Raymundo Cordero Garcia
@ufms.br
Professor
RESEARCH, TEACHING, or OTHER INTERESTS
Electrical and Electronic Engineering
Scopus Publications
Scopus Publications
Raymundo Cordero, Igor Ono, Thyago Estrabis, Gabriel Gentil, Matheus Caramalac, and Walter Suemistu
Springer Science and Business Media LLC
Moacyr A. G. de Brito, Egon H. B. Dourado, Leonardo P. Sampaio, Sergio A. O. da Silva, and Raymundo C. Garcia
MDPI AG
This paper presents an analysis of the sliding mode control (SMC) method applied to a single-phase grid-connected voltage source inverter (VSI) with L and LCL filters. First, simulation results were presented for the L filter, and then, after some adjustments, the same theory was applied to the LCL VSI with active damping. To improve the obtained results for the SMC control, we adopted the hyperbolic tangent function and the explicit establishment of the modulation index m in the mathematical procedure to help reduce the chattering phenomena; later on, the same function was replaced by the usage of a proportional plus resonant controller to continuously improve the control system responses.
Matheus Pelzl, Raymundo Cordero, Thyago Estrabis, and Walter Suemitsu
IEEE
The current control of a LCL-filtered grid converter is important to optimize the connection of a renewable energy source with the electrical grid. To achieve this objective, a robust and accurate sinusoidal current control is required to transfer power to the grid with a power factor near unity. On the other hand, Generalized predictive control (GPC) was applied to control the output current of the LCL filter connected to an AC grid. GPC control law depends on a Hessian matrix. However, depending on the plant and the GPC structure, this matrix could be ill-conditioned (almost singular), being the GPC control law very sensitive to problems such as noise or numerical representation errors, typical problems in embedded systems. This paper proposes the application of truncated singular value decomposition (TSVD) to get a robust GPC system to control the LCL filter output current. Simulations show that the proposed approach allows robust LCL filter output current control against noise and numerical errors.
Raymundo Cordero, Matheus Pelzl, Polynne Modesto, and Walter Suemitsu
IEEE
Resolver is a sensor used to measure the motor shaft angle in harsh conditions. This sensor produces two amplitude-modulation voltages. On the other hand, vector control of three-phase motors requires sensing at least two stator currents. Hence, the data acquisition system (DAQ) of a motor drive must digitize at least four analog signals when a resolver is applied in vector control. Most DAQs apply time-division multiplexing (TDM) to simplify the signal digitization. However, frequency-division multiplexing (FDM) was proposed to simplify the acquisition of the stator currents of a three-phase motor drives when a resolver is used as angular position sensor. FDM allows a faster sampling of the signals than TDM. This multiplexing approach was improved by using a higher resolver excitation signal. This paper explores the application of FDM in vector control of a permanent magnet synchronous motor and analyze the effect of this multiplexing approach in the motor speed control.
Rhuan Barbosa, Matheus Pelzl, Raymundo Cordero, Matheus Caramalac, and Walter Suemitsu
IEEE
Electric motor is a nonlinear plant whose dynamics depends on the operation point. Non-linear controllers based on artificial intelligence, such as Fuzzy logic, usually have better performance to control power electronics devices than linear controllers (e.g., PID regulators). Fuzzy controllers are applied in many power electronics applications and motor drives. On the other hand, many FPGAs are being used to implement motor drives control algorithms as a FPGA allows creating a customized control architecture and has fast processing speed. However, learning and implement Fuzzy controllers in FPGA for undergraduation students is a difficult task. This paper presents a didactic implementation of a Fuzzy controller in FPGA applied to scalar speed control of an induction motor. Scalar control was selected due to it has a less theoretical complexity that other control techniques such as direct torque control (DTC) and field oriented control (FOC). FPGA-in-the-loop (FIL) methodology was applied to test the Fuzzy controller: the controller was implemented in FPGA, and the inverter and motor was designed in a simulation software. Tests show that the methodology used to create the Fuzzy controller allows students to learn about Fuzzy logic and FPGA programming.
Raymundo Cordero, Thyago Estrabis, Gabriel Gentil, Matheus Caramalac, Walter Suemitsu, João Onofre, Moacyr Brito, and Juliano dos Santos
MDPI AG
Some novel applications require the tracking/rejection of biased sinusoidal reference/distur-bances. According to the internal model principle (IMP), a controller must embed the model of a biased sinusoidal signal to track references and also reject perturbations modeled through the aforementioned signal. However, the design of that kind of controller is not straightforward, especially when they are implemented in digital processors. This paper presents a controller, based on generalized predictive control (GPC), designed for tracking/rejection of biased sinusoidal signals. In general, GPC is based on the prediction of the plant responses through an augmented prediction model. The proposed approach develops an augmented model that predicts the future errors. The prediction model and the control law used in the proposed approach embed the discrete-time model of a biased sinusoidal signal. Thus, the proposed controller can track/reject biased sinusoidal references/disturbances. The predicted errors and the future inputs of the proposed augmented model are used to define the cost function that measures the control performance. An optimization technique was applied to obtain the solution of the cost function, which is the optimal sequence of future model inputs that allows defining the control law. Experimental tests prove that the proposed controller can asymptotically track and reject biased sinusoidal signals.
Patrik Olã Bressan, José Marcato Junior, José Augusto Correa Martins, Maximilian Jaderson de Melo, Diogo Nunes Gonçalves, Daniel Matte Freitas, Ana Paula Marques Ramos, Michelle Taís Garcia Furuya, Lucas Prado Osco, Jonathan de Andrade Silva,et al.
Elsevier BV
R. Cordero, T. Estrabis, M. A. Brito, and G. Gentil
Institute of Electrical and Electronics Engineers (IEEE)
Sinusoidal reference tracking is required in important practical applications. Resonant controllers are suitable for that task. However, stable implementation of these controllers in a digital processor is difficult to achieve. On the other hand, quasi-resonant controllers are easier to implement, but they do not guarantee asymptotic reference tracking. This brief proposes a new resonant controller based on Generalized Predictive Control (GPC) and Internal Model Principle (IMP). The first-order and second-order difference operators are applied to create a GPC system whose structure embeds the ${Z}$ -transform of the sinusoidal reference. Thus, according to IMP, the proposed controller, named Resonant Generalized Predictive Control (RGPC), asymptotically tracks sinusoidal references. Besides, the proposed RGPC has the advantages of GPC, such as fast response and easy implementation in digital processors. Experimental tests prove that the proposed RGPC has better performance than other controllers for sinusoidal reference tracking.
Raymundo Cordero, Sara de Oliveira, Nicolle Arakaki, Polynne Modesto, and Gleidson Kumagai
IEEE
Frequency response method is an important approach in the design and analysis of plants and controllers. Bode plot is a simple technique to graphically represent a system frequency response. Getting the Bode plot from experimental data would help students to be motivated and understand the frequency response method, which is usually taught through simulations or theoretical examples. There are tools that allow getting the experimental Bode plot of a plant, but they are expensive. This paper presents an educational low-cost system that experimentally gets the Bode plot using Arduino. The sound card of the notebook intended for programming the Arduino is used to generate the sinusoidal voltages used to get the plant frequency response. A phase detector and two peak detectors allows getting the phase delay and the gain for different frequencies. Those data are sent to the notebook, where a processing program developed in the open-source Octave software used those data to create the Bode plot. Experimental results shows that the proposed hardware can be easily applied as an educational tool to understand frequency response through Bode plot.
Raymundo Cordero, Polynne Modesto, Thyago Estrabis, and João Onofre
Springer International Publishing
André D’Estefani, Raymundo Cordero, and João Onofre
Springer International Publishing
Thyago Estrabis, Cesar Santos, Raymundo Cordero, Walter Suemitsu, Gabriel Gentil, and Matheus Pelzl
IEEE
LCL filters are widely used to connect a renewable electrical power source to the electrical grid. The optimal power transfer to the grid depends on the tracking of a sinusoidal current reference synchronized to the grid voltage. However, the tracking of that reference is a difficult task. On the other hand, the sinusoidal reference can be considered as composed of a set of polynomials of different degrees. Thus, this paper explores the application of polynomial reference tracking generalized predictive controller (Poly-GPC) to control the output current of the LCL filter connected to an AC grid. Different tests using the Poly-GPC with different polynomial reference degrees were performed to verify the relationship between the polynomial degree used to approximate the sinusoidal reference with the control accuracy. Simulation results show that the Poly-GPC can be used to control an LCL filter. An analysis of the effect of the polynomial order used to approximate the sinusoidal reference in the current reference tracking is done. The Poly-GPC adds integrators to the control system to reduce the tracking error. It was observed that adding too many integrators may create instability. However, a low number of integrators reduces the tracking performance.
Thyago Estrabis, Matheus Pelzl, Raymundo Cordero, Walter Suemitsu, Luigi Galotto, and Gabriel Gentil
IEEE
Precise and robust sensing of motor stator currents is essential for the closed-loop control of three-phase electrical motors. Usually, vector control techniques require representing the stator currents in an orthogonal αß reference system through Clarke transformation. However, problems such as aging, high temperatures and errors in the conditioning circuits distort the current signals received by the data acquisition system (DAQ) of the motor drive. Those distortions produce current measurement errors that affect the motor drive performance. This paper analyses the application of an auto-regressive neural network (AANN) to compensate for the measurement errors of the three-phase stator currents. The three stator currents of a three-phase motor are sensed to have data redundancy, as the sum of these currents is zero. AANN estimates the actual values of the stationary αß stator currents based on the distorted three-phase current signals. The compensation performance considering different AANN topologies is analyzed. Simulation results show that AANN allows compensating for the current measurement distortion. Low number of artificial neurons in the AANN hidden layers limits the compensation accuracy. However, a high number of neurons in the hidden layer also reduces the compensation performance due to over-fitting.
Américo K. Tanji, Moacyr A. G. de Brito, Marcos G. Alves, Raymundo C. Garcia, Gen-Lang Chen, and Naji R. N. Ama
MDPI AG
The electrocardiogram (ECG) is basic equipment used in the diagnosis of cardiac illness. However, in non-developed countries, most of the population does not have access to medical tests, and many hospitals do not even have these ECGs. On the other hand, the electrical signals generated by the heart and acquired by the ECG have low power and are affected by electromagnetic interference (EMI), mainly produced by the electrical system. Filtering EMI when frequency varies is a challenging task. Within this context, this work aims to produce an easy-to-use low-cost ECG with good electromagnetic disturbances rejection. The proposed noise rejection system is composed of two moving average filters and a phase-locked-loop, namely 2MAV-PLL. The system operates with a low sampling frequency and attenuates the EMI noise present in the ECG signal regardless of the amplitude, obtaining a filtered signal with a 44-dB signal–noise ratio (SNR) between the frequencies of± 10 Hz of the fundamental frequency. Simulation and experimental results prove that the ECG system can attenuate the EMI using relatively low sampling frequency, giving adequate information for health professionals to properly evaluate an electrocardiogram.
Marco Aurelio Duarte Alves, Joao O. P. Pinto, Luigi Galotto, Marcio L. M. Kimpara, Raymundo Cordero Garcia, Ruben Barros Godoy, Hebert C. Goncalves Teixeira, and Mario C. M. Campos
Institute of Electrical and Electronics Engineers (IEEE)
This paper presents the use of a radial basis function artificial neural network to estimate sensor readings exploring the analytical redundancy via auto-association. However, in order to guarantee optimal performance of the network, the training and optimization processes have been modified. In the conventional training algorithm, even if a stop criterion, such as summed squared error, is reached, one or more of the individual performance metrics, including: i) accuracy; ii) robustness; iii) spillover and iv) filtering of the neural network, may not be satisfactory while validating sensor measurements. Essentially, the proposed modification in the training algorithm is based on seeking to ensure that one or more of the metrics are met. This paper describes the proposed algorithm including all of its mathematical foundation. Afterward, a data set of a water injection pump for an oil and gas processing unit was used to train the RBF network using the conventional and the modified algorithm, and the performance of each was evaluated. Furthermore, the AAKR model is applied to the same dataset as a quality reference parameter. Finally, a comparison analysis of the developed models is presented for each of the performance metrics, as well as for overall effectiveness, demonstrating that the main advantage of the proposed approach is to obtain the estimation results equivalent or superior to the AAKR with shorter runtime and the disadvantage of having higher complexity during the model training.
R. Cordero, T. Estrabis, G. Gentil, E. A. Batista, and C. Q. Andrea
Institute of Electrical and Electronics Engineers (IEEE)
Some important applications require control systems capable of tracking high-degree polynomial references. However, polynomial reference tracking is difficult because the controller must have a fast response to track variable references. Generalized Predictive Control (GPC), used in industrial applications, has a fast response. However, up to now, GPC approaches in the literature are not designed for high-degree polynomial reference tracking. For that reason, this brief proposes a GPC system for the tracking of polynomial references of any degree. The high-order backward difference operator was used to develop an augmented prediction model designed to have an arbitrary number of embedded integrators. Thus, according to the internal model principle, the proposed predictive controller can track polynomial references of any degree. An optimization technique is used to define future control actions, while the control law is defined through the receding horizon principle. Simulation and experimental results prove that the proposed controller performs better than other approaches described in the literature.
R. Cordero, T. Estrabis, E. A. Batista, C. Q. Andrea, and G. Gentil
Institute of Electrical and Electronics Engineers (IEEE)
This brief proposes an adaptation of the Generalized Predictive Control (GPC) for ramp-reference tracking. The second-order difference operation and the plant model are used to get an augmented model with two embedded integrators and whose output is the tracking error. Differently from other GPC-based tracking algorithms, the proposed approach does not require information about the reference parameters, and the GPC prediction horizon is composed of the predicted errors instead of the expected plant outputs. Thus, the optimization function and the receding horizon strategy used in conventional GPC can be applied to get the control law. Simulation and experimental results prove that the proposed approach can successfully track constant and ramp references. The proposed method is applicable for single-input single-outputs plants. However, the mathematical background presented in this brief can be used in the development of new GPC strategies.
Raymundo Cordero Garcia, Faete J. T. Filho, Joao Onofre Pereira Pinto, Walter Issamu Suemitsu, Brayan Sobral da Fonseca, and Angelo Darcy Molin Brun
Institute of Electrical and Electronics Engineers (IEEE)
Frequency domain multiplexing (FDM) allows simplifying the data acquisition in vector control when the resolver is used as a position sensor. However, the crosstalk reduction in the demultiplexing process is still a difficult task. This article proposes an improvement of the FDM-based acquisition system through synchronous sampling and Differential Evolution (DE). The resolver signals and the PWM carrier are synchronized so that the resolver outputs are zero when the PWM carrier reaches its valleys. Thus, the fundamental component of the stator currents can be easily estimated from the signals sent to the acquisition system. These estimated current signals and an angle tracking observer (ATO) are used to estimate the angular position. DE and a discretized model of the ATO are applied in order to improve the angle estimation transient response and to reduce crosstalk. Conditions to apply the proposed multiplexing approach will be defined. Simulation and experimental results show that the proposed approach allows an accurate estimation of the current fundamental components and the angular position when FDM is used, with better performance respect to other approaches in the literature. This is the first time that a DE is used to tune an ATO.
Ruben B. Godoy, Moacyr A. G. de Brito, Raymundo C. Garcia, Marcio L. M. Kimpara, and João Onofre P. Pinto
Springer Science and Business Media LLC
Thyago Estrabis, Gabriel Gentil, and Raymundo Cordero
MDPI AG
High-performance motor drives that operate in harsh conditions require an accurate and robust angular position measurement to correctly estimate the speed and reduce the torque ripple produced by angular estimation error. For that reason, a resolver is used in motor drives as a position sensor due to its robustness. A resolver-to-digital converter (RDC) is an observer used to get the angular position from the resolver signals. Most RDCs are based on angle tracking observers (ATOs). On the other hand, generalized predictive control (GPC) has become a powerful tool in developing controllers and observers for industrial applications. However, no GPC-based RDC with zero steady-state error during constant speed operation has been proposed. This paper proposes an RDC based on the second-order difference GPC (SOD-GPC). In SOD-GPC, the second-order difference operator is applied to design a GPC model with two embedded integrators. Thus, the SOD-GPC is used to design a type-II ATO whose steady-state angle estimation error tends to zero during constant speed operation. Simulation and experimental results prove that the proposed RDC system has better performance than other literature approaches.
Thyago Estrabis, Raymundo Cordero, Moacyr Brito, Walter Suemitsu, Gabriel Gentil, and Joao Anjos
IEEE
This paper explores the application of polynomial reference tracking generalized predictive controller (Poly-GPC) to control the output current of the LCL filter connected to an AC grid. The Poly-GPC system allows the LCL output current to track the sinusoidal current reference generated to transfer the power from the Voltage Source Inverter (VSI) to the grid. The proposed controller considers that the sinusoidal current reference can be approximated as a set of polynomial signals. Simulation results show that the proposed controller can be used to control the LCL output current successfully.
Brayan Fonseca, Joao O. P. Pinto, Walter I. Suemitsu, Raymundo C. Garcia, and Marcio L. M. Kimpara
IEEE
The objective of this paper is to implement a hierarchical-like fuzzy controller of a five-phase salient pole permanent magnet synchronous motor (FP-PMSM) drive aiming to reduce the torque ripple. The fuzzy controller was developed as an intrinsically hierarchical controller, i.e., the controller controls both the speed and the pulsating torque through quadrature axis voltage. The speed control has priority over the torque ripple control. This feature is achieved by properly choosing the inputs and defining the fuzzy rules. The rules for torque ripple control are fired only when the speed has reached its desired value. This is possible only because of the speed sluggishness, against torque fastness, and the fuzzy controller fastness. One of the advantages of the fuzzy controllers, including the one proposed in this paper, is that it is developed without the need of the machine model. The paper is organized as follows: i) motivation and discussion of previous works, ii) system overview, iii) five-phase inverter SVPWM description, iv) description of the prototype composed by an 11 kW FP-PMSM, retrofitted from a three-phase PMSM, driven by a FP-IGBT VFI, 200 Vdc, and a mechanical load, v) experimental results. The experimental results show that the torque ripple using the PI controller is around 6.0 Nm peak-to-peak while using a fuzzy controller is around 2.0 Nm (3 times reduction).
Polynne Modesto, Raymundo Cordero, and Andre D'Estefani
IEEE
Resolver is an angular position sensor widely used in motor drives when robustness is critical. This sensor generates two high-frequency amplitude-modulated signals which give information about the angular position. A resolver-to-digital converter (RDC) is an equipment used to get the angular position from the resolver outputs. Many RDCs are based on angle tracking observer (ATO) which reduce the angle estimation error. The transient behavior of the angle estimation depends on the ATO parameters. This paper proposes the tuning of an ATO with two embedded integrators (a type-II system) through root-locus technique. It was used a lead compensator to improve the transient response of the ATO, while the embedded integrators make the steady-state error tend to zero for constant position and speed operation. Simulation results show that the ATO was properly tuned through root locus technique, allowing a good angle estimation.
Polynne Modesto, Thyago Estrabis, and Raymundo Cordero
IEEE
Frequency-domain multiplexing (FDM) allows simplifying the acquisition hardware applied in the vector control of three-phase motors, when a resolver sensor is used to get the angular position. Conventionally, an analog switch is used together with an analog-to-digital converter to digitize the signals. This approach is based on time-domain multiplexing (TDM). However, the application of FDM in data acquisition has many advantages respect to the conventional approach based on TDM. Signals from the stator current sensors and from the resolver can be multiplexed in frequency by combining these signals through analog adders. Nevertheless, the demultiplexing process in order to recover the original data is still a open question. This paper does an analysis of the demultiplexed signals, in order to give more theoretical background for the development of improved data acquisition systems based on FDM. Simulation results show that using a high-pass filter improves the demultiplexing of the resolver outputs.
Felipe A. Monteiro, Thyago Estrabis, Raymundo Cordero, Juliana Montemor, and Joao O. P. Pinto
IEEE
Resolver is a sensor used in applications that require a reliable angle measurement. However, getting the angular position from the resolver outputs is a difficult task. Observers called resolver-to-digital converters (RDCs) are used to get the angular position from resolver. In many researches, RDCs are estimation algorithms (software-based RDCs). The transient response and robustness against noise of the angle estimation depends on the parameters of the RDC. This paper proposes the use of a genetic algorithm (GA) to set the parameters of a type-III software-based RDC. GA is a heuristic algorithm that search a solution that minimize a fitness function. In this paper, the solution is composed by the gains of the angular tracking observer (ATO) that composes the RDC. On the other hand, the cost function is a linear combination of the error peak, the settling time and the effect of noise in the angle estimation. Simulations shows that the angle estimation using the proposed approach has accuracy, good transient response and robustness against noise. Besides, GA allows customizing the ATO in order for the RDC to give an estimation where the noise rejection or the settling time is priority.