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This article proposes an adaptive input-output Feedback Linearization Control ( FLC ) techniques for Synchronous Reluctance Motor ( SynRM ) drives, taking into consideration the iron losses. As a main original content, this work proposes a control law based on a new dynamic model of the SynRM including iron losses as well as the on-line estimation of the static inductances. The on-line estimation of the SynRM static inductances permits to inherently take into consideration the magnetic saturation phenomena occuring on both axes. As a major result, it permits a null stator current steady state tracking error even with a proportional derivative controller. The estimation law is obtained thanks to a Lyapunov-based analysis and thus the stability of the entire control system, including the estimation algorithm, is intrinsically guaranteed. The proposed adaptive FLC technique, has been tested experimentally on a suitably developed test set-up, and compared experimentally with its non-adaptive versions in both tuned and detuned working conditions. Moreover, a sensitivity analysis of the performance of the adaptive FLC to the variations of the stator resistance at low speed has been made. Finally, an analysis of the effects of the iron losses on the control performance and stability at high speed in the field weakening region at medium/high loads has been made.

We propose an asymptotic position and speed observer for inertial navigation in the case where the position measurements are sporadic and affected by noise. We cast the problem in a hybrid dynamics framework where the continuous motion is affected by unknown continuous-time disturbances and the sporadic position measurements are affected by discrete-time noise. We show that the peculiar hybrid cascaded structure describing the estimation error dynamics is globally finite-gain exponentially ISS with gains depending intuitively on our tuning parameters. Experimental results, as well as the comparison with an Extended Kalman Filter (EKF), confirm the effectiveness of the proposed solution with an execution time two orders of magnitude faster and with a simplified observer tuning because our bounds are an explicit function of the observer tuning knobs

This article proposes a new input-output feedback linearization control (FLC) technique of linear induction motors (LIMs), taking into consideration both the dynamic end-effects and the iron losses. Starting from a previously conceived dynamic model, including the dynamic end-effects and the iron losses, all the theoretical framework of the FLC has been developed. The proposed FLC improves a previous version of FLC in accounting also the iron losses, which in LIMs with fixed-secondary sheet play a pivotal role more than in rotating induction motors (RIMs). The proposed FLC has been experimentally tested on a suitably developed test setup, and experimental comparisons between the proposed FLC, the classic field-oriented control and a previously developed FLC, not accounting for the iron losses, have been shown in variable flux working conditions.

In 2020 the European Commission approved the GND (Green New Deal), a strategic plan aimed at the decarbonization of the EU by 2050. In this scenario, the diffusion of alternative renewable energy sources (RESs) play a key role, particularly electric energy production from wind and photovoltaic power plants. Regardless, the nonprogrammable nature of these power sources led recent studies to focus the interest on the power-to-gas solution (PtG), consisting of the electrolytic transformation of excesses of unused electric energy into hydrogen. The complexity of this technology requires the development of strategic optimization models aimed at finding the best locations for new PtG plants in specific territorial scenarios. This paper presents the development of a GIS-based optimization model that combines an operational research approach with territorial services based on geographic information system (GIS) data. The study is located in Sicily (Italy), considering the large renewable energy penetration in the larger Mediterranean island. The developed model allows us to find the best location for new PtG installations in the considered area by combining GIS automated processing with cost function resolution. The results of this work could be useful in the years to come in light of the rapid spread of hydrogen energy production in Italy.

We suggest a new mechanism—the liquidity insurance channel—based on the widespread reliance of high credit quality firms on bank credit lines for liquidity management. Our model matches the patterns of usage of loans and credit lines in the cross‐section of firms and defines the conditions under which shocks to bank health affect primarily low or high credit quality firms. Our framework can explain why credit line origination is more cyclical than loan origination. Overall, we uncover a novel interaction between bank health and economic activity through the provision of bank credit lines to high credit quality firms.

This paper proposes a control system for a quadratic boost DC/DC converter in a wide range of operations, based on an inner loop with a sliding mode controller, for reaching a desired equilibrium state, and an outer loop with integral-type controller, for assuring robustness against load and input voltage variations and converter parameter uncertainties. The sliding mode controller is designed with the extended linearization method and assures local asymptotic stability, whereas the integral controller is designed using classical frequency methods, and assures input–output stability. It is shown that the proposed controller also deals with the sudden changes in the nominal operating conditions; thus, if a change of the operating conditions takes place, the proposed control scheme automatically creates a sliding regime which stabilizes the converter trajectories to the new equilibrium point. Experimental results carried out on a suitably developed test set up show the effectiveness of the proposed approach.

We review the literature on debt structure, which is a central element in a firm's capital structure. We first survey both theoretical and empirical research pertaining to debt characteristics—maturity and priority—and debt types—bank loans, corporate bonds, credit lines, commercial paper, and capital leases. We then present comprehensive empirical evidence on public US firms’ debt structure over the period 2002–2018, highlighting that more than three-quarters of US firms concentrate their borrowing in one debt type, and offer some suggestive explanations for the observed pattern. Finally, we discuss directions for future research, including a better understanding of debt structure choices by non-US firms and by private firms, the cross-sectional and temporal variations in debt structure, the corporate policy implications of firms’ debt structure choices, and the interaction between types of assets and debt structure.

This paper proposes an adaptive input-output Feedback Linearization (FL) techniques for Synchronous Reluctance Motor (SynRM) drives, taking into consideration the iron losses. As a main original content, this work proposes a control law based on a new dynamic model of the SynRM including iron losses as well as the on-line estimation of the static inductances. The on-line estimation of the SynRM static inductances permits to inherently take into consideration the magnetic saturation phenomena occuring on both axes. The estimation law is obtained thanks to a Lyapunov-based analysis and thus the stability of the entire control system, including the estimation algorithm, is intrinsically guaranteed. The proposed adaptive FL control improves formerly developed non linear controllers, characterized either by disregarding the saturation phenomenon or by considering it on the basis of an apriori known model. The proposed control technique, has been tested experimentally on a suitably developed test set-up.

The aim of this paper is the design of a hybrid nonlinear observer for mobile vehicles. The main problem is that position and velocity measurements are provided with a very low frequency, and the time between two consecutive measurements could be not constant, but it could vary randomly within a certain interval of time. For this reason the proposed observer has been contextualized in the hybrid systems framework. The convergence analysis of the estimation error has been carried out, and the sensitivity analysis has been performed in order to evaluate the bound of the estimation error when the measurements are biased and/or noisy. Simulation and experimental results, carried out on a mobile vehicle, show the feasibility of the proposed observer and the good behaviors in terms of estimation error that can be achieved

The recent diffusion of RES (Renewable Energy Sources), considering the electric energy produced by photovoltaic and wind plants, brought to light the problem of the unpredictable nature of wind and solar energy. P2G (Power to Gas) implementation seems to be the right solution, transforming curtailed energy in hydrogen. The choice of the settlement of P2G plants is linked to many factors like the distances between the gas grid and the settlement of RES plants, the transportation networks, the energy production, and population distribution. In light of this, the implementation of a Multi-Criteria Analysis (MCA) into a Geographic Information System (GIS) processing represents a good strategy to achieve the goal in a specific territorial asset. In this work, this method has been applied to the case of study of Sicily (Italy). The paper shows in detail the geomatic semi-automated processing that allows to find the set of possible solutions and further to choose the best localization for new P2G plants, connected to a Relational Database Management System (RDBMS) and integrated with a WebGIS visualization for real-time analysis. This system is useful for the management, the development, and the study of hydrogen technologies, in order to link the electrical network and the gas network datasets with economical and infrastructural assets through GIS processing. In the future new factors will join in the process as policies on hydrogen take shape.

International audience; A novel estimation strategy for inertial navigation in indoor/outdoor environments is proposed with a specific attention to the sporadic nature of the non-periodic measurements. After introducing the inertial navigation model, we introduce an observer providing an asymptotic estimate of the plant state. We use a hybrid dynamical systems representation for our results, in order to provide an effective, and elegant theoretical framework. The estimation error dynamics with the proposed observer shows a peculiar cascaded interconnection of three subsystems (allowing for intuitive gain tuning), with perturbations occurring either on the jump or on the flow dynamics (depending on the specific subsystem under consideration). For this structure, we show global exponential stability of the error dynamics. Hardware-in-the-loop results confirm the effectiveness of the proposed solution.

Unlike other debt, most bank loans have floating rates mechanically tied to monetary policy rates. Hence, monetary policy can directly affect the liquidity and balance sheet strength of firms through existing loans. We show that firms—especially financially constrained firms—with more unhedged loans display a stronger sensitivity of their stock price, cash holdings, inventory, and fixed capital investment to monetary policy. This effect disappears when policy rates are at the zero lower bound, revealing a new limitation of unconventional monetary policy. The floating-rate channel is at least as important as the bank lending channel operating through new loans.

This paper describes how the ADRC (Active Disturbance Rejection Control) strategy can be successfully applied to SynRM (Synchronous Reluctance Motor) drives. The ADRC is an adaptive robust extension of the input-output Feedback Linearization Control (FLC). Its main feature is that the nonlinear transformation of the state is computed on-line and not by using the model. As a consequence, any unmodelled dynamics or uncertainty of the parameters can be addressed. The control strategy has been verified successfully with experimental tests confirming the high dynamic response of the drive.

This paper proposes an input-output feedback linearization techniques for linear induction motors, taking into consideration the dynamic end-effects. As a main original content, this work proposes a new control law based on the on-line estimation of the induced-part time constant. The estimation law is obtained thanks to a Lyapunov based analysis and thus the stability of the entire control system, including the estimation algorithm, is intrinsically guaranteed. Moreover, with such an approach even the on-lihe variation of the induced-part time constant with the speed is retrieved, thus improving the behavior of previously developed approaches where such a variation vs. speed is considered a priori known. The proposed control technique, integrating the on-line induced-part time constant estimation, is tested by means of simulations and experiments carried out on a suitably developed test set-up. (C) 2016 Elsevier Ltd. All rights reserved.

A buck-based, isolated, high-voltage-ratio DC/DC converter that allows supplying a proton exchange membrane (PEM) electrolyzer from a micro-wind energy conversion system ( μ WECS) has been recently presented. It exhibits low ripple at the switching frequency on the output voltage and current and represents an attractive solution for low-cost hydrogen production. In this paper, a more accurate mathematical model of such a converter is derived and discussed. Then, a model-based robust controller is designed in the frequency domain using the Internal Model Control structure and in the context of H 2 ∕ H ∞ optimal control. The controller satisfies the condition of robust stability and behavior, i.e., it guarantees stability and the desired behavior in the presence of parametric variations and unmodeled dynamics. In particular, the robustness in the presence of variations of DC-link voltage and buck input inductance is verified from the theoretical point of view. The validation of the controller is performed by integrating it into a detailed switching model of the DC/DC converter, which is implemented on a widely used circuit-oriented simulator. Good results are obtained in terms of dynamic and steady-state behavior, even in the presence of the above variations. A comparison is also carried out with the results obtained using an integral controller designed on the basis of the above mathematical model. Such a comparison shows the superiority of the robust controller over the integral controller in all the operating conditions, especially when the DC-link voltage is subject to significant variations and is affected by a non-negligible low-frequency ripple due to the presence of the diode rectifier at the output of the μ WECS.

This paper deals with hydrogen production via water electrolysis, which is considered the most attractive and promising solution. Specifically, the use of renewable energy sources, such as wind electric power generators, is hypothesized for supplying the electrolyzer, aiming to strongly reduce the environmental impact. In particular, micro-wind energy conversion systems (μWECSs) are attractive for their low cost and easy installation. In order to interface the μWECS and the electrolyzer, suitable power conditioning systems such as step-down DC-DC converters are mandatory. However, due to the requested high conversion ratio between the DC bus grid, i.e. the output of a three-phase diode rectifier connected to the output of the electric generator, and the rated supply voltage of the electrolyzer, the classic buck converter alone is not suitable. Therefore, a converter is proposed and designed, consisting of a buck converter, a full-bridge IGBT converter, a single-phase transformer, and a diode bridge rectifier; LC filters are also included between buck and full-bridge converters, and at the output of the diode bridge rectifier with the aim of reducing the ripple on currents and voltages. The components of the described physical system from the output of the three-phase rectifier up to the electrolyzer are then modeled assuming the transformer as ideal, and the model is employed for designing a PI-type controller. Experimental results are provided in order to demonstrate the effectiveness of the developed converter and its control for these applications.

This work deals with the tuning of an Extended Kalman Filter for sensorless control of induction motors for electrical traction in automotive. Assuming that the parameters of the induction motor-load model are known, Genetic Algorithms are used for obtaining the system noise covariance matrix, considering the measurement noise covariance matrix equal to the identity matrix. It is shown that only stator currents have to be acquired for reaching this objective, which is easy to accomplish using Hall-effect transducers. In fact, the Genetic Algorithm minimizes, with respect to the system covariance matrix, a suitable measure of the displacement between the stator currents experimentally acquired and those estimated by the Kalman filter. The proposed method is validated by experiments.

This paper deals with convergence analysis of the extended Kalman filters (EKFs) for sensorless motion control systems with induction motor (IM). An EKF is tuned according to a six-order discrete-time model of the IM, affected by system and measurement noises, obtained by applying a first-order Euler discretization to a six-order continuous-time model. Some properties of the discrete-time model have been explored. Among these properties, the observability property is relevant, which leads to conditions that can be directly linked with the working conditions of the machine. Starting from these properties, the convergence of the stochastic state estimation process, in mean square sense, has been shown. The convergence is also explored with reference to the difference between the samples of the state of the continuous-time model and that estimated by the EKF. The results theoretically achieved have been also validated by means of experimental tests carried out on an IM prototype.

By means of a difference-in-differences approach (sigma-DID), we investigate the effect that hedging has on corporate risk. Examining the relation between hedging and the idiosyncratic variance of stock returns, we show that when new commodity derivatives are introduced in the Chicago Mercantile Exchange, firms with exposure to the commodities experience up to a 40% drop in the variance of stock returns. The effect is persistent over time and it is associated with real effects: firms that hedge more also experience an increase in profit margins, investment, access to credit lines, and a drop in cash holdings. Our results establish a direct link between corporate risk management policies and stock return behaviour.

In this work an indoor position estimation algorithm will be proposed. The position will be measured by means of a sensor network composed by fixed beacons placed on the indoor environment and a mobile beacon mounted on the object to be tracked. The mobile beacon communicates with all the fixed beacons by means of ultra wide-band signals, and the distance between them is computed by means of time of flight techniques. Moreover, inertial measurements will be used when the position measurements are not available. Two main problems will be considered in the proposed architecture: the fact that the beacons work with a lower update rate than the IMU, and that the mobile beacon can comunicate with only one fixed beacon at a time. Experimental results will be shown in order to validate the effectiveness of the proposed technique.

We describe and test a mechanism through which outstanding bank loans affect the firm balance sheet channel of monetary policy transmission. Unlike other debt, most bank loans have floating rates mechanically tied to monetary policy rates. Hence, monetary policy-induced changes to floating rates affect the liquidity, balance sheet strength, and investment of financially constrained firms that use bank debt. We show that firms---especially financially constrained firms---with more unhedged bank debt display stronger sensitivity of their stock price, cash holdings, sales, inventory, and fixed capital investment to monetary policy. This effect disappears when policy rates are at the zero lower bound, which further supports the floating rate mechanism and reveals a new limitation of unconventional monetary policy. We argue that the floating rate channel can have a significant macroeconomic effect due to the large size of the aggregate stock of unhedged floating-rate business debt, an effect at least as important as the bank lending channel through new loans.

We revisit the relation between equity returns and financial leverage through the lens of a tradeoff model with adjustment costs of debt. The model provides a “look-alike” Modigliani-Miller equation according to which equity returns increase with relative leverage, which is defined as the difference between observed leverage and target leverage. The model shows that the traditional positive and linear relation between leverage and returns breaks down in the presence of adjustment costs. We provide empirical evidence that relative leverage is a reliable predictor of equity returns, while leverage is not.

This paper, starting from recent papers in the scientific literature dealing with Rotating Induction Motor (RIM) dynamic modelling, as a first step, improves its space-vector dynamic model, including both the magnetic saturation and iron losses; The main original aspects of the proposed model are the following: 1) the magnetic saturation of the iron core has been described on the basis of both current versus flux and flux versus current functions, 3) it includes the iron losses, separating them in hysteresis and eddy current ones, 4) it includes the effect of the load on the magnetic saturation. Afterwards, it proposes an off-line technique for the estimation of electrical parameters of this model, which is based on Genetic Algorithms (GA). The proposed method is based on input-output measurements and needs neither the machine design geometrical data nor a Finite Element Analysis (FEA) of the machine. It focuses on the application of an algorithm based on the minimization of a suitable cost function depending on the stator current error. The proposed electrical parameters estimation method has been initially tested in numerical simulation and further verified experimentally on a suitably developed test set-up.

We provide a new perspective on bank-dependency - the (bank) "liquidity insurance channel" - based on the predominance of large, high credit quality firms among credit line users. Our model can match the pattern of bank dependency in the cross-section of firms, and predicts when shocks to bank health will affect primarily low or high credit quality firms. Our framework can also explain why credit line origination is more cyclical than loan origination. Overall, we uncover an important link between bank health and economic activity through the provision and effectiveness of bank credit lines to large, high credit quality firms.

This paper deals with a robust input-output feedback linearization control technique for induction motors. Indeed, classic feedback linearization presents two main disadvantages: 1) the accuracy of the dynamic model; and 2) the corresponding correct knowledge of the model parameters. To address this issue, the linear controller has been substituted with a suitably controller designed to be robust to the variations of the main parameters of the induction motor, like stator and rotor resistances, and the three-phase magnetizing inductance. The proposed controller has been tested both in numerical simulation and experimentally on a suitably designed test setup. Moreover, it has been compared with the classical feedback linearization based on linear controllers, highlighting the improvements in terms of dynamic performance, when parameter variations occur. Results confirm a significant increase of the robustness of the controller against parameter variations.

We reconcile two seemingly contrasting empirical facts, active capital structure rebalancing and slow adjustments towards target leverage, through the lens of a standard dynamic capital structure model. In the model, firms adjust leverage towards a dynamic target, which is firm specific and responds to changes in firms' characteristics and investment opportunities. Capital market imperfections make leverage more stable than target leverage, generating slow adjustments despite active capital structure rebalancing. We quantify the extent of convergence towards dynamic targets by means of structural estimation. Although neither leverage ratios nor leverage targets are moving fast|making it a race between a tortoise and a snail - we find that leverage targets are roughly twenty to forty percent more volatile than leverage ratios over horizons ranging from five to thirty years. Adjustment speeds exhibit significant heterogeneity across firms and time. Standard reduced-form partial adjustment models neglect this property and, as a consequence, largely underestimate average speeds of adjustment.

Using Augmented Reality (AR) could offer stimuli to rehabilitation from neuro-motor disorders, since the patient can be aided in a better known reality than Virtual Reality (VR). The main goal for an AR system is to achieve a good quality of tracking the real object to align with virtual contents. Often a single sensor could not provide enough information to that end due to a low updating rate; therefore joining an other high updating rate sensor could be indispensable, but how to combine data from different sensors especially when they work all at different rates? In this paper an approach based on recursive parameter estimation, focusing on multi-rate tracking in AR devices is suggested. The system of this study has a multi-sensor configuration provided by a webcam and a 3-Axis MEMS inertial sensor, both working at different sample rates. Also an augmented reality application, designed for the neuro-motor rehabilitation of the upper limb, has been developed and shown.

The visual tracking of an object is a well-known problem, and it involves many fields of applications. Often a single sensor, the camera, could not provide enough information in order to track the whole object trajectory due to a low updating rate; therefore a multi-sensor system, based also on inertial measurements, could be necessary to improve the tracking accuracy. This leads to the fundamental question: how can information from different sensors be combined when they work at different rates? In this paper an approach based on recursive parameter estimation focusing on multi-rate situations is suggested. The problem is here formulated as the state-of-the-art problem of the visual tracking of an object in augmented reality environments. The multi-sensor system consists of a webcam and a 3-axis MEMS inertial sensor both with different sample rates. The augmented reality application has been designed for the object detection problem, and it has been tested experimentally in a suitably developed test set-up.

We examine the relation between the financial health of banks and their willingness to supply capital to borrowers under previously committed credit lines. We show that during the collapse of the Asset Backed Commercial Paper market in the last quarter of 2007 and the first half of 2008, banks with higher exposure to conduits renegotiated significantly tougher conditions on the outstanding credit lines offered to borrowers in violation of a covenant. Looking at the broader period of the financial crisis (2007-2010), we find that a worsening in financial health at banks led to a lower probability of waivers, following a covenant violation on a credit line. Our paper suggests that a worsening in financial conditions of lenders can bear financial implications for firms that use credit lines as an instrument of liquidity management.

By providing liquidity to depositors and credit-line borrowers, banks can be exposed to double-runs on assets and liabilities. For identification, we exploit the 2007 freeze of the European interbank market and the Italian Credit Register. After the shock, there are sizeable, aggregate double-runs. In the cross-section, credit-line drawdowns are not larger for banks more exposed to the interbank market; however, they are larger when we condition on the same firms with multiple credit lines. We show that, ex-ante, more exposed banks actively manage their liquidity risk by granting fewer credit lines to firms that run more during crises. Peydró acknowledges financial support from Project ECO2012-32434 of the Spanish Ministry of Economics and Competitiveness and the European Research Council Grant (Project 648398).