0000000000596861
AUTHOR
Maurizio Cirrincione
Impedance estimation of FEA's grid in fiji islands by V-I measurement by using the synchronous reference frame-PLL
In recent years there has been a significant increase in distributed renewable energy generation feeding into the grid, with resulting detriment of the stability of the network, since present networks have not been designed for this purpose. To feed-in these renewable energy sources with minimum impact, it is essential to know a few grid parameters (voltage, current, grid impedance) at the point in which power supply is convenient. For this purpose in this paper an algorithm is proposed to obtain the estimated network impedance. This algorithm operates in time domain by a synchronous reference coordinate transformation, it requires only the measurement of the phase voltage with no-load and …
Parameter identification of linear induction motor model in extended range of operation by means of input-output data
This paper proposes a technique for the off-line estimation of the electrical parameters of the equivalent circuit of linear induction machines (LIM), taking into consideration the end effects, and focuses on the application of an algorithm based on the minimization of a suitable cost function involving the differences of measured and computed by simulation inductor current components. This method exploits an entire start-up transient of the LIM to estimate all the 4 electrical parameters of the machine (Rs, L s, σ Ls, Tr). It proposes also a set of tests to be made to estimate the variation of the magnetic parameters of the LIM versus the magnetizing current as well as the magnetizing curv…
Neural based MRAS sensorless techniques for high performance linear induction motor drives.
This paper proposes a neural based MRAS (Model reference Adaptive System) speed observer suited for linear induction motors (LIM). Starting from the dynamical equation of the LIM in the synchronous reference frame in literature, the so-called voltage and current models of the LIM in the stationary reference frame, taking into consideration the end effects, have been deduced. Then, while the inductor equations have been used as reference model of the MRAS observer, the induced part equations have been discretized and rearranged so to be represented by a linear neural network (ADALINE). On this basis, the so called TLS EXIN neuron has been used to compute on-line, in recursive form, the machi…
Supercapacitor diagnosis using an Extended Kalman Filtering approach
This paper deals with the model-based analysis of a Supercapacitor for diagnostic purposes. A two legs nonlinear physical model is assumed for the Supercapacitor and the corresponding second-order nonlinear state-space mathematical model is obtained. Then, an Extended Kalman Filter is tuned so that the estimated outputs reproduce the voltages at the equivalent capacitance terminals; they give information on the state of health of the supercapacitor but are not directly measurable. In particular, an optimization problem is firstly formulated, involving the experimental input-output data and those given by the Extended Kalman Filter.
A Novel Neural Approach to the Determination of the Distribution Function in Magnetic Preisach Systems
This paper presents a novel method to identify both the functional dependence of the Preisach function as well as its numerical parameters on the basis of some known magnetic behavior. In this paper, the identification of the Preisach function of a material is performed by using a neural network trained by a collection of hysteresis curves, whose Preisach functions are known. When a new hysteresis curve is given as input to this neural network, it is able to give as output both the functional dependence of the Preisach function as well as its numerical parameters.
Improving the speed estimation by load torque estimation in induction motor drives: an MRAS and NUIO approach
This paper proposes the application of the NUIO inside a FOC induction motor drive for the simultaneous estimation of the load torque and the rotor speed. The idea is to estimate at first the speed with the current model in parallel with a reference model developed on the basis of the voltage model of the induction machine. Then, the estimated speed is given as input to a nonlinear unknown input observer (NUIO) to estimate the load torque. This estimation is then used to correct the previous estimation of the speed. Simulation and experimental results confirm the goodness of the method for an extended range of speed and different load torque, and they confirm the reduction of error in trans…
Robust control for high performance induction motor drives based on partial state-feedback linearization
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 w…
A Saturation Model of the Synchronous Reluctance Motor and its Identification by Genetic Algorithms
This paper proposes a complete saturation model of the Synchronous Reluctance Motor (Syn1231), accounting for both the self-saturation and cross-saturation effects. This model is based on an analytical relationship between the stator flux and current components, and is characterized by parameters presenting an interesting physical interpretation, differently from many other saturation model in the scientific literature. It proposes also an identification technique of such a model based on stand-still tests, without the need of locking the rotor. The proposed saturation model permits the complete description of the magnetic behaviour of the machine with 8 parameters, fewer than those require…
GA-based Off-Line Parameter Estimation of the Induction Motor Model Including Magnetic Saturation and Iron Losses
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 thi…
Adaptive Feed-Forward Neural Network for Wind Power Delivery
This paper describes a grid connected wind energy conversion system. The interconnecting filter is a simple inductor with a series resistor to minimize three-phase current Total Harmonic Distortion (THD). Using the Recursive Least Squares (RLS) Estimator, an online grid impedance technique is proposed in the stationary reference frame using the Recursive Least Squares (RLS) Estimator. An Adaptive Feedforward Neural (AFN) Controller has also been developed using the inverse of the system to improve the performance of the current Proportional-Integral controller under dynamical conditions and provide better DC link voltage stability. The neural network weights are computed in real-time using …
Online Estimation of the Mechanical Parameters of an Induction Machine Using Speed Loop characteristics and Recursive Least Square Technique
This paper presents a novel approach for estimation of mechanical parameters, inertia and friction coefficient of an Induction Machine (IM) using speed loop characteristics and Recursive Least Square (RLS) estimator. Using the 5th order dynamic equation for Induction Machine and the forgetting factor based RLS algorithm the technique herein proposed employs the speed of the machine and the torque as the inputs for the estimator. Results obtained compares the estimated parameters with the actual parameters under multiple step varying and exponentially varying scenarios. Upon analyzing the results, the validity and the effectiveness of the proposed identification technique is confirmed
Space-vector State Dynamic Model of the Synchronous Reluctance Motor Considering Self, Cross-Saturation and Iron Losses
This paper proposes a space-vector dynamic model of the Synchronous Reluctance Motor (SynRM) including both self-saturation, cross-saturation effects, and iron losses expressed in state form, where the magnetizing current has been selected as a state variable. The proposed dynamic model is based on an original function between the stator flux and the magnetizing current components, improving a previously developed magnetic model. Additionally, the proposed model includes, besides the magnetic saturation, also iron losses. The proposed model requires 11 coefficients, among which 6 describe the self-saturation on both axes and 5 describe the cross-saturation. Starting from the definition of a…
Descriptor-type Kalman Filter and TLS EXIN Speed Estimate for Sensorless Control of a Linear Induction Motor.
This paper proposes a speed observer for linear induction motors (LIMs), which is composed of two parts: 1) a linear Kalman filter (KF) for the online estimation of the inductor currents and induced part flux linkage components; and 2) a speed estimator based on the total least squares (TLS) EXIN neuron. The TLS estimator receives as inputs the state variables, estimated by the KF, and provides as output the LIM linear speed, which is fed back to the KF and the control system. The KF is based on the classic space-vector model of the rotating induction machine. The end effects of the LIMs have been considered an uncertainty treated by the KF. The TLS EXIN neuron has been used to compute, in …
Intelligent Energy Management System
Energy management is nowadays a subject of great importance and complexity. It consists in choosing among a set of sources able to produce energy that will give energy to a set of loads by minimising losses and costs. The sources and loads are heterogeneous, distributed and the reaction of the system, the choice of sources, must be done in real-time to avoid power outage. The goal of this paper is to present a system able to self-regulate a heterogeneous set of power sources and loads organised as a coherent group of entities that is called micro-grid, in order to optimize several criteria such as: cost and efficiency. This system is based upon the Multi-Agent Systems paradigm. Each micro-g…
Development of a Fractional PI controller in an FPGA environment for a Robust High-Performance PMSM Electrical Drive
This paper proposes the application of a Fractional Order PI (FOPI) in the speed loop of a high performance PMSM drive to obtain both speed tracking and load rejection performance with a 1-DOF Proportional Integral (PI) controller and 2-DOF Integral Proportional (IP) controller. Hardware validation was implemented in Field Programmable Gate Array on the LabVIEW environment, based on the National Instruments System-on-Module sbRIO-9651 with Xilinx Zynq-7020. Simulation and experimental results are presented to comparing the performance of a PI, IP and FOPI controllers in the speed loop of a Field Oriented Control (FOC) of a Permanent Magnet Synchronous Motor (PMSM).
Sea wave energy to supply the Aeolian Islands in sustainable way
The diffusion of technologies supplied by Renewable Energy Sources is contributing in the challenge of reduction of energy dependence from fossil fuels, avoiding the emission of several polluting substances and greenhouse gases. Despite the technological development and important results around the world, in several remote areas or small islands the electrical energy production is based on obsolete technologies, supplied by fossil fuels. This solution is not sustainable for the environment, as the emissions of several pollutants. Focusing the attention on small islands, these areas usually have a standalone grid, as the high cost to build an electrical connection to the mainland, in compari…
A Nonlinear Control of Synchronous Reluctance Motors (SynRM) Based on Feedback Linearization Considering the Self and Cross-Saturation Effects
This paper proposes a nonlinear controller based on feedback linearization for Synchronous Reluctance Motors (SynRM) drives that takes into consideration the self and cross-saturation effects. Such control technique permits the dynamics of both the speed and flux loops to be maintained constant independently from the load and the saturation of the iron core. The proposed technique has been tested experimentally on a suitably developed test set-up.
Space‐vector state dynamic model of SynRM considering self‐ and cross‐saturation and related parameter identification
This study proposes a state formulation of the space-vector dynamic model of the Synchronous Reluctance Motor (SynRM) considering both saturation and cross-saturation effects. The proposed model adopts the stator currents as state variables and has been theoretically developed in both the rotor and stator reference frames. The proposed magnetic model is based on a flux versus current approach and relies on the knowledge of 11 parameters. Starting from the definition of a suitable co-energy variation function, new flux versus current functions have been initially developed, based on the hyperbolic functions and, consequently, the static and dynamic inductance versus current functions have be…
Parameter identification of induction motor model by means of State Space-Vector Model Output Error Minimization
This paper proposes a technique for the off-line estimation of the electrical parameters of the equivalent circuit of an Induction Machines (IM), and focuses on the application of an algorithm based on the minimization of a suitable cost function involving the differences between the measured stator current direct (sD) and quadrature (sQ) components and the corresponding estimated by the IM state model. This method exploits an entire start-up transient of the IM to estimate all of the 4 electrical parameters of the machine (Rs, Ls, σLs, Tr). It proposes also a set of tests to be made in order to estimate the variation of the magnetic parameters of the IM versus the rotor magnetizing current…
A nonlinear observer for rotor flux estimation considering magnetic saturation effects in induction motor drives
This paper proposes a non-linear observer for In- duction Machine (IM) drives which takes into consideration the saturation effects. The non-linear observer is based on an original formulation of the dynamic model of the IM taking into consideration the magnetic saturation of the iron core. A Lyapunov based convergence analysis is proposed in order to suitably compute the observer gain guaranteeing the stability of the observer. The proposed non-linear observer has been tested in numerical simulation and experimentally on a suitably developed test set-up. Its behaviour has been compared to that obtained with a classic Full-Order Luenberger Observer (FOLO) in variable flux working conditions…
Sensorless Control of PMSM Fractional Horsepower Drives by Signal Injection and Neural Adaptive-Band Filtering
This paper presents a sensorless technique for permanent-magnet synchronous motors (PMSMs) based on high-frequency pulsating voltage injection. Starting from a speed estimation scheme well known in the literature, this paper proposes the adoption of a neural network (NN) based adaptive variable-band filter instead of a fixed-bandwidth filter, needed for catching the speed information from the sidebands of the stator current. The proposed NN filter is based on a linear NN adaptive linear neuron (ADALINE), trained with a classic least mean squares (LMS) algorithm, and is twice adaptive. From one side, it is adaptive in the sense that its weights are adapted online recursively. From another si…
Robust motion control of nonlinear quadrotor model with wind disturbance observer
This paper focuses on robust wind disturbance rejection for nonlinear quadrotor models. By leveraging on nonlinear unknown observer theory, it proposes a nonlinear dynamic filter that, using sensors already on-board the aircraft, can estimate in real-time wind gust signals in the three dimensions. The wind disturbance is then treated as input to the PD controller for a quick and robust flight pathway in presence of disturbances. With this scheme, the wind disturbance can be precisely estimated online and compensated in real-time. Hence, the quadrotor can successfully reach its desired attitude and position. To show the effective and desired performance of the method, simulation results are …
Hybrid Propulsion Efficiency Increment through Exhaust Energy Recovery—Part 1: Radial Turbine Modelling and Design
The efficiency of Hybrid Electric Vehicles (HEVs) may be substantially increased if the energy of the exhaust gases, which do not complete the expansion inside the cylinder of the internal combustion engine, is efficiently recovered by means of a properly designed turbogenerator and employed for vehicle propulsion; previous studies, carried out by the same authors of this work, showed a potential hybrid vehicle fuel efficiency increment up to 15% by employing a 20 kW turbine on a 100 HP rated power thermal unit. The innovative thermal unit here proposed is composed of a supercharged engine endowed with a properly designed turbogenerator, which comprises two fundamental elements: an exhaust …
Adaptive feedback linearizing control of linear induction motor considering the end-effects
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 …
PEM Fuel Cell System Model Predictive Control and real-time operation on a power emulator
Fuel Cell Systems (FCS) seem to be among the most reliable devices to produce clean energy, although they still suffer for many problems, mostly related to the fragility of the Polymer Electrolyte Membrane (PEM). Particularly, this paper focuses on the oxygen starvation, that leads both a decrease of the FCS performance and a shortening in the FCS lifetime. The purpose is to use the Model Predictive Control (MPC) and its capacity of accounting for linear constraints for managing the air system without risking to damage the fuel cell. Two control inputs and no static feed-forward actions have been used. Results show that the MPC is able to avoid the oxygen starvation, even with a sudden incr…
Enhanced Current Loop PI Controllers with Adaptive Feed-Forward Neural Network via Estimation of Grid Impedance: Application to Three-Phase Grid-Tied PV Inverters
This paper describes a single-stage grid-connected three-phase photovoltaic inverter feeding power to the grid. Using the Recursive Least Squares (RLS) Estimator, an online grid impedance technique is proposed in the stationary reference frame. The method iteratively estimates the grid resistance and inductance values and is effective in detecting inverter islanding according to IEEE standard 929-2000. An Adaptive Feedforward Neural (AFN) Controller has also been developed using the inverse of the system to improve the performance of the inner-loop Proportional-Integral controllers under dynamical conditions and provide better DC link voltage stability. The neural network weights are comput…
Input-Output Feedback Linearizing Control of Linear Induction Motor Taking into Consideration the End-Effects. Part II: Simulation and Experimental Results
This is the second part of a paper, divided in two parts, dealing with the application of the input–output feedback linearization (FL) control technique to linear induction motors (LIMs). The first part has treated the theoretical formulation of the input–output feedback linearization control technique as to be applied to linear induction motors. This second part describes the set of tests, both in numerical simulations and experiments, performed to assess the validity of the control technique. In particular, it addresses the issues of the sensitivity of the FL control versus the LIM electrical parameters’ variations and the improvements achievable by considering the LIM dynamic end effects…
Greening and sustainable energy approach applied for Balearic Islands and Fiji Islands: a comparative study
Renewable energy sources are expanding around the world, with significative results in the electricity generation sector. Despite this, the share of renewable energy sources in small islands is very low, except in rare cases. In this context, the paper analyses the energy mix currently used to produce electricity in the Balearic Islands and the Fiji Islands. These two archipelagos show several differences but have in common the strong energy dependence from fossil fuels. In order to increase the energy sustainability of small islands, a preliminary energy assessment is realized, using climate data collected from GIS-tools and introducing a numerical approach. As target, the Authors consider…
A Preliminary Energy Assessment to Improve the Energy Sustainability in the Small Islands of the Mediterranean Sea
Power plants supplied by renewable energy sources are expanding around the world, in order to reduce the carbon dioxide emissions, limit the global warming and improve the energy sustainability. Despite the relevant achieved results, small islands are heavily reliant on fossil fuels. In this context, renewable energy sources are available but practically unused, due to landscape and economic constraints. This condition is quite common in the Mediterranean Sea. These islands are normally fed by a stand-alone electrical grid and a power plant, equipped with diesel engines. In order to improve the sustainability of the energy sector, the paper considers the case study of Ustica, a small Italia…
Dynamical Compensation of the Load Torque in a High-Performance Electrical Drive with an Induction Motor
This paper describes a new method for dynamical estimation of load disturbance in induction motors by using Nonlinear Unknown Input Observers (NUIO). This estimation is then used to compensate dynamically the load torque in a Field Oriented Control (FOC) induction motor drive to increase its load-rejection capability. The method has been verified both in simulation and experimentally on a experimental rig.
Feedback Linearization Based Nonlinear Control of SynRM Drives Accounting for Self- and Cross-Saturation
This article proposes a nonlinear controller based on feedback linearization (FL) for synchronous reluctance motor (SynRM) drives which takes into consideration the magnetic saturation. The proposed nonlinear FL control based control technique has been developed starting from the theoretical definition of an original dynamic model of the SynRM taking into consideration both the self- and the cross-saturation effects. Such a control technique permits the dynamics of both the speed and axis flux loops to be maintained constant independently from the load and the saturation of the iron core in both constant flux and variable direct axis flux operating conditions. Finally, sensitivity of the pe…
Wind gust estimation for precise quasi-hovering control of quadrotor aircraft
Abstract This paper focuses on the control of quadrotor vehicles without wind sensors that are required to accurately track low-speed trajectories in the presence of moderate yet unknown wind gusts. By modeling the wind disturbance as exogenous inputs, and assuming that compensation of its effects can be achieved through quasi-static vehicle motions, this paper proposes an innovative estimation and control scheme comprising a linear dynamic filter for the estimation of such unknown inputs and requiring only position and attitude information. The filter is built upon results from Unknown Input Observer theory and allows estimation of wind and vehicle state without measurement of the wind its…
A Model Modulated Predictive Current Control Algorithm for the Synchronous Reluctance Motor
This paper proposes a Model Modulated Predictive Control (M2PC) specifically developed for Synchronous Reluctance Motors (SynRM) drives and based on a purposely developed magnetic model taking into account both self- and cross-saturation. The proposed M2PC exploits the discrete-time version of the dynamic model to compute the current prediction and the resulting predicted current error. The built-in PWM modulator chooses the optimal pair of voltage space-vector to be applied by the inverter to minimize the current error. The magnetic model permits obtaining good dynamic performance in every working condition.
Neural Sensorless Control of Linear Induction Motors by a Full-Order Luenberger Observer Considering the End Effects
This paper proposes a neural based full-order Luenberger adaptive speed observer for sensorless linear induction motor (LIM) drives, where the linear speed is estimated with the total least squares (TLS) EXIN neuron. A novel state space-vector representation of the LIM has been deduced, taking into consideration its dynamic end effects. The state equations of the LIM have been rearranged into a matrix form to be solved, in terms of the LIM linear speed, by any least squares technique. The TLS EXIN neuron has been used to compute online, in recursive form, the machine linear speed. A new gain matrix choice of the Luenberger observer, specifically taking into consideration the LIM dynamic end…
Feedback Linearizing Control of Induction Motor Considering Magnetic Saturation Effects
This paper presents an input-output feedback linearization (FL) control technique for rotating induction motors, which takes into consideration the magnetic saturation of the iron core. Starting from a new formulation of the dynamic model taking into consideration the magnetic saturation expressed in a space-state form in the rotor-flux-oriented reference frame, the corresponding FL technique has been developed. To this aim, a particular care has been given to the choice of nonlinear functions interpolating the magnetic parameters versus the rotor magnetizing current and the corresponding magnetic characteristic. The proposed FL technique has been tested experimentally on a suitably develop…
Space-vector State Dynamic Model of the SynRM Considering Self, Cross-Saturation and Iron Losses and Related Identification Technique
This article proposes a space-vector dynamic model of the Synchronous Reluctance Motor (SynRM) including both self-saturation, cross-saturation effects, and iron losses. The model is expressed in state form, where the magnetizing current has been selected as a state variable. The proposed dynamic model is based on an original function describing the relationship between the stator flux and the magnetizing current components, improving a previously developed magnetic model. Additionally, the proposed model includes, besides the magnetic saturation, also iron losses. The proposed model requires 11 coefficients, among which 6 describe the self-saturation on both axes and 5 describe the cross-s…
Sensorless induction machine drive for fly-wheel generation unit based on a TLS-based non-linear observer
This paper proposes a sensorless technique for an induction machine Flywheel Energy Storage System (FESS) based on a non-linear observer integrated with a total least-squares speed estimator taking into consideration the IM (Induction Machine) saturation effects. The nonlinear observer is based on an original formulation of the dynamic model of the IM including the magnetic saturation, rearranged in a space-state form, after assuming as state variables the stator current and the rotor magnetizing current space-vectors in the stator reference frame. The choice of the observer gain has been made by the use of Lyapunov's method. The speed signal needed by the non-linear observer for the flux e…
Input-Output Feedback Linearization Control of Linear Induction Motors Including the dynamic End-Effects
This paper proposes the theoretical framework and the consequent application of the input-output feedback linearization (FL) control technique to linear induction motors (LIM). LIM, additionally to RIM, presents other strong non-linearities caused by the dynamic end effects, leading to a space-vector dynamic model with time-varying inductance and resistance terms and a braking force term. This paper, starting from a recently developed dynamic model of the LIM taking into consideration its end effects, defines a FL technique suited for LIMs, since it inherently considers its dynamic end effects. The proposed approach has been validated experimentally on a suitably developed test set-up. Furt…
Input-Output Feedback Linearization Control with On-Line Inductances Estimation of Synchronous Reluctance Motors
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 guaran…
Enhancing Speed Loop PI Controllers with Adaptive Feed-forward Neural Networks: Application to Induction Motor Drives
This paper proposes the idea to improve the performance of the speed loop PI controller by using feed-forward and adaptive control actions. Indeed, when the system to be controlled is required to track a rapidly changing reference frame, higher bandwidth is usually required, making the system more sensitive to noise and consequently less robust. In such cases, to achieve a better performance in reference tracking while keeping noise rejection capacity, one idea is to use a feed-forward controller, employed to enhance the required tracking, leaving the feedback action to stabilize the system and suppress higher frequency disturbance. As such, this paper analysis the classical PI based field …
Vector Projection-based Sensorless Control of a SynRM Drive Including Self and Cross-Saturation
This paper presents a sensorless technique for SynRM drives that is based on a vector projection method and takes into consideration the magnetic saturation of the motor, both the self and the cross-saturation. The proposed method is based on the dynamic equation of the SynRM including saturation, rewritten in integral form, and does not involve any high-frequency carrier injection. The technique has been tested in numerical simulation and experimentally on a suitably developed test set-up. Experimental results show a correct behavior of the sensorless SynRM drive, properly accomplishing speed transients in a wide speed range, including low speed, still maintaining a good accuracy in the sp…
MRAS speed observer for high performance linear induction motor drives based on linear neural networks
This paper proposes a Neural Network (NN) MRAS (Model Reference Adaptive System) speed observer suited for linear induction motor (LIM) drives. The voltage and current models of the LIM in the stationary reference frame, taking into consideration the end effects, have been obtained. Then, equations of the induced part have been discretized and rearranged so as to be represented by a linear neural network the TLS EXIN neuron, which has been used to compute the machine linear speed on-line and in recursive form. The proposed NN MRAS observer has been tested experimentally on a suitably developed test setup. Its performance has been also compared to the classic MRAS speed observer.
Erle-copter Simulation using ROS and Gazebo
The recent decrease in the price as well as size of semi-conductor logic and due to significant advancements in technologies such as microcontrollers, motors and sensors, the application of quadcopters in several fields has been achieved. However, testing of quadcopter prototypes still has a risk of damage due to faults and unexpected behavior. Hence, a method of testing of quadcopters in simulation mimicking the actual conditions of the real environment in an actual hardware test has been proposed. For this purpose, Gazebo simulator integrated with ROS has been chosen for the simulation of the path of the quadcopter. Moreover, the software Matlab/Simulink has been interfaced with Gazebo in…
Input-Output Feedback Linearization Control with On-line MRAS Based Inductor Resistance Estimation of Linear Induction Motors Including the Dynamic End-Effects
This paper proposes the theoretical framework and the consequent application of the input–output feedback linearization (FL) control technique to linear induction motors (LIMs). LIM, additionally to rotating induction motor, presents other strong nonlinearities caused by the dynamic end effects, leading to a space-vector dynamic model with time-varying inductance and resistance terms and a braking force term. This paper, starting from a recently developed dynamic model of the LIM taking into consideration its end effects, defines a FL technique suited for LIMs, since it inherently considers its dynamic end effects. Additionally, it proposes a technique for the on-line estimation of the indu…
A renewable energy mix to supply small islands. A comparative study applied to Balearic Islands and Fiji
Abstract Power plants supplied by renewables are expanding around the world, increasing the sustainability of the energy sector. In this context, small islands are heavily reliant on fossil fuels. However, this paper shows that the same problem can be found also in small islands belonging to developed countries. To increase the energy sustainability of small islands, the authors assembled a simplified mathematical approach to evaluate the potential electricity production, exploiting the local available energy sources: solar, wind and sea wave. The mathematical model requires few information in input, such as climatic data about the local energy sources and technical features on the selected…
Active Disturbance Rejection Control of Synchronous Reluctance Motors
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.
Improvement of a low-cost buoy for the measurement of the sea wave weather
This article presents the result of an experimental meteorological buoy designed by the Department of Engineering of the University of Palermo, characterized by low costs and great versatility, and equipped with industrially certified measuring and detection instruments. This buoy can measure the parameters of the water column and continuously transmit the data to a remote acquisition centre. Maintenance requirements are very limited.
Adaptive Feedback Linearization Control of SynRM Drives With On-Line Inductance Estimation
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 thank…
Sensorless control of PMSM by a linear neural network: TLS EXIN neuron
Sensorless vector control applied to the Permanent Magnet Synchronous Motors (PMSMs) is a very challenging subject. It permits obtaining high dinamical performance by exploiting increased reliability and also reduced cost. Among the different methodologies proposed in literature, a model based approach has been proposed here. In particular, the space vector equations of the PMSM have been re-elaborated to permit the use of a Least Squares technique. The problem has been then faced-up to with the so-called TLS EXIN neuron, which is a linear neural network able to solve the TLS problem on-line. Simulation tests have been done on both interior mounted and surface mounted machines.
Input-Output Feedback Linearization Control of a Linear Induction Motor Taking Into Consideration Its Dynamic End-Effects and Iron Losses
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 FL…
An Economic Approach to Size of a Renewable Energy Mix in Small Islands
The importance of renewable energy exploitation reduces the energy dependence on fossil fuels. Despite technological progress, in several remote areas and small islands the energy production is nowadays dominated by the utilization of fossil fuels. With new, increasingly stringent laws on polluting emissions and the need to lower production costs, it is necessary to exploit as many renewable sources as possible. In order to implement these considerations, it was decided to study renewable energy production. The study was carried out by estimating the energy production on a monthly and annual basis considering a mix of three plants, namely marine, solar, and wind. Simulations on wave product…
Robust Active Disturbance Rejection Control of Induction Motor Systems Based on Additional Sliding-Mode Component
This paper deals with motion control systems with induction motor, subject to severe requirements on both dynamics and steady-state behavior. The proposed control methodology could be viewed as an advancement of the standard field oriented control. It consists of two control loops, i.e., the rotor flux and the speed control loops, designed using the active disturbance rejection control method, with the aim to cope with both exogenous and endogenous disturbances, which are estimated by means of two linear extended state observers and then compensated. Moreover, with the aim of achieving total robustness, a sliding-mode based component is designed, in order to take into account disturbance es…
A Space-Vector State Dynamic Model of the Synchronous Reluctance Motor Including Self and Cross-Saturation Effects and its Parameters Estimation
This paper proposes a space-vector dynamic model of the Synchronous Reluctance Motor (SynRM) including both self-saturation and cross-saturation effects and selecting as state variables the stator currents. The proposed dynamic model is based on an original function between the stator flux and stator current components, and relies on 8 coefficients (fewer than other models in the scientific literature), presenting an interesting physical interpretation. Starting from this approach, both the static and dynamic inductances expressions of the model have been analytically developed, so that the reciprocity conditions for the cross saturation is satisfied. This paper presents also a technique fo…
Hybrid Propulsion Efficiency Increment through Exhaust Energy Recovery—Part 2: Numerical Simulation Results
The efficiency of hybrid electric vehicles may be substantially increased if the energy of exhaust gases, which do not complete the expansion inside the cylinder of the internal combustion engine, is efficiently recovered using a properly designed turbo-generator and employed for vehicle propulsion. Previous studies, carried out by the same authors of this work, showed a potential hybrid vehicle fuel efficiency increment up to 15% employing a 20 kW turbine on a 100 HP-rated power thermal unit. The innovative thermal unit proposed here is composed of a supercharged engine endowed with a properly designed turbo-generator, which comprises two fundamental elements: an exhaust gas turbine expres…
Input-output feedback linearizing control of linear induction motor taking into consideration the end-effects. Part I: Theoretical analysis
Abstract This first part of a paper, divided into two parts, deals with the theoretical formulation of the input–output feedback linearization (FL) control technique as to be applied to linear induction motors (LIMs). Linear induction motors, differently from rotating induction motors (RIMs), present other strong non-linearities caused by the so-called dynamic end effects, leading to a space-vector model with time-varying inductance and resistance terms and an additional braking force term. This paper, starting from a dynamic model of the LIM taking into consideration its dynamic end effects, previously developed by the same authors, defines a feedback linearization (FL) technique suited fo…
PMSM Drives Sensorless Position Control with Signal Injection and Neural Filtering
Vector Field Oriented Control (FOC) is one of the best control methods for high-dynamic electrical drives. To avoid the adoption of the speed/position sensor (resolver/encoder), a sensorless technique should be used. Among the various sensorless methods in literature, those based on machine saliency detection by signal injection seem to be most useful for thier giving the possibility of closing the position control loop. This paper proposes a method for enhancing both rotating and pulsating voltage carrier injection methods by a neural adaptive band filter. Results show the goodness of the proposed solution.