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Grid-Following Voltage Source Converter with a PLL-less PI Passivity-Based Controller for Unbalanced Grid Conditions
Sofía Avila-Becerril;Juan R. Rodríguez-Rodríguez;Alfredo Velazquez-Ibañez;Mario R. Arrieta-Paternina
IEEE Transactions on Power Electronics
Year: 2025 | Early Access Article |
Actual voltage-source converters (VSCs) advocate flexible and fast controls, low-voltage ripple levels at the DC-link, and grid compliances for operating under imbalanced grid conditions. To counteract these needs, this investigation focuses on proposing a straightforward passivity-inspired controller structure that facilitates the reference signals' generation to appropriately and quickly regulat...Show More
A Robust Sequential MPC With a Chattering Free Adaptive Sliding-Mode Speed Controller
Mahdi Bahmani;Armin Shabani;Davood Arab Khaburi;Jose Rodriguez
2025 16th Power Electronics, Drive Systems, and Technologies Conference (PEDSTC)
Year: 2025 | Conference Paper |
Model predictive torque control has gained much attention due to its fast response to torque changes. Nevertheless, finding the optimum weighting factor is a complex and time-consuming process. Sequential model predictive control (SMPC) with a hierarchical structure eliminates the need for a weighting factor. In conventional SMPC, a PI speed controller has been utilized to generate torque referenc...Show More
Voltage Control of Standalone Inverter-Interfaced Renewable Energy Resources Using an Adaptive Sliding Mode Control with Optimized PID Sliding Surface
Moslem Dehghani;Mokhtar Aly;Jose Rodriguez;Ebrahim Shojaeipor;Seyyed Mohammad Bornapour;Mohammad Mehdi Ghanbarian
2025 16th Power Electronics, Drive Systems, and Technologies Conference (PEDSTC)
Year: 2025 | Conference Paper |
In this paper, a robust adaptive Sliding Mode Controller (SMC) with an optimized Proportional-IntegralDerivative (PID) sliding surface has been proposed to control the voltage and frequency of standalone inverter-interfaced renewable energy resources. The suggested controller improves the tracking performance in order to tend the tracking error to zero, and also rejects the uncertainties and distu...Show More
A Modular and Reconfigurable Offboard Battery Charger using Model Predictive Control with Inherent Smooth Mode Transition Capability
IEEE Journal of Emerging and Selected Topics in Power Electronics
Year: 2025 | Early Access Article |
This article proposes a modular and reconfigurable offboard charger with enhanced performance over a wide output voltage range for charging existing and next-generation electric vehicles (EVs). The proposed charger utilizes power electronic building blocks (PEBBs), which are configured in either star or delta configurations based on battery voltage to optimize performance across diverse output vol...Show More
Applying Model-Free Predictive Current Control With Parallel Cost Functions for Open-End Winding Synchronous Reluctance Motor
Mahdi S. Mousavi;Behnam Nikmaram;Abolfazl Nassaji;S. Alireza Davari;Freddy Flores-Bahamonde;Jose Rodriguez
This article presents a model-free predictive current control (MFPCC) with parallel cost functions for the common dc-link dual-inverter-fed open-end winding synchronous reluctance motor (OW-SynRM). The MFPCC has a general prediction algorithm that can be implemented in any reference frame. Using this feature, and the fact that each winding of the OW-SynRM is supplied separately by two legs of the ...Show More
Novel Virtual Impedance Compensation Algorithm for Operation Stabilization of 3P4L3L PV-BES Microgrids With Constant Power Loads
Yi Zhu;Huiqing Wen;Yong Yang;Caifeng Wen;Jianliang Mao;Pan Wang;Yihua Hu;Cristian Garcia;Jose Rodriguez
A hybrid microgrid system that includes photovoltaic (PV) panels, battery energy storages (BESs), and constant power loads (CPLs) is presented in this article, where three-phase four-leg three-level (3P4L3L) is utilized as the main power interface. As the penetration of CPLs increases significantly, the operational stability of PV-BES Microgrids has become one of the most challenging issues. To ta...Show More
Model-Free Predictive Control of Five-Level T-Type Nested Neutral Point Clamped Converter
Catalina González-Castaño;Margarita Norambuena;Alex Navas-Fonseca;Freddy Flores-Bahamonde;Alireza Davari;Hector Young;Rasool Heydari;José Rodriguez
IEEE Journal of Emerging and Selected Topics in Power Electronics
Year: 2025 | Early Access Article |
Multilevel converters have been turned into a prominent solution for high-power, medium-voltage applications. However, controlling multilevel converters is a complex task, which is typically implemented through Single-Input Single-Output loops or via finite control set model predictive control (FCS-PC). Moreover, among the latest proposed multilevel converters, the five-level T-type nested neutral...Show More
Low Prediction Error Model-Free Predictive Control on PMSM Drives with Ordinary Kriging Time-Shift
Yao Wei;Hector Young;Shuyi Fang;Dongliang Ke;Haotian Xie;Fengxiang Wang;José Rodríguez
IEEE Transactions on Transportation Electrification
Year: 2025 | Early Access Article |
Model-free predictive control (MFPC) is developed to address the issue of the weak robustness in model predictive control (MPC) based on a physical model. In predictive control algorithms, the knowledge of future values of the reference is vital and this information is conventionally obtained using the Lagrange extrapolation algorithm. However, during implementation numerical errors introduced by ...Show More
Enhanced Fault Diagnosis in Rotating Machinery Using a Hybrid CWT-LeNet-5-LSTM Model: Performance Across Various Load Conditions
Muhammad Ahsan;Muhammad Waqar Hassan;Jose Rodriguez;Mohamed Abdelrahem
The presented research paper proposes a novel integrated technique combining LeNet-5 with Continuous Wavelet Transform (CWT) along with Long Short-Term Memory (LSTM). The purpose of this integration is to improve the performance of mechanisms used for the detection of defects in rotatory machines across various operating conditions. The Convolutional Neural Networks (CNN) assists the presented CWT...Show More
Enhanced Modulated Model Predictive Control for Matrix Converters in Overmodulation Zones
Ali Sarajian;Quanxue Guan;Ibrahim Harbi;Davood Arab Khaburi;Ralph Kennel;Cristian Garcia;Patrick Wheeler;Jose Rodriguez
Modulated Model Predictive Control (MMPC) techniques can be applied to enhance matrix converter (MC) performance in the linear modulation zone (LMZ). However, extending the converter operation in the overmodulation zone (OMZ) remains a problem. A key limitation of existing control methods in the OMZ is using the duty cycles calculated for the LMZ without considering the voltage or current referenc...Show More
Event-Driven Based Reinforcement Learning Predictive Controller Design for Three-Phase NPC Converters Using Online Approximators
Xing Liu;Lin Qiu;Youtong Fang;Kui Wang;Yongdong Li;Jose Rodríguez
This article is concerned with a two-step event-driven in reinforcement learning model-free predictive control problem leveraging online approximators for power converter systems, in which the limitations from system uncertainties and unnecessary switching loss are all addressed. To be specific, the key features of this technical note are: 1) a critic neural network to learn the performance functi...Show More
A Cross-Decoupled Current Harmonics Suppression Method for IPMSM Based on Notch Filter and Second-Order Generalized Integrator
Chao Du;Shuang Yang;Lin Qiu;Jien Ma;Youtong Fang;Jose Rodriguez
The second-order generalized integrator (SOGI) is widely applied for current harmonics suppression of interior permanent magnet synchronous motors (IPMSMs). However, SOGI is single-degree of freedom and exists a tradeoff issue between the dynamic convergence response and the stable convergence precision. Thus, the final performance of current harmonics suppression is influenced. In order to addres...Show More
Model Predictive Current Control of Six-Phase Switched Reluctance Motor With Enhanced Robustness Based on Improved Lehuy Model
Chao Sun;Xiaodong Sun;Cristian Garcia;Jose Rodriguez;Zebin Yang;Shouyi Han
This article proposes a model predictive current control (MPCC) with enhanced robustness for a six-phase switched reluctance motor (six-phase SRM) based on an improved Lehuy model (ILM). First, based on the six-phase SRM’s nonlinear characteristics and the conventional Lehuy model (CLM), a high-fidelity ILM is established, demonstrating its advantages in reducing modeling errors. Next, the MPCC fo...Show More
Tolerant Sequential Model Predictive Control Based on Lexicographic Optimization Method for T-Type Three-Phase Three-Level Inverters
Shengwei Chen;Yong Yang;Rong Chen;Jiefeng Hu;Huiqing Wen;Yiwang Wang;Weimin Wu;Gang Fang;Jose Rodriguez
Due to the existence of the neutral point (NP) voltage, controlling the three-level inverters has essentially become a multiobjective optimization problem (MOOP) that needs to provide stable output voltages for the load and maintain the NP voltage simultaneously. Traditionally, this MOOP is converted into a single-objective optimization problem by weighting factors. However, since the physical dim...Show More
Design Method for Polynomial Orders in ARX-Based Model-Free Predictive Controllers
Bryan Cartes;Patricio Burgos;Claudio A. Cifuentes;Hector Young;Yao Wei;Christian A. Rojas;Jose Rodriguez
Model-free (MF) strategies have emerged as a promising solution to challenges associated with modeling errors and uncertainties in predictive control (PC) systems. In this context, MF-PC schemes utilizing Auto-Regressive with eXogenous input (ARX) time-series models offer a flexible approach for online predictor construction using input-output data. However, the design of the polynomial orders wit...Show More
Design and Analysis of Predictive Inductor Current Control for PMSM Drives With LC Filter
Changming Zheng;Miao Xie;Xuanxuan Dong;Zheng Gong;Tomislav Dragičević;Jose Rodriguez
Permanent-magnet synchronous motor drives equipped with an LC filter offer an effective solution to motor-side overvoltage issues in long cable applications, but undesired resonances are also induced. This paper presents a predictive inductor current controller (PICC) to stabilize PMSM drives with an LC filter. A baseline PICC is first designed based on a continuous control set, which achieves exc...Show More
Combining Data-Driven and Event-Driven for Online Learning Predictive Control in Power Converters
Xing Liu;Lin Qiu;Youtong Fang;Kui Wang;Yongdong Li;Jose Rodríguez
The combination of data-driven and event-driven opens up the possibility of alleviating the long-standing research challenges for power converters in classical finite control-set model predictive control, i.e., model parametric uncertainties and unnecessary switching loss. Inspire by this, we will launch a major study on the problem of designing online learning predictive controller. Unlike most p...Show More
A Master-Slave Model Predictive Control Approach for Microgrids
Fernanda Carnielutti;Mokhtar Aly;Margarita Norambuena;Jiefeng Hu;Josep Guerrero;José Rodriguez
This article proposes a master-slave finite control set model predictive control (FCS-MPC) for microgrids. To demonstrate it, a microgrid is considered, composed of a master neutral-point clamped (NPC) inverter with a battery energy storage system (BESS) and output LC filter; two slave NPC inverters with photovoltaic (PV) panels and output LCL filters; RL and nonlinear loads. Two modes of operatio...Show More
Data-Enabled Finite State Predictive Control for Power Converters via Adaline Neural Network
Wenjie Wu;Lin Qiu;Xing Liu;Jien Ma;Jose Rodriguez;Youtong Fang
Finite control-set model predictive control (FCS-MPC) has been found as a promising alternative in the control of power converters and motor drives, albeit with model dependence issues. This inherent defect of the FCS-MPC controller triggered the widespread of model-free or data-driven control schemes in recent decades. This article, at hand, presents a data-enabled finite set predictive control s...Show More
FCS-MPC of Power Converters: An Event-Driven Brain Emotional Learning Approach
Xing Liu;Lin Qiu;Youtong Fang;Kui Wang;Yongdong Li;Jose Rodríguez
This study is concerned with an event-driven brain emotional online learning approach for finite control-set model predictive control (FCS-MPC) framework subject to system uncertainties and low switching frequency (SF). The developed framework consists of three key features: First, a bidirectional fuzzy brain emotional online learning approach along with a robustifying control term is leveraged to...Show More
Multiple-Voltage-Vector Model-Free Predictive Deadbeat Control With Updated Reference Voltage Vector for PMSM Drive
Xiangcheng Li;Yong Yang;Jun Sun;Yang Xiao;Mingdi Fan;Kai Ni;Jiefeng Hu;Huiqing Wen;Hui Yang;Jose Rodriguez
Model predictive control (MPC) has been extensively investigated for its impressive dynamic response and efficacy in controlling non-linear systems. However, MPC faces challenges in terms of robustness, primarily due to its dependency on system parameters. In contrast, model-free predictive control (MFPC) offers an alternative that relies on the inputs and outputs of the system without applying sy...Show More
Large-Signal Stability for DAB Converters Feeding Constant Power Load Based on State Trajectory Analysis
Peichao Xu;Huiqing Wen;Qinglei Bu;Lanbo Dai;Yi Zhu;Shahamat Shahzad Khan;Haochen Shi;Jiafeng Zhou;Jieming Ma;Yihua Hu;Jose Rodriguez
Different from resistive loads, constant power loads (CPLs) may threaten the stability of power interfaces (PIs) due to the negative incremental impedance. As one of the promising PIs, dual active bridge (DAB) converters have received widespread attention. However, the large-signal stability criteria of DAB converters under CPLs remain challenging. To fill this gap, this article thoroughly explore...Show More
Predefined-Time Sliding Mode Predictive Current Control for Disturbance Suppression and Dynamic Response Improvement in SPMSM Drives
Long He;Fengxiang Wang;Wei Tian;José Rodríguez;Marcelo Lobo Heldwein
This article proposes a novel predefined-time sliding mode predictive current control (PDO-SMPCC+HDO) technique to simultaneously enhance disturbance rejection and dynamic response in surface-mounted permanent magnet synchronous motor (SPMSM) drives. Specifically, a composite disturbance predictive model incorporating both slowly varying disturbance and sixth current harmonic disturbance is develo...Show More
Sensorless FCS-MPCC PMSM Drives With Improved Sliding Mode Observer and Low-Complexity Discrete Vector Selection – An Assessment
Mingxing Gu;Yong Yang;Yang Xiao;Mingdi Fan;Yiwang Wang;Huiqing Wen;Chee Shen Lim;Hui Yang;Jose Rodriguez
This paper proposes a virtual voltage vector-based finite-control-set model predictive control (FCS-MPCC) for a sensorless permanent magnet synchronous motor (PMSM) drive. First, an adaptive sliding-mode back electromotive force observer is integrated to improve the observer accuracy, especially in terms of rotor field speed and position. Then, a simple virtual voltage vector selection algorithm i...Show More
Universal Integrated Onboard Charger With Model Predictive Current Control for Plug-In EV Charging
This letter proposes a new universal integrated onboard charger (IOBC) to achieve a wide output voltage range ranging from 48–450 V for plug-in electric vehicle battery charging applications without employing additional power conversion stages. In addition, a model predictive current control (MPCC) is proposed to accomplish boost and buck operation with inherent seamless mode transitions. The prop...Show More
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