Generalized Predictive Control with Added Zeros and Poles in Its Augmented Model for Power Electronics Applications Raymundo Cordero, Matheus Caramalac, Wisam Ali Energies, 2024 Generalized predictive control (GPC) became one of the most popular and useful control strategies for academic and industry applications. An augmented model is applied to predict the future plant responses. This augmented model can be designed to embed the model of the plant reference, allowing its tracking by the controller according to the internal model principle (IMP). On the other hand, the performance of many controllers can be improved by adding zeros and poles in their structures (e.g., lead and lag compensators). However, according to the authors’ research, adding arbitrary poles or zeros to the GPC augmented model has not been explored yet. This paper presents a simple methodology to add arbitrary zeros and poles in the GPC augmented model. A new augmented model state variable is defined. The control law of the proposed approach embeds zeros and poles when zero-pole cancellation is avoided. Simulation results (considering a LCL filter controlled by a single-phase inverter of 500 W and a polynomial reference tracking controller) and experimental tests (using a third-order linear plant controlled by a resonant controller) prove that the proposed approach improves the transient response of different kinds of predictive tracking controllers applied to control different plants (including power electronics applications), without affecting the steady-state tracking capabilities of the control systems.
Variable Frequency Resonant Controller Based on Generalized Predictive Control for Biased-Sinusoidal Reference Tracking and Multi-Layer Perceptron Raymundo Cordero, Juliana Gonzales, Thyago Estrabis, Luigi Galotto, Rebeca Padilla, João Onofre Energies, 2024 Resonant controllers are widely used in power electronics to track sinusoidal references. According to the internal model principle (IMP), these controllers should embed the poles of the Laplace or Z transform of the reference for the closed-loop system to track the reference asymptotically. Thus, tracking a sinusoidal reference is difficult as the controller should adapt its structure to embed the poles of the sinusoidal reference with variable frequency, as those poles depend on that variable frequency. On the other hand, Generalized Predictive Control (GPC) is widespread in industry applications due to its fast response, robustness and capability to include constraints. Resonant controllers based on GPC, which satisfy IMP, have been developed. However, these controllers consider the sinusoidal frequency to be constant. This paper presents a new GPC-based resonant controller with an adaptive and simple control law to track references with variable frequencies. A PLL estimates the frequency of the reference. A multi-layer perceptron uses the estimated frequency to define the gain matrix required to calculate the GPC control action. The GPC control action and the estimated frequency define the control law, which satisfies IMP in steady-state conditions. The authors did not find in the literature the proposed mathematical development of an adaptive GPC resonant controller with a discrete-time augmented model whose control law satisfies IMP. Thus, the proposed approach is helpful to develop other adaptive predictive controllers. Experimental results show that the proposed controller can track sinusoidal references whose frequencies vary in time.
Modelling of an Induction Motor and Model Reference Adaptive System (MRAS) for Speed Estimation in Xcos Rhuan Barbosa, Raymundo Cordero, Lucas Maldonado, Tatielle L. de Souza, Moacyr A. G. de Brito 2024 16th Seminar on Power Electronics and Control Sepoc 2024, 2024 Techniques based on Model Reference Adaptive System (MRAS) are considered as effective approaches for speed estimation due to their commendable performance and direct stability analysis. Different works about the application of MRAS in speed sensorless control of induction motor can be found in literature. However, students usually have problems to understand and implement MRAS algorithm. On the other hand, open source softwares allow students to understand and simulate algorithm, as students can be easily watch, analyze and edit the block diagram. Hence, this paper introduces the block diagram of a 3-phase induction motor and the MRAS algorithm developed in SCILAB/Xcos. SCILAB is an open-source software that include a block diagram simulation interface called Xcos. The MRAS algorithm in this work compares the rotor flux estimated by a reference model and an adjustable model (that depends on the mechanical speed), to get a flux estimation error. A PI regulator adjust the mechanical speed value in the adjustable model to reduce that error. The block diagrams of the dq0 induction model and the MRAS algorithm developed in Xcos and presented in this work allow student to easily understand both algorithms, widely used in motor drives. It is worth to mention that authors did not find any MRAS diagram implemented in Xcos in literature.
Sliding Mode Control for Single-Phase Grid-Connected Voltage Source Inverter with L and LCL Filters Moacyr A. G. de Brito, Egon H. B. Dourado, Leonardo P. Sampaio, Sergio A. O. da Silva, Raymundo C. Garcia Eng, 2023 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.
Application of Frequency Division Multiplexing in the Speed Control of PMSM Raymundo Cordero, Matheus Pelzl, Polynne Modesto, Walter Suemitsu Cobep 2023 17th Brazilian Power Electronics Conference and Spec 2023 8th IEEE Southern Power Electronics Conference Proceedings, 2023 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.
Application of Generalized Predictive Controller and Truncated Singular Value Decomposition for the Control of a LCL Filtered Grid Converter Matheus Pelzl, Raymundo Cordero, Thyago Estrabis, Walter Suemitsu Cobep 2023 17th Brazilian Power Electronics Conference and Spec 2023 8th IEEE Southern Power Electronics Conference Proceedings, 2023 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.
Didactic FPGA-in-the-Loop Scalar Fuzzy Control Setup for Motor Drive Education Rhuan Barbosa, Matheus Pelzl, Raymundo Cordero, Matheus Caramalac, Walter Suemitsu Cobep 2023 17th Brazilian Power Electronics Conference and Spec 2023 8th IEEE Southern Power Electronics Conference Proceedings, 2023 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.
Tracking and Rejection of Biased Sinusoidal Signals Using Generalized Predictive Controller Raymundo Cordero, Thyago Estrabis, Gabriel Gentil, Matheus Caramalac, Walter Suemitsu, João Onofre, Moacyr Brito, Juliano dos Santos Energies, 2022 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.
Semantic segmentation with labeling uncertainty and class imbalance applied to vegetation mapping 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, Zhipeng Luo, Raymundo Cordero Garcia, Lingfei Ma, Jonathan Li, Wesley Nunes Gonçalves International Journal of Applied Earth Observation and Geoinformation, 2022 Recently, Convolutional Neural Networks (CNN) methods achieved impressive success in semantic segmentation tasks. However, challenges like class imbalance around samples and the uncertainty in human pixel-labeling are not completely addressed. Here we present an approach that calculates a weight for each pixel considering its class and uncertainty during the labeling process. The pixel-wise weights are used at the training phase to increase or decrease the importance of the pixels accordingly. Experimental results were conducted adapting well-known CNN methods FCN and SegNet; however, this strategy can be applied to any segmentation method. We evaluated the experiments for semantic segmentation of urban trees in aerial imageries. The robustness of the approach was assessed using a dataset with terrestrial images from vegetation with a drastic imbalance condition. We achieved significant improvements in the tasks compared to the baseline methods. We also verified that the proposed strategy proved to be more invariant to noise. The approach presented in this paper could be used within a wide range of semantic segmentation methods to improve their robustness.
Modeling and Simulation of a Stirling Engine in SCILAB Raymundo Cordero, Thyago Estrabis, Joao Onofre, Felipe Alexandre Monteiro, Augusto Hayashi 2019 IEEE 15th Brazilian Power Electronics Conference and 5th IEEE Southern Power Electronics Conference Cobep Spec 2019, 2019
Application of Model Predictive Control in a Resolver-to-Digital Converter Thyago Vasconcelos Estrabis, Raymundo Cordero Garcia, Edson Antonio Batista, Cristiano Quevedo Andrea, Marcio Afonso Soleira Grassi 2019 IEEE 15th Brazilian Power Electronics Conference and 5th IEEE Southern Power Electronics Conference Cobep Spec 2019, 2019
Hybrid MPPT Algorithms for Photovoltaic Systems Leandro T. Omine, Moacyr A. G. de Brito, Joao O. P. Pinto, Raymundo C. Garcia 2018 IEEE 4th Southern Power Electronics Conference Spec 2018, 2018
