non-iterative data-driven (DD) method employed to tune a controller's parameters aiming to achieve a prescribed closed-loop performance. In its most common formulation, the parameters of a linearly parametrized controller are estimated by solving a least squares (LS) problem, which in the presence of noise leads to a biased estimate of the controller's parameters. To eliminate this bias, an instrumental variable (IV) variant of the method is usual, at the cost of increasing significantly the estimate's variance. In the present work, we propose to apply the constrained total least squares (CTLS) solution to the VRFT problem. We formulate explicitly the VRFT solution with CTLS for controllers described by an autoregressive exogenous (ARX) model. The effectiveness of the proposed solution is illustrated by two case studies in which it is compared to the usual VRFT solutions and to another, statistically efficient, design method.

eess.SY↗

arXiv2020

Optimal allocation of excitation and measurement for identification of dynamic networks

In this paper, the problem of choosing the best allocation of excitations and measurements for the identification of a dynamic network is formally stated and analyzed. The best choice will be one that achieves the most accurate identification with the least costly experiment. Accuracy is assessed by the trace of the asymptotic covariance matrix of the parameters estimates, whereas the cost criterion is the number of excitations and measurements. Analytical and numerical results are presented for two classes of dynamic networks in state space form: branches and cycles. From these results, a number of guidelines for the choice emerge, which are based either on the topology of the network or on the relative magnitude of the modules being identified. An example is given to illustrate that these guidelines can to some extent be applied to networks of more generic topology.

math.OC↗