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Jorge Rodas was born in Asuncion, Paraguay in 1984. He received his B.Eng. degree in Electronic Engineering from the Universidad Nacional de Asuncion, Paraguay, in 2009. He received his M.Sc. degrees from the Universidad de Vigo, Spain, in 2012 and from the Universidad de Sevilla, Spain, in 2013, and his joint-university Ph.D. degree between the Universidad Nacional de Asuncion and the Universidad de Sevilla in 2016. In 2011, he joined the Laboratory of Power and Control Systems, Faculty of Engineering, Universidad Nacional de Asuncion, where he currently serves as Professor. In 2017 he joined the Power Electronics and Industrial Control Research Group of École de Technologie Supérieure (Montreal, Canada), under the supervision of Prof. Maarouf Saad, for a research stay. He serves as an Associate Editor of Alexandria Engineering Journal (AEJ) and Guest Editor in Energies and frontiers in Energy Research. His research interest focuses on applications of advanced control to real-world problems. Current research activities include the application of model predictive control and nonlinear control to power electronic converters, renewable energy conversion systems, electric motor drives, and robotic systems (especially unmanned aerial vehicles).
Multiphase machines have attracted the attention of the research and industrial communities due to their advantages, namely better power distribution and fault-tolerant capabilities without extra hardware. However, the multiphase machine requires high-performance control strategies to take advantage of these features. From this perspective, the field-oriented control with the inner current control loop that uses using an explicit modulation stage has been considered the benchmark solution thanks to the reduced harmonic distortion obtained with this regulation strategy. Nevertheless, nonlinear controllers, thanks to their inherent nature, allow exploiting the extra multiphase capabilities in a simplified manner. Consequently, this paper aims to concentrate and discuss the latest developments on nonlinear current control of two of the most popular multiphase electric drive configurations, five-phase and six-phase. Then, this paper covers mainly finite-control-set model predictive control and their variations. Moreover, sliding-mode control is also explained. Finally, this paper includes experimental assessments of the most recent nonlinear current control techniques considering steady-state and transient conditions, stability and performance analysis.
Jorge Rodas; Ignacio Gonzalez-Prieto; Yassine Kali; Maarouf Saad; Jesus Doval-Gandoy. Recent Advances in Model Predictive and Sliding Mode Current Control Techniques of Multiphase Induction Machines. Frontiers in Energy Research 2021, 9, 1 .
AMA StyleJorge Rodas, Ignacio Gonzalez-Prieto, Yassine Kali, Maarouf Saad, Jesus Doval-Gandoy. Recent Advances in Model Predictive and Sliding Mode Current Control Techniques of Multiphase Induction Machines. Frontiers in Energy Research. 2021; 9 ():1.
Chicago/Turabian StyleJorge Rodas; Ignacio Gonzalez-Prieto; Yassine Kali; Maarouf Saad; Jesus Doval-Gandoy. 2021. "Recent Advances in Model Predictive and Sliding Mode Current Control Techniques of Multiphase Induction Machines." Frontiers in Energy Research 9, no. : 1.
With the increased emphasis on climate change and reducing harmful emissions in the atmosphere, interest in power electronics converters and electric motor drives has led to significant new developments in areas such as renewable energy systems or electric propulsion
Federico Barrero; Jorge Rodas. Control of Power Electronics Converters and Electric Motor Drives. Energies 2021, 14, 4591 .
AMA StyleFederico Barrero, Jorge Rodas. Control of Power Electronics Converters and Electric Motor Drives. Energies. 2021; 14 (15):4591.
Chicago/Turabian StyleFederico Barrero; Jorge Rodas. 2021. "Control of Power Electronics Converters and Electric Motor Drives." Energies 14, no. 15: 4591.
Finite-set model predictive control (FS-MPC) as predictive current control (PCC) is considered an exciting option for the stator current control of multiphase machines due to their control flexibility and easy inclusion of constraints. The weighting factors (WFs) of PCC must be tuned for the variables of interest, such as the machine losses x - y currents, typically performed by trial and error procedure. Tuning methods based on artificial neural network (ANN) or the coefficient of variation were proposed for three-phase inverter and motor drive applications. However, the extension of this concept to the multiphase machine application is not straightforward, and only empirical procedures have been reported. In this context, this paper proposes an optimal method to tune the WF of the PCC based on the multi-objective particle swarm optimization (MOPSO) algorithm. A Pareto dominance concept is used for the MOPSO to find the optimal WF values for the PCC, comparing parameters of root-mean-square error of the stator tracking currents. The proposed method offers a systematic approach to the WF selection, with an algorithm of easy implementation with direct control over the size of the search space and the speed of convergence. Simulation and experimental results in steady-state and transient conditions are provided to validate the proposed offline tuning procedure of the PCC of a six-phase induction machine. The improvements of RMSE can be more than 500% for x - y subspace, with minor effect in α - β subspace. Finally, the proposed method is extended to a more complex cost function, and the results are compared with an ANN approach.
Hector Fretes; Jorge Rodas; Jesus Doval-Gandoy; Victor Gomez; Nicolas Gomez; Mateja Novak; Jose Rodriguez; Tomislav Dragicevic. Pareto Optimal Weighting Factor Design of Predictive Current Controller of a Six-Phase Induction Machine based on Particle Swarm Optimization Algorithm. IEEE Journal of Emerging and Selected Topics in Power Electronics 2021, PP, 1 -1.
AMA StyleHector Fretes, Jorge Rodas, Jesus Doval-Gandoy, Victor Gomez, Nicolas Gomez, Mateja Novak, Jose Rodriguez, Tomislav Dragicevic. Pareto Optimal Weighting Factor Design of Predictive Current Controller of a Six-Phase Induction Machine based on Particle Swarm Optimization Algorithm. IEEE Journal of Emerging and Selected Topics in Power Electronics. 2021; PP (99):1-1.
Chicago/Turabian StyleHector Fretes; Jorge Rodas; Jesus Doval-Gandoy; Victor Gomez; Nicolas Gomez; Mateja Novak; Jose Rodriguez; Tomislav Dragicevic. 2021. "Pareto Optimal Weighting Factor Design of Predictive Current Controller of a Six-Phase Induction Machine based on Particle Swarm Optimization Algorithm." IEEE Journal of Emerging and Selected Topics in Power Electronics PP, no. 99: 1-1.
The development of new control techniques for multiphase induction machines (IMs) has become a point of great interest to exploit the advantages of these machines compared to three-phase topology, for example, the reduced phase currents and lower harmonic contents. One of the most analyzed techniques is the model-based predictive current control (MPC) with a finite control set. This technique presents high x–y currents because of the application of one switching state throughout the whole sampling period. Nevertheless, it is one of the most used due to its excellent dynamic response. To overcome the aforementioned drawbacks, new techniques called virtual vectors have been developed, but although there are several articles with experimental results, the algorithm for implementing the technique has not been appropriately described. This document provides a clear and detailed explanation for algorithm implementation of virtual vectors through two proposed variants VV4 and VV11, in a six-phase machine drive. The first entails lower computational cost and the second lower loss in the x–y plane. According to performance indicators such as the total harmonic distortion and the mean square error for both case studies, experimental tests were evaluated to determine the implementation’s behaviour.
Carlos Romero; Larizza Delorme; Osvaldo Gonzalez; Magno Ayala; Jorge Rodas; Raul Gregor. Algorithm for Implementation of Optimal Vector Combinations in Model Predictive Current Control of Six-Phase Induction Machines. Energies 2021, 14, 3857 .
AMA StyleCarlos Romero, Larizza Delorme, Osvaldo Gonzalez, Magno Ayala, Jorge Rodas, Raul Gregor. Algorithm for Implementation of Optimal Vector Combinations in Model Predictive Current Control of Six-Phase Induction Machines. Energies. 2021; 14 (13):3857.
Chicago/Turabian StyleCarlos Romero; Larizza Delorme; Osvaldo Gonzalez; Magno Ayala; Jorge Rodas; Raul Gregor. 2021. "Algorithm for Implementation of Optimal Vector Combinations in Model Predictive Current Control of Six-Phase Induction Machines." Energies 14, no. 13: 3857.
Modulated model predictive current control techniques are considered an interesting option to control multiphase drives due to their control flexibility and fast dynamic response. However, a practical stability study of those techniques is still missing. This paper presents an experimental stability study, to quantify the limits of stability, to modulated predictive current controllers applied to an asymmetrical six-phase induction machine. Experimental results are presented to verify the results of the theoretical analysis in terms of stability ranges regarding sampling frequency and rotor speed.
Magno Ayala; Jesus Doval-Gandoy; Osvaldo Gonzalez; Jorge Rodas; Raul Gregor; Marco Rivera. Experimental Stability Study of Modulated Model Predictive Current Controllers Applied to Six-Phase Induction Motor Drives. IEEE Transactions on Power Electronics 2021, 36, 13275 -13284.
AMA StyleMagno Ayala, Jesus Doval-Gandoy, Osvaldo Gonzalez, Jorge Rodas, Raul Gregor, Marco Rivera. Experimental Stability Study of Modulated Model Predictive Current Controllers Applied to Six-Phase Induction Motor Drives. IEEE Transactions on Power Electronics. 2021; 36 (11):13275-13284.
Chicago/Turabian StyleMagno Ayala; Jesus Doval-Gandoy; Osvaldo Gonzalez; Jorge Rodas; Raul Gregor; Marco Rivera. 2021. "Experimental Stability Study of Modulated Model Predictive Current Controllers Applied to Six-Phase Induction Motor Drives." IEEE Transactions on Power Electronics 36, no. 11: 13275-13284.
Model-based predictive control techniques, with finite set control, are considered an interesting option to control multiphase drives due to their control flexibility and fast dynamic response. However, those techniques have some drawbacks such as a high computational cost, poor ( x−y ) currents reduction, and steady-state error, especially at high speeds. To improve some of these drawbacks, modulation stages have been presented as an alternative. However, some of those drawbacks have not been improved. This article proposes a novel approach to the classic predictive current control (PCC) applied to an asymmetrical six-phase induction machine, where a space vector modulation with specific vectors is used in order to improve the ( x−y ) currents, the steady-state error and total harmonic distortion (THD) at high operation speeds. Experimental results are presented to demonstrate the characteristics of the proposed control technique in terms of current tracking, ( x−y ) currents reduction and THD of stator currents compared to the classic PCC.
Magno Ayala; Jesus Doval-Gandoy; Jorge Rodas; Osvaldo Gonzalez; Raul Gregor; Marco Rivera. A Novel Modulated Model Predictive Control Applied to Six-Phase Induction Motor Drives. IEEE Transactions on Industrial Electronics 2021, 68, 3672 -3682.
AMA StyleMagno Ayala, Jesus Doval-Gandoy, Jorge Rodas, Osvaldo Gonzalez, Raul Gregor, Marco Rivera. A Novel Modulated Model Predictive Control Applied to Six-Phase Induction Motor Drives. IEEE Transactions on Industrial Electronics. 2021; 68 (5):3672-3682.
Chicago/Turabian StyleMagno Ayala; Jesus Doval-Gandoy; Jorge Rodas; Osvaldo Gonzalez; Raul Gregor; Marco Rivera. 2021. "A Novel Modulated Model Predictive Control Applied to Six-Phase Induction Motor Drives." IEEE Transactions on Industrial Electronics 68, no. 5: 3672-3682.
The proposal of new current control techniques for power converters and electric motor drives has been one of the main research topics in the fields of power converters and drives during the past years. Usually, when evaluating and comparing the performance of current controllers, various figures of merit (FMs) are used, e.g., the mean squared error or the absolute error between the reference and the measurement. Here, it is shown that such FMs have a random nature. Nevertheless, only one result is reported in many published articles, for each FMs. Also, it is not indicated whether or not more than one trial has been performed to obtain the FM. In that case, opposite conclusions can be reached when two current controllers are compared, depending on the chosen results. In this sense, the number, $n$ , of experimental runs required to accurately compare any FM, is proposed in order to address this problem. Likewise, a statistical comparison procedure is introduced to evaluate the relative performance of two controllers using any FM. Also, based on the proposed statistical comparison methodology compared to other criteria, an exhaustive simulation analysis is presented comparing the accuracy of decision-making. Finally, a real data set application based on experimental results is used to illustrate the proposed procedure.
Gustavo I. Rivas-Martinez; Jorge Rodas; Jesus Doval Gandoy. Statistical Tools to Evaluate the Performance of Current Control Strategies of Power Converters and Drives. IEEE Transactions on Instrumentation and Measurement 2021, 70, 1 -11.
AMA StyleGustavo I. Rivas-Martinez, Jorge Rodas, Jesus Doval Gandoy. Statistical Tools to Evaluate the Performance of Current Control Strategies of Power Converters and Drives. IEEE Transactions on Instrumentation and Measurement. 2021; 70 ():1-11.
Chicago/Turabian StyleGustavo I. Rivas-Martinez; Jorge Rodas; Jesus Doval Gandoy. 2021. "Statistical Tools to Evaluate the Performance of Current Control Strategies of Power Converters and Drives." IEEE Transactions on Instrumentation and Measurement 70, no. : 1-11.
In this manuscript, the high-accuracy stator currents tracking issue is considered for a six-phase induction motor subject to external perturbations and uncertainties due to unmeasurable rotor currents and electrical parameter variations. To achieve the control goals, the common two-cascade controllers structure is required for this type of motor. The first controller in the outer loop consists of a proportional integral to regulate the speed. Then, the second is the proposed inner nonlinear stator currents controller based on a robust discrete-time terminal super-twisting algorithm supported by the time-delay estimation method. For the design procedure, the discrete-time stator currents dynamics are derived; for example, the vector of the matched perturbations and unmeasurable rotor currents are specified to simplify the estimation. A detailed stability analysis of the closed-loop error dynamics using Lyapunov theory is given. Finally, a real asymmetrical six-phase induction motor is used to implement in real-time the developed method and to illustrate its effectiveness and robustness. The results obtained reveal a satisfactory stator currents tracking in steady state and transient conditions and under variation in the magnetizing inductance. Moreover, a comparative study with an existing method in steady state for two different rotor speeds is presented to show the superiority of the proposed discrete-time technique.
Yassine Kali; Maarouf Saad; Jesus Doval-Gandoy; Jorge Rodas. Discrete Terminal Super-Twisting Current Control of a Six-Phase Induction Motor. Energies 2021, 14, 1339 .
AMA StyleYassine Kali, Maarouf Saad, Jesus Doval-Gandoy, Jorge Rodas. Discrete Terminal Super-Twisting Current Control of a Six-Phase Induction Motor. Energies. 2021; 14 (5):1339.
Chicago/Turabian StyleYassine Kali; Maarouf Saad; Jesus Doval-Gandoy; Jorge Rodas. 2021. "Discrete Terminal Super-Twisting Current Control of a Six-Phase Induction Motor." Energies 14, no. 5: 1339.
Multiphase machines have been reemerged for high-power as well as fault-tolerant applications such as electric vehicles and wind turbines. Nevertheless, these types of machines are typically built only for industries for specific purposes. Therefore, the availability of multiphase machines in the market for academic research work, for instance at universities, is limited due to they require special construction processes and involve high initial costs for the companies. For that reason, the aim of this paper is to present a step-by-step design of a multiphase winding of an induction machine (IM) from a commercial three-phase IM for academic research use. The obtained results will be first analyzed by using the ANSYS Maxwell simulation environment. Then, a model-based current controller will be performed to validate the proposed design and the electric parameters of the six-phase IM.
Echague Gary; Ayala Magno; Rodas Jorge. Design, Analysis and Validation of a Six-Phase Induction Machine from a Commercial Three-Phase for Academic Research. IEEE Latin America Transactions 2020, 18, 1943 -1952.
AMA StyleEchague Gary, Ayala Magno, Rodas Jorge. Design, Analysis and Validation of a Six-Phase Induction Machine from a Commercial Three-Phase for Academic Research. IEEE Latin America Transactions. 2020; 18 (11):1943-1952.
Chicago/Turabian StyleEchague Gary; Ayala Magno; Rodas Jorge. 2020. "Design, Analysis and Validation of a Six-Phase Induction Machine from a Commercial Three-Phase for Academic Research." IEEE Latin America Transactions 18, no. 11: 1943-1952.
In this paper, a simultaneous calibration algorithm of the parameters of the attitude and altitude control for an unmanned aerial vehicle (UAV) is proposed. The algorithm is based on the multi-objective particle swarm optimization (MOPSO) technique. This algorithm is implemented by using the free PX4 software for the Pixhawk2 controller. The behavior of the UAV is simulated given its physical characteristics by means of a non-linear model and a search of the controller parameters. This latter is based on a proportional (P) position controller in cascade with a proportional-integral-derivative (PID) speed controller of its height and each one of its Euler angles. To perform this search, the PID gains K p1 , K p2 , K i and K d of each of the degrees of freedom are used to define vectors considered particle positions by the MOPSO algorithm, which moves them through a search space to find sets of optimum values according to Pareto, or the Pareto Front. The search is carried out based exclusively on Pareto dominance concepts, comparing parameters of step responses (overshoot, rise time, root-mean-square error) of each of the degrees of freedom. In order to show the efficiency of the proposal, simulation results are provided by using the calibration methodology obtaining good results.
Nicolas Gomez; Victor Gomez; Enrique Paiva; Jorge Rodas; Raul Gregor. Flight Controller Optimization of Unmanned Aerial Vehicles using a Particle Swarm Algorithm. 2020 International Conference on Unmanned Aircraft Systems (ICUAS) 2020 .
AMA StyleNicolas Gomez, Victor Gomez, Enrique Paiva, Jorge Rodas, Raul Gregor. Flight Controller Optimization of Unmanned Aerial Vehicles using a Particle Swarm Algorithm. 2020 International Conference on Unmanned Aircraft Systems (ICUAS). 2020; ():.
Chicago/Turabian StyleNicolas Gomez; Victor Gomez; Enrique Paiva; Jorge Rodas; Raul Gregor. 2020. "Flight Controller Optimization of Unmanned Aerial Vehicles using a Particle Swarm Algorithm." 2020 International Conference on Unmanned Aircraft Systems (ICUAS) , no. : .
Multiphase machines are gaining popularity in clean, reliable and affordable energy systems for their robustness, reliability and fault-tolerant behavior. This paper addresses the problem of parameters estimation and the problem of controlling the currents of an asymmetrical six-phase induction machine with unmeasurable rotor currents. On one hand, this work proposes the use of recursive least squares estimation method that is effective and simple and allows fast convergence of the parameters to their real values. On the other hand, this paper proposes an augmented super-twisting algorithm that allows high tracking accuracy, fast finite-time convergence, matched and mismatched uncertainties rejection. Hardware-in-the-loop simulations have been conducted to demonstrate the performance and the efficiency of the estimation method and the developed nonlinear controller for the considered system.
Yassine Kali; Maarouf Saad; Ayoub Bouchama; Reza Dehbozorgi; Jean-Nicolas Paquin; Luc-Andre Gregoire; Jean Belanger; Jorge Rodas. HIL Simulation of On-line Parameters Estimation and Current Control of a Six-Phase Induction Machine using OPAL-RT Technologies. 2020 IEEE Power & Energy Society General Meeting (PESGM) 2020, 1 -5.
AMA StyleYassine Kali, Maarouf Saad, Ayoub Bouchama, Reza Dehbozorgi, Jean-Nicolas Paquin, Luc-Andre Gregoire, Jean Belanger, Jorge Rodas. HIL Simulation of On-line Parameters Estimation and Current Control of a Six-Phase Induction Machine using OPAL-RT Technologies. 2020 IEEE Power & Energy Society General Meeting (PESGM). 2020; ():1-5.
Chicago/Turabian StyleYassine Kali; Maarouf Saad; Ayoub Bouchama; Reza Dehbozorgi; Jean-Nicolas Paquin; Luc-Andre Gregoire; Jean Belanger; Jorge Rodas. 2020. "HIL Simulation of On-line Parameters Estimation and Current Control of a Six-Phase Induction Machine using OPAL-RT Technologies." 2020 IEEE Power & Energy Society General Meeting (PESGM) , no. : 1-5.
Unmanned aerial vehicles (UAVs) are affordable these days. For that reason, there are currently examples of the use of UAVs in recreational, professional and research applications. Most of the commercial UAVs use Px4 for their operating system. Even though Px4 allows one to change the flight controller structure, the proportional-integral-derivative (PID) format is still by far the most popular choice. A selection of the PID controller parameters is required before the UAV can be used. Although there are guidelines for the design of PID parameters, they do not guarantee the stability of the UAV, which in many cases, leads to collisions involving the UAV during the calibration process. In this paper, an offline tuning procedure based on the multi-objective particle swarm optimization (MOPSO) algorithm for the attitude and altitude control of a Px4-based UAV is proposed. A Pareto dominance concept is used for the MOPSO to find values for the PID comparing parameters of step responses (overshoot, rise time and root-mean-square). Experimental results are provided to validate the proposed tuning procedure by using a quadrotor as a case study.
Victor Gomez; Nicolas Gomez; Jorge Rodas; Enrique Paiva; Maarouf Saad; Raul Gregor. Pareto Optimal PID Tuning for Px4-Based Unmanned Aerial Vehicles by Using a Multi-Objective Particle Swarm Optimization Algorithm. Aerospace 2020, 7, 71 .
AMA StyleVictor Gomez, Nicolas Gomez, Jorge Rodas, Enrique Paiva, Maarouf Saad, Raul Gregor. Pareto Optimal PID Tuning for Px4-Based Unmanned Aerial Vehicles by Using a Multi-Objective Particle Swarm Optimization Algorithm. Aerospace. 2020; 7 (6):71.
Chicago/Turabian StyleVictor Gomez; Nicolas Gomez; Jorge Rodas; Enrique Paiva; Maarouf Saad; Raul Gregor. 2020. "Pareto Optimal PID Tuning for Px4-Based Unmanned Aerial Vehicles by Using a Multi-Objective Particle Swarm Optimization Algorithm." Aerospace 7, no. 6: 71.
Multiphase induction generators are gaining popularity in wind energy systems for their robustness, reliability and fault-tolerant behavior when compared to the famous three-phase ones. This work proposes an advanced robust nonlinear control strategy for a multiphase induction generator in a variable speed wind energy conversion system. The considered structure in this paper consists of a six-phase induction generator and two conventional three-phase two-level voltage source converters. The stator currents of the structure are regulated using the proposed method that consists of a time delay estimation-based modified super-twisting. On one hand, and a proportional-integral regulates the speed in an outer control loop. On the other hand, the proposed method regulates the stator currents in an inner control loop. The stability analysis of the closed-loop error dynamics is proved using a quadratic Lyapunov function. Finally, numerical simulations have been carried out on a model of a real six-phase induction generator to show the good features of the designed method.
Yassine Kali; Maarouf Saad; Jorge Rodas; Imad Mougharbel; Khalid Benjelloun. Robust Control of a 6-Phase Induction Generator for Variable Speed Wind Energy Conversion System. 2020 5th International Conference on Renewable Energies for Developing Countries (REDEC) 2020, 1 -6.
AMA StyleYassine Kali, Maarouf Saad, Jorge Rodas, Imad Mougharbel, Khalid Benjelloun. Robust Control of a 6-Phase Induction Generator for Variable Speed Wind Energy Conversion System. 2020 5th International Conference on Renewable Energies for Developing Countries (REDEC). 2020; ():1-6.
Chicago/Turabian StyleYassine Kali; Maarouf Saad; Jorge Rodas; Imad Mougharbel; Khalid Benjelloun. 2020. "Robust Control of a 6-Phase Induction Generator for Variable Speed Wind Energy Conversion System." 2020 5th International Conference on Renewable Energies for Developing Countries (REDEC) , no. : 1-6.
In this paper, the problem of controlling three-phase induction motors with unmeasurable states is tackled. To that end, a finite-time robust nonlinear current control is applied. The controller employed is the first order sliding mode with exponential reaching law variant. Moreover, in order to estimate some variables that are not measurable, such as the rotor current, a state observer based on Luenberger observer is implemented. Simulation results show a good tracking of the desired reference, given that there exist some dynamics which were not modeled and there are fast changes in the reference.
E. Paiva; L. Delorme; M. Gomez-Redondo; E. Cristaldo; J. Rodas; Y. Kali; R. Gregor. Sliding Mode Current Control with Luenberger Observer applied to a Three Phase Induction Motor. 2020 5th International Conference on Renewable Energies for Developing Countries (REDEC) 2020, 1 -5.
AMA StyleE. Paiva, L. Delorme, M. Gomez-Redondo, E. Cristaldo, J. Rodas, Y. Kali, R. Gregor. Sliding Mode Current Control with Luenberger Observer applied to a Three Phase Induction Motor. 2020 5th International Conference on Renewable Energies for Developing Countries (REDEC). 2020; ():1-5.
Chicago/Turabian StyleE. Paiva; L. Delorme; M. Gomez-Redondo; E. Cristaldo; J. Rodas; Y. Kali; R. Gregor. 2020. "Sliding Mode Current Control with Luenberger Observer applied to a Three Phase Induction Motor." 2020 5th International Conference on Renewable Energies for Developing Countries (REDEC) , no. : 1-5.
In this paper, the problem of high-accuracy stator currents tracking of a six-phase induction motor in the presence of perturbations and unmeasurable rotor currents is tackled. Since the good features offered by sliding mode theory motivate the community of researchers on control, a time delay estimation based discrete-time super-twisting controller is proposed. First of all, an outer loop is performed to regulate the speed and to construct the desired stator currents. Then, the inner loop, based on an indirect rotor field-oriented control, is performed based on the proposed method. The proposed structure allows an accurate and simple estimation of uncertainties and rotor currents, a good tracking, a fast convergence of the currents tracking error to a neighbour of zero. The design procedure and the stability analysis are detailed for the current closed-loop system. Experimental work was carried out on a six-phase induction motor to demonstrate the effectiveness of the developed discrete approach. In addition, the performances obtained are compared to the ones obtained using the discrete-time sliding mode with time delay estimation. The results obtained highlighted the satisfactory stator currents tracking performance in steady-state and transient conditions and under different sampling times, parameters mismatch and with load and no-load conditions.
Yassine Kali; Magno Ayala; Jorge Rodas; Maarouf Saad; Jesus Doval-Gandoy; Raul Gregor; Khalid Benjelloun. Time Delay Estimation Based Discrete-Time Super-Twisting Current Control for a Six-Phase Induction Motor. IEEE Transactions on Power Electronics 2020, 35, 12570 -12580.
AMA StyleYassine Kali, Magno Ayala, Jorge Rodas, Maarouf Saad, Jesus Doval-Gandoy, Raul Gregor, Khalid Benjelloun. Time Delay Estimation Based Discrete-Time Super-Twisting Current Control for a Six-Phase Induction Motor. IEEE Transactions on Power Electronics. 2020; 35 (11):12570-12580.
Chicago/Turabian StyleYassine Kali; Magno Ayala; Jorge Rodas; Maarouf Saad; Jesus Doval-Gandoy; Raul Gregor; Khalid Benjelloun. 2020. "Time Delay Estimation Based Discrete-Time Super-Twisting Current Control for a Six-Phase Induction Motor." IEEE Transactions on Power Electronics 35, no. 11: 12570-12580.
Nowadays, model predictive current control strategy has become a viable alternative because of its fast response for high-reliability systems, such as multiphase machines. In that regard, this paper proposes a comparative assessment of four current controllers based on the model using different approaches as virtual vectors, modulation techniques and further, combining these strategies in order to deal at the same time with the regulation of the main and secondary currents components, known as (α-ß) and (x-y), respectively, applied to six-phase induction machines. Simulation results are presented so as to show the effectiveness of the four model predictive current controllers, taking into account the mean squared error and the total harmonic distortion of the stator currents in both steady and dynamic conditions.
O. Gonzalez; M. Ayala; C. Romero; Jorge Rodas; R. Gregor; L. Delorme; I. Gonzalez-Prieto; M.J. Duran; M. Rivera. Comparative Assessment of Model Predictive Current Control Strategies applied to Six-Phase Induction Machines. 2020 IEEE International Conference on Industrial Technology (ICIT) 2020, 1037 -1043.
AMA StyleO. Gonzalez, M. Ayala, C. Romero, Jorge Rodas, R. Gregor, L. Delorme, I. Gonzalez-Prieto, M.J. Duran, M. Rivera. Comparative Assessment of Model Predictive Current Control Strategies applied to Six-Phase Induction Machines. 2020 IEEE International Conference on Industrial Technology (ICIT). 2020; ():1037-1043.
Chicago/Turabian StyleO. Gonzalez; M. Ayala; C. Romero; Jorge Rodas; R. Gregor; L. Delorme; I. Gonzalez-Prieto; M.J. Duran; M. Rivera. 2020. "Comparative Assessment of Model Predictive Current Control Strategies applied to Six-Phase Induction Machines." 2020 IEEE International Conference on Industrial Technology (ICIT) , no. : 1037-1043.
Unmanned aerial vehicles have become a disruptive technology, which has experienced exponential growth in several applications. The control of these vehicles is a fairly wide area and the cascade PID controller is the most used in practice. However, this latter structure doesn’t ensure high performances in the presence of unmodelled dynamics, uncertainties and external abrupt disturbances. To that end, this work proposes a new method that consists of a non-linear cascade configuration of the variable structure control between first order sliding mode based on exponential reaching law and modified super-twisting second order sliding mode algorithm. The developed method is tested on simulation on a quadrotor system, the results obtained demonstrate good performance for trajectory tracking and as well as other non-linear controller options, it is robust against unmodeled dynamics and disturbances.
E. Paiva; M. Gomez-Redondo; J. Rodas; Y. Kali; M. Saad; R. Gregor; H. Fretes. Cascade First and Second Order Sliding Mode Controller of a QuadRotor UAV based on Exponential Reaching Law and Modified Super-Twisting Algorithm. 2019 Workshop on Research, Education and Development of Unmanned Aerial Systems (RED UAS) 2019, 100 -105.
AMA StyleE. Paiva, M. Gomez-Redondo, J. Rodas, Y. Kali, M. Saad, R. Gregor, H. Fretes. Cascade First and Second Order Sliding Mode Controller of a QuadRotor UAV based on Exponential Reaching Law and Modified Super-Twisting Algorithm. 2019 Workshop on Research, Education and Development of Unmanned Aerial Systems (RED UAS). 2019; ():100-105.
Chicago/Turabian StyleE. Paiva; M. Gomez-Redondo; J. Rodas; Y. Kali; M. Saad; R. Gregor; H. Fretes. 2019. "Cascade First and Second Order Sliding Mode Controller of a QuadRotor UAV based on Exponential Reaching Law and Modified Super-Twisting Algorithm." 2019 Workshop on Research, Education and Development of Unmanned Aerial Systems (RED UAS) , no. : 100-105.
This study deals with the problem of controlling rotor speed and stator currents of an asymmetrical six-phase induction machine with uncertain dynamics, disturbances, and unmeasurable rotor currents and proposes a robust non-linear variable structure controller. First of all, an outer control loop based on a proportional–integral regulator is performed to control the rotor speed and to construct the desired stator current references. Then, the inner loop is performed based on the proposed method that combines the time delay estimation method and discrete sliding mode control based on exponential reaching law. This structure allows an accurate and simple estimation of uncertainties and rotor currents, a high-tracking precision, a convergence of the stator currents to their known desired references in finite-time and chattering reduction. The design procedure is detailed step by step and the stability analysis and the convergence time are established for the current closed-loop system. Experimental work was carried out on an asymmetrical six-phase induction motor drive to show the effectiveness and performance of the proposed robust non-linear discrete method. The results obtained highlighted the good tracking performance of the stator currents.
Yassine Kali; Maarouf Saad; Jesus Doval‐Gandoy; Jorge Rodas; Khalid Benjelloun. Discrete sliding mode control based on exponential reaching law and time delay estimation for an asymmetrical six‐phase induction machine drive. IET Electric Power Applications 2019, 13, 1660 -1671.
AMA StyleYassine Kali, Maarouf Saad, Jesus Doval‐Gandoy, Jorge Rodas, Khalid Benjelloun. Discrete sliding mode control based on exponential reaching law and time delay estimation for an asymmetrical six‐phase induction machine drive. IET Electric Power Applications. 2019; 13 (11):1660-1671.
Chicago/Turabian StyleYassine Kali; Maarouf Saad; Jesus Doval‐Gandoy; Jorge Rodas; Khalid Benjelloun. 2019. "Discrete sliding mode control based on exponential reaching law and time delay estimation for an asymmetrical six‐phase induction machine drive." IET Electric Power Applications 13, no. 11: 1660-1671.
In this work, a time delay estimation based optimal conventional and second order sliding mode stator currents controller are proposed and compared for a six-phase induction machine fed by voltage source power converters. In a first step, the speed is regulated in an outer loop using a proportional-integral controller. Then, in a second step, the stator currents are controlled in an inner loop using the proposed methods. On one hand, the first method is a combination of time delay estimation with optimal first order sliding mode with exponential reaching law. On the other hand, the second method is a combination of time delay estimation with optimal super-twisting control. Based on Lyapunov theory, the stability of the stator currents closed-loop error dynamics is demonstrated and sufficient conditions of stability are determinate. As a case example, numerical simulations have been conducted on an asymmetrical six-phase induction machine to demonstrate the good features of the developed nonlinear controllers.
Y. Kali; J. Rodas; M. Saad; R. Gregor; J. Doval-Gandoy; K. Benjelloun. Comparative Study of Time Delay Estimation Based Optimal 1st and 2nd Order Sliding Mode for Current Regulation of Six-Phase Induction Machines. IECON 2019 - 45th Annual Conference of the IEEE Industrial Electronics Society 2019, 1, 6194 -6199.
AMA StyleY. Kali, J. Rodas, M. Saad, R. Gregor, J. Doval-Gandoy, K. Benjelloun. Comparative Study of Time Delay Estimation Based Optimal 1st and 2nd Order Sliding Mode for Current Regulation of Six-Phase Induction Machines. IECON 2019 - 45th Annual Conference of the IEEE Industrial Electronics Society. 2019; 1 ():6194-6199.
Chicago/Turabian StyleY. Kali; J. Rodas; M. Saad; R. Gregor; J. Doval-Gandoy; K. Benjelloun. 2019. "Comparative Study of Time Delay Estimation Based Optimal 1st and 2nd Order Sliding Mode for Current Regulation of Six-Phase Induction Machines." IECON 2019 - 45th Annual Conference of the IEEE Industrial Electronics Society 1, no. : 6194-6199.
Finite control set model-based predictive control techniques are distinguished by being an interesting alternative to traditional field oriented control techniques for multiphase drives due to their fast dynamic response and flexibility in the introduction of constraints. However, those predictive control techniques have some drawbacks regulating the (x−y) current components which can cause machine losses as well as a high computational burden. This paper presents a comparative study of an enhanced predictive current control technique with a conventional predictive control technique and two hybrid predictive control techniques applied to an asymmetrical six-phase induction motor drive in terms of current tracking, total harmonic distortion of stator currents and computational burden. Experimental results are reported to demonstrate the benefits of the different current control techniques by using the mean squared error and total harmonic distortion of stator currents as quality figures of merit and the number of floating point operations to measure the computational burden of each predictive control, thus concluding the advantages and limitations of each technique at transient and steady regimes.
Magno Ayala; Jesus Doval-Gandoy; Jorge Rodas; Osvaldo Gonzalez; Raul Gregor. Current control designed with model based predictive control for six-phase motor drives. ISA Transactions 2019, 98, 496 -504.
AMA StyleMagno Ayala, Jesus Doval-Gandoy, Jorge Rodas, Osvaldo Gonzalez, Raul Gregor. Current control designed with model based predictive control for six-phase motor drives. ISA Transactions. 2019; 98 ():496-504.
Chicago/Turabian StyleMagno Ayala; Jesus Doval-Gandoy; Jorge Rodas; Osvaldo Gonzalez; Raul Gregor. 2019. "Current control designed with model based predictive control for six-phase motor drives." ISA Transactions 98, no. : 496-504.