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The smart-grid has requirements of flexible automation, efficiency, reliability, resiliency and scalability. These are necessitated by the increasing penetration of power-electronics converters that interface distributed renewable energy systems which energize the fast-evolving electric power network. Microgrids (MGs) have been identified as modular grids with the potential to effectively satisfy these characteristics when enhanced with advanced control capabilities. Model predictive control (MPC) facilitates the multivariable control of power electronic systems while accommodating physical constraints without the necessity for a cascaded structure. These features result in fast control dynamic response and good performance for systems involving non-linearities. This paper is a survey of the recent advances in MPC-based converters in MGs. Schemes for the primary control of MG parameters are presented. We also present opportunities for the MPC converter control of autonomous MGs (power quality and inertia enhancement), and transportation electrification. Finally, we demonstrate MPC’s capabilities through hardware-in-the-loop (HiL) results for a proposed adaptive MPC scheme for grid-forming converters.
Zhenbin Zhang; Oluleke Babayomi; Tomislav Dragicevic; Rasool Heydari; Cristian Garcia; Jose Rodriguez; Ralph Kennel. Advances and opportunities in the model predictive control of microgrids: Part I–Primary layer. International Journal of Electrical Power & Energy Systems 2021, 134, 107339 .
AMA StyleZhenbin Zhang, Oluleke Babayomi, Tomislav Dragicevic, Rasool Heydari, Cristian Garcia, Jose Rodriguez, Ralph Kennel. Advances and opportunities in the model predictive control of microgrids: Part I–Primary layer. International Journal of Electrical Power & Energy Systems. 2021; 134 ():107339.
Chicago/Turabian StyleZhenbin Zhang; Oluleke Babayomi; Tomislav Dragicevic; Rasool Heydari; Cristian Garcia; Jose Rodriguez; Ralph Kennel. 2021. "Advances and opportunities in the model predictive control of microgrids: Part I–Primary layer." International Journal of Electrical Power & Energy Systems 134, no. : 107339.
The smart-grid has requirements of flexible automation, efficiency, reliability, resiliency and scalability. These are necessitated by the increasing penetration of power-electronics converters that interface distributed renewable energy systems which energize the fast-evolving electric power network. Microgrids (MGs) have been identified as modular grids with the potential to effectively satisfy these characteristics when enhanced with advanced control capabilities. Model predictive control (MPC) facilitates the multivariable control of power electronic systems while accommodating physical constraints without the necessity for a cascaded structure. These features result in fast control dynamic response and good performance for systems involving non-linearities. This paper is a survey of the recent advances in MPC-based converters in MGs. Schemes for the primary control of MG parameters are presented. We also present opportunities for the MPC converter control of autonomous MGs (power quality and inertia enhancement), and transportation electrification. Finally, we demonstrate MPC’s capabilities through hardware-in-the-loop (HiL) results for a proposed adaptive MPC scheme for grid-forming converters.
Zhenbin Zhang; Oluleke Babayomi; Tomislav Dragicevic; Rasool Heydari; Cristian Garcia; Jose Rodriguez; Ralph Kennel. Advances and opportunities in the model predictive control of microgrids: Part I–primary layer. International Journal of Electrical Power & Energy Systems 2021, 134, 107411 .
AMA StyleZhenbin Zhang, Oluleke Babayomi, Tomislav Dragicevic, Rasool Heydari, Cristian Garcia, Jose Rodriguez, Ralph Kennel. Advances and opportunities in the model predictive control of microgrids: Part I–primary layer. International Journal of Electrical Power & Energy Systems. 2021; 134 ():107411.
Chicago/Turabian StyleZhenbin Zhang; Oluleke Babayomi; Tomislav Dragicevic; Rasool Heydari; Cristian Garcia; Jose Rodriguez; Ralph Kennel. 2021. "Advances and opportunities in the model predictive control of microgrids: Part I–primary layer." International Journal of Electrical Power & Energy Systems 134, no. : 107411.
Model predictive control (MPC) is a flexible and multivariable control technique with better dynamic performance than linear control. However, MPC is sensitive to parametric mismatches that reduce its control capabilities. In this paper, we present a new method of improving the robustness of MPC to filter parameter variations/mismatches by easily implementable parameter estimation. Furthermore, we extend the proposed technique for wider operating conditions by novel neuro-fuzzy estimation. The results, which are demonstrated by both simulations and real-time hardware-in-the-loop tests, show a steady-state parameter estimation accuracy of 95%, and at least 20% improvement in total harmonic distortion (THD) than conventional non-adaptive MPC under parameter mismatches up to 50% of the nominal values.
Oluleke Babayomi; Zhenbin Zhang; Yu Li; Ralph Kennel. Adaptive Predictive Control with Neuro-Fuzzy Parameter Estimation for Microgrid Grid-Forming Converters. Sustainability 2021, 13, 7038 .
AMA StyleOluleke Babayomi, Zhenbin Zhang, Yu Li, Ralph Kennel. Adaptive Predictive Control with Neuro-Fuzzy Parameter Estimation for Microgrid Grid-Forming Converters. Sustainability. 2021; 13 (13):7038.
Chicago/Turabian StyleOluleke Babayomi; Zhenbin Zhang; Yu Li; Ralph Kennel. 2021. "Adaptive Predictive Control with Neuro-Fuzzy Parameter Estimation for Microgrid Grid-Forming Converters." Sustainability 13, no. 13: 7038.
This paper investigates the combination of twomodel predictive control concepts, sequential model predictivecontrol and long-horizon model predictive control for powerelectronics. To achieve sequential model predictive control, theoptimization problem is split into two subproblems: The first onesummarizes all control goals which linearly depend on the systeminputs. Sequential model predictive control generally requires toobtain more than one solution for the first subproblem. Due tothe mixed-integer nature of finite control set model predictivecontrol power electronics a special sphere decoder is thereforeproposed within the paper. The second subproblem consists ofall those control goals which depend nonlinearly on the systeminputs and is solved by an exhaustive search. The effectivenessof the proposed method is validated via numerical simulationsat different scenarios on a three-level neutral point clampedpermanent magnet synchronous generator wind turbine systemand compared to other long-horizon model predictive controlmethods.
Ferdinand Grimm; Pouya Kolahian; Zhenbin Zhang; Mehdi Baghdadi. A Sphere Decoding Algorithm for Multistep Sequential Model-Predictive Control. IEEE Transactions on Industry Applications 2021, 57, 2931 -2940.
AMA StyleFerdinand Grimm, Pouya Kolahian, Zhenbin Zhang, Mehdi Baghdadi. A Sphere Decoding Algorithm for Multistep Sequential Model-Predictive Control. IEEE Transactions on Industry Applications. 2021; 57 (3):2931-2940.
Chicago/Turabian StyleFerdinand Grimm; Pouya Kolahian; Zhenbin Zhang; Mehdi Baghdadi. 2021. "A Sphere Decoding Algorithm for Multistep Sequential Model-Predictive Control." IEEE Transactions on Industry Applications 57, no. 3: 2931-2940.
Model-based predictive control that highly depends on system parameters has been widely investigated. In contrast, model-free predictive current control (MFPCC) can be performed based on input or output measured data, rather than on any system model information. In such a strategy, the current gradients due to each of the possible voltage vectors are stored and used to predict future currents. Current gradient knowledge therefore provides a significant foundation for MFPCC. In conventional MFPCC, however, the stagnation existing in the current gradient update always impacts the reliability of current gradients and further worsens the control performance. In this paper, an improved MFPCC with an advanced current gradient updating mechanism is proposed. In the proposed strategy, to guarantee the reliability of the current gradients, two contiguous measured current gradients due to the applied voltage vectors are used to estimate the current gradients for all the possible voltage vectors. This simple method takes advantage of the mathematical relationships between the voltage vectors. In this way, all the current gradients can be obtained within one control period, effectively reducing the stagnation effect in conventional MFPCC. The proposed MFPCC scheme is evaluated on a permanent magnet synchronous machine (PMSM) drive setup to demonstrate its effectiveness
Chenwei Ma; Huayu Li; Xuliang Yao; Zhenbin Zhang; Frederik De Belie. An Improved Model-Free Predictive Current Control with Advanced Current Gradient Updating Mechanism. IEEE Transactions on Industrial Electronics 2020, PP, 1 -1.
AMA StyleChenwei Ma, Huayu Li, Xuliang Yao, Zhenbin Zhang, Frederik De Belie. An Improved Model-Free Predictive Current Control with Advanced Current Gradient Updating Mechanism. IEEE Transactions on Industrial Electronics. 2020; PP (99):1-1.
Chicago/Turabian StyleChenwei Ma; Huayu Li; Xuliang Yao; Zhenbin Zhang; Frederik De Belie. 2020. "An Improved Model-Free Predictive Current Control with Advanced Current Gradient Updating Mechanism." IEEE Transactions on Industrial Electronics PP, no. 99: 1-1.
In this work, we propose a high-quality control solution for islanded microgrids with multi-parallel power converters; it uses a full state-variable direct model predictive control (FSV-DMPC) and has a simple structure. Unlike the conventional cascaded control loops, the proposed FSV-DMPC solution tracks the optimal reference generated by a robust droop loop using a unified cost function. This proposal enables the FSV-DMPC to be inserted into the entire control framework with plug-and-play capability; it is robust to parameter variations, while also guaranteeing dynamics and stability. We conduct a deep analysis of the proposed approach, taking into account both the characteristics of the solution and the bounded stability of the system. Through comprehensive comparative studies with a classical double-loop linear controller, we validate that our solution achieves superior output voltage regulation during the load transients in terms of voltage error and settling time. Meanwhile, similar steady-state performances are accomplished for both methods. Finally, we verify our approach experimentally in different scenarios through a lab-constructed microgrid test-bench. Experimental data confirm that the proposed approach achieves excellent steady-state and transient performances, and obtains accurate load sharing.
Yu Li; Zhenbin Zhang; Cungang Hu; Mohamed Abdelrahem; Ralph Kennel; Jose Rodriguez. A Full State-Variable Direct Predictive Control for Islanded Microgrids With Parallel Converters. IEEE Journal of Emerging and Selected Topics in Power Electronics 2020, 9, 4615 -4628.
AMA StyleYu Li, Zhenbin Zhang, Cungang Hu, Mohamed Abdelrahem, Ralph Kennel, Jose Rodriguez. A Full State-Variable Direct Predictive Control for Islanded Microgrids With Parallel Converters. IEEE Journal of Emerging and Selected Topics in Power Electronics. 2020; 9 (4):4615-4628.
Chicago/Turabian StyleYu Li; Zhenbin Zhang; Cungang Hu; Mohamed Abdelrahem; Ralph Kennel; Jose Rodriguez. 2020. "A Full State-Variable Direct Predictive Control for Islanded Microgrids With Parallel Converters." IEEE Journal of Emerging and Selected Topics in Power Electronics 9, no. 4: 4615-4628.
In this work, we propose an effective and simple control approach for islanded DC microgrids that allows each distributed generator (DG) to achieve accurate voltage regulation and power-sharing. An improved dynamic consensus protocol, which is robust to measurement noise and states initialization, is employed to enable each agent to locally calculate the average bus voltage with a sparse cyber network. On this basis, we propose a cooperative controller that merges the voltage regulation and power-sharing objectives in a unified fashion. The proposed approach only uses neighbors’ voltage information to regulates the average bus voltage to its nominal value while maintaining proportional power-sharing or optimal power dispatch. This significantly simplifies its implementation and reduces the communication bandwidth requirement. A global model of the DC microgrid considering the cyber network is established in the form of a state-space-model, where the reference voltage vector corresponds to the input and the average bus voltage vector denotes the state. Then, the input-to-state stability analysis is carried out. To the end, comprehensive hardware-in-the-loop (HiL) tests are conducted to validate the effectiveness of the proposed control strategy. The proposed control strategy exhibits plug-and-play capability, and it is resilient to message update rate and communication failure.
Yu Li; Zhenbin Zhang; Tomislav Dragicevic; Jose Rodriguez. A Unified Distributed Cooperative Control of DC Microgrids Using Consensus Protocol. IEEE Transactions on Smart Grid 2020, 12, 1880 -1892.
AMA StyleYu Li, Zhenbin Zhang, Tomislav Dragicevic, Jose Rodriguez. A Unified Distributed Cooperative Control of DC Microgrids Using Consensus Protocol. IEEE Transactions on Smart Grid. 2020; 12 (3):1880-1892.
Chicago/Turabian StyleYu Li; Zhenbin Zhang; Tomislav Dragicevic; Jose Rodriguez. 2020. "A Unified Distributed Cooperative Control of DC Microgrids Using Consensus Protocol." IEEE Transactions on Smart Grid 12, no. 3: 1880-1892.
Single-inductor multiple-input multiple-output (SIMIMO) dc-dc converters can integrate different input sources and supply power to multiple output loads with fewer components. This paper proposed a current-source-mode (CSM) SIMIMO dc-dc converter. By virtue of the constant inductor current, the proposed CSM SIMIMO dc-dc converter can avoid cross regulation naturally and allow the use of much simpler control strategy. The proposed configuration has the advantage of all inputs and outputs sharing a common ground and ease of expansion. Moreover, the number of the main circuit components is reduced. A CSM single-inductor dual-input dual-output (SIDIDO) dc-dc converter is constructed for illlustration. The two input sources can work independently in the event of the two input sources being disconnected. A detailed comparison of the different SIDIDO dc-dc converters is provided.
Zheng Dong; Zhen Li; Xiaolu Lucia Li; Chi K. Tse; Zhenbin Zhang. Single-Inductor Multiple-Input Multiple-Output Converter With Common Ground, High Scalability, and No Cross-Regulation. IEEE Transactions on Power Electronics 2020, 36, 6750 -6760.
AMA StyleZheng Dong, Zhen Li, Xiaolu Lucia Li, Chi K. Tse, Zhenbin Zhang. Single-Inductor Multiple-Input Multiple-Output Converter With Common Ground, High Scalability, and No Cross-Regulation. IEEE Transactions on Power Electronics. 2020; 36 (6):6750-6760.
Chicago/Turabian StyleZheng Dong; Zhen Li; Xiaolu Lucia Li; Chi K. Tse; Zhenbin Zhang. 2020. "Single-Inductor Multiple-Input Multiple-Output Converter With Common Ground, High Scalability, and No Cross-Regulation." IEEE Transactions on Power Electronics 36, no. 6: 6750-6760.
Voltage source inverters with output LC filter enable a sinusoidal output voltage with low harmonics, thus suitable for islanded ac microgrid or uninterruptible power supply applications. Conventional finite-set model predictive voltage control applies only a single switching vector per control period, leading to a variable switching frequency and significant output ripple. This paper resolves these issues by proposing an improved model predictive voltage control with optimal switching sequence (OSS-MPVC). First, an improved vector switching sequence is defined, aiming to reduce the output-voltage ripple with a constant switching frequency. Then, to tackle the difficulty in extending the OSS to high-order systems due to the coupling effect of the output filter, a generalized ‘one-step estimation’ solution is proposed, which directly associates the control-variable gradients with the vector switching sequence. To further enhance the output-voltage tracking accuracy, inter-sample dynamics are taken into account in the cost function. The control delay and dead-time compensation are also considered. Simulations and experimental results verify the feasibility of the proposed method.
Changming Zheng; Tomislav Dragicevic; Zhenbin Zhang; Jose Rodriguez; Frede Blaabjerg. Model Predictive Control of LC-Filtered Voltage Source Inverters With Optimal Switching Sequence. IEEE Transactions on Power Electronics 2020, 36, 3422 -3436.
AMA StyleChangming Zheng, Tomislav Dragicevic, Zhenbin Zhang, Jose Rodriguez, Frede Blaabjerg. Model Predictive Control of LC-Filtered Voltage Source Inverters With Optimal Switching Sequence. IEEE Transactions on Power Electronics. 2020; 36 (3):3422-3436.
Chicago/Turabian StyleChangming Zheng; Tomislav Dragicevic; Zhenbin Zhang; Jose Rodriguez; Frede Blaabjerg. 2020. "Model Predictive Control of LC-Filtered Voltage Source Inverters With Optimal Switching Sequence." IEEE Transactions on Power Electronics 36, no. 3: 3422-3436.
In the medium-voltage AC/DC distribution networks with distributed renewable sources on islands, a multi-port receiver is the key factor for hybrid power conversion. However, the most used modular multilevel converter (MMC)-based multi-port converters (MCs) face the coordination and complexity challenges due to their double-stage control system and voltage-balancing control of capacitors. In particular, the control system is more unstable and complicated when the control of circulating currents is considered. In this paper, an isolated modular multilevel converter (I-MMC) is used as a receiver, and a unified coordinated control scheme based on the multiple modulation freedoms is proposed. Due to the voltage clamping of high-frequency transformers, there is no concern of the capacitors’ voltage-balancing control. Based on the proposed single-stage control system, the unified coordinated control scheme solves the coordination problem of the MMC-based MCs. The multiple modulation freedoms corresponding to an AC port, two DC ports, and three-phase circulating currents can independently control respective targets. The control structure is simplified, while the control freedoms are ensured. Experimental results confirming the performance of the designed control system is shown.
Chuang Liu; Dehao Kong; Zhenbin Zhang; Zhongchen Pei; Ralph Kennel. Single-Stage Control System of I-MMC-Based Island MVDC Link Receiver With Multiple Modulation Freedoms. IEEE Access 2020, 8, 10088 -10097.
AMA StyleChuang Liu, Dehao Kong, Zhenbin Zhang, Zhongchen Pei, Ralph Kennel. Single-Stage Control System of I-MMC-Based Island MVDC Link Receiver With Multiple Modulation Freedoms. IEEE Access. 2020; 8 (99):10088-10097.
Chicago/Turabian StyleChuang Liu; Dehao Kong; Zhenbin Zhang; Zhongchen Pei; Ralph Kennel. 2020. "Single-Stage Control System of I-MMC-Based Island MVDC Link Receiver With Multiple Modulation Freedoms." IEEE Access 8, no. 99: 10088-10097.
Xiaonan Gao; Mohamed Abdelrahem; Christoph M. Hackl; Zhenbin Zhang; Ralph Kennel. Direct Predictive Speed Control With a Sliding Manifold Term for PMSM Drives. IEEE Journal of Emerging and Selected Topics in Power Electronics 2019, 8, 1258 -1267.
AMA StyleXiaonan Gao, Mohamed Abdelrahem, Christoph M. Hackl, Zhenbin Zhang, Ralph Kennel. Direct Predictive Speed Control With a Sliding Manifold Term for PMSM Drives. IEEE Journal of Emerging and Selected Topics in Power Electronics. 2019; 8 (2):1258-1267.
Chicago/Turabian StyleXiaonan Gao; Mohamed Abdelrahem; Christoph M. Hackl; Zhenbin Zhang; Ralph Kennel. 2019. "Direct Predictive Speed Control With a Sliding Manifold Term for PMSM Drives." IEEE Journal of Emerging and Selected Topics in Power Electronics 8, no. 2: 1258-1267.
This paper introduces the high-frequency link (HFL) concept into the modular multilevel converter (MMC) topology, which can totally reduce the individual DC-link capacitors at the high-voltage (HV) side. The proposed converter, called isolated modular multilevel converter (I-M2C), has basic triple ports of medium-voltage AC (MVAC), medium-voltage DC (MVDC), and low-voltage DC (LVDC). Thus, it is especially suitable for hybrid DC and AC applications in power generation and transmission, such as Solid-State Transformer (SST), etc. The fundamental principle and applied Phase-Shift Pulse Width Modulation (PSPWM) control scheme are presented in detail. And the design of the clamping circuit and analysis of duty loss are carried out. The experimental results are given to illustrate the efficient operation characteristics.
Chuang Liu; Chao Liu; Guowei Cai; Hong Ying; Zhenbin Zhang; Renzhong Shan; Zhongchen Pei; Xiaomin Song. An Isolated Modular Multilevel Converter (I-M2C) Topology Based on High-Frequency Link (HFL) Concept. IEEE Transactions on Power Electronics 2019, 35, 1576 -1588.
AMA StyleChuang Liu, Chao Liu, Guowei Cai, Hong Ying, Zhenbin Zhang, Renzhong Shan, Zhongchen Pei, Xiaomin Song. An Isolated Modular Multilevel Converter (I-M2C) Topology Based on High-Frequency Link (HFL) Concept. IEEE Transactions on Power Electronics. 2019; 35 (2):1576-1588.
Chicago/Turabian StyleChuang Liu; Chao Liu; Guowei Cai; Hong Ying; Zhenbin Zhang; Renzhong Shan; Zhongchen Pei; Xiaomin Song. 2019. "An Isolated Modular Multilevel Converter (I-M2C) Topology Based on High-Frequency Link (HFL) Concept." IEEE Transactions on Power Electronics 35, no. 2: 1576-1588.
Finite set model predictive torque control (FCSMPTC) of induction machines has received widespread attention in recent years due to its fast dynamic response, intuitive concept, and ability to handle nonlinear constraints. However, FCSMPTC essentially belongs to the open-loop control paradigm, and unmatched parameters inevitably cause electromagnetic torque tracking error. In addition, the outer loop (i.e., the speed loop) based on a proportional-integral (PI) regulator cannot achieve optimal control between speed dynamic response and torque tracking error compensation. The traditional control paradigm is abbreviated as PI-MPTC. In order to solve the aforementioned problem, this paper proposes active disturbance rejection-based model predictive torque control (ADR-MPTC). Firstly, the influence mechanism of mismatched parameters on torque prediction error in PI-MPTC is studied, and then the performance of a traditional PI regulator used to compensate for torque prediction error is analyzed. Secondly, this paper introduces several parts of the proposed ADR-MPTC, including the design of the torque prediction error observer, nonlinear prediction error compensation strategies, an enhanced predictive torque control, and a simplified full order flux observer. Finally, PI-MPTC and ADR-MPTC are studied experimentally. The experimental results show that compared with PI-MPTC, ADRMPTC performs better in dynamic and steady states, and has stronger robustness.
Liming Yan; Fengxiang Wang; Manfeng Dou; Zhenbin Zhang; Ralph Kennel; Jose Rodriguez. Active Disturbance-Rejection-Based Speed Control in Model Predictive Control for Induction Machines. IEEE Transactions on Industrial Electronics 2019, 67, 2574 -2584.
AMA StyleLiming Yan, Fengxiang Wang, Manfeng Dou, Zhenbin Zhang, Ralph Kennel, Jose Rodriguez. Active Disturbance-Rejection-Based Speed Control in Model Predictive Control for Induction Machines. IEEE Transactions on Industrial Electronics. 2019; 67 (4):2574-2584.
Chicago/Turabian StyleLiming Yan; Fengxiang Wang; Manfeng Dou; Zhenbin Zhang; Ralph Kennel; Jose Rodriguez. 2019. "Active Disturbance-Rejection-Based Speed Control in Model Predictive Control for Induction Machines." IEEE Transactions on Industrial Electronics 67, no. 4: 2574-2584.
In this study, direct speed control based on a finite control set-model predictive speed control (FCS-MPSC)with a voltage smoother is presented to reduce current ripple. In the proposed control scheme, the controller predicts the future current and speed states with a finite set of smoothed voltages and outputs the optimal smoothed voltage by using pulse width modulation (PWM). Because of this control scheme, a sudden change in the output voltage, which causes a large current ripple, is avoided. The simulated and experimental results obtained with a permanent magnet synchronous motor (PMSM), fed by a 2-level 3-phase inverter., shows that the proposed method effectively reduces the current ripple as compared with a standard FCS-MPSC.
Hiroaki Kawai; Zhenbin Zhang; Ralph Kennel. Finite Control Set-Model Predictive Speed Control with a Voltage Smoother. IECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society 2018, 528 -533.
AMA StyleHiroaki Kawai, Zhenbin Zhang, Ralph Kennel. Finite Control Set-Model Predictive Speed Control with a Voltage Smoother. IECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society. 2018; ():528-533.
Chicago/Turabian StyleHiroaki Kawai; Zhenbin Zhang; Ralph Kennel. 2018. "Finite Control Set-Model Predictive Speed Control with a Voltage Smoother." IECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society , no. : 528-533.
This paper presents a new and very simple strategy for torque and flux control of AC machines. The method is based on Model Predictive Control and uses one cost function for the torque and a separate cost function for the flux. This strategy introduces a drastic simplification, achieving a very fast dynamic behavior in the controlled machines. Experimental results obtained with an induction machine confirm the drive's very good performance.
Margarita Norambuena Gae; Jose Rodriguez; Zhenbin Zhang; Fengxiang Wang; Cristian Garcia; Ralph Kennel. A Very Simple Strategy for High-Quality Performance of AC Machines Using Model Predictive Control. IEEE Transactions on Power Electronics 2018, 34, 794 -800.
AMA StyleMargarita Norambuena Gae, Jose Rodriguez, Zhenbin Zhang, Fengxiang Wang, Cristian Garcia, Ralph Kennel. A Very Simple Strategy for High-Quality Performance of AC Machines Using Model Predictive Control. IEEE Transactions on Power Electronics. 2018; 34 (1):794-800.
Chicago/Turabian StyleMargarita Norambuena Gae; Jose Rodriguez; Zhenbin Zhang; Fengxiang Wang; Cristian Garcia; Ralph Kennel. 2018. "A Very Simple Strategy for High-Quality Performance of AC Machines Using Model Predictive Control." IEEE Transactions on Power Electronics 34, no. 1: 794-800.
A direct-drive permanent magnet synchronous generator (PMSG) with a three-level neutral-point-clamped back-to-back power converter is an attractive configuration for high-power wind energy conversion systems. For such a topology, finite-control-set model-predictive control (FCS-MPC) has emerged as a promising alternative. However, due to its fully model-based concept, variation of system parameters (in particular, the stator and grid filter inductance and rotor permanent-flux linkage) will (seriously) affect the system control performances when using the classical FCS-MPC. In this work, a robust FCS-MPC method with revised predictions is proposed and validated for such a system. With the proposed solution, not only the system robustness against parameter variations is improved, but also the control variable ripples are evidently reduced. The proposed method has been implemented with a fully field-programmable-gate-array-based real-time hardware. Its performance improvements in comparison with the conventional solutions are validated with experimental data.
Zhenbin Zhang; Zhen Li; Marian P. Kazmierkowski; Jose Rodriguez; Ralph Kennel. Robust Predictive Control of Three-Level NPC Back-to-Back Power Converter PMSG Wind Turbine Systems With Revised Predictions. IEEE Transactions on Power Electronics 2018, 33, 9588 -9598.
AMA StyleZhenbin Zhang, Zhen Li, Marian P. Kazmierkowski, Jose Rodriguez, Ralph Kennel. Robust Predictive Control of Three-Level NPC Back-to-Back Power Converter PMSG Wind Turbine Systems With Revised Predictions. IEEE Transactions on Power Electronics. 2018; 33 (11):9588-9598.
Chicago/Turabian StyleZhenbin Zhang; Zhen Li; Marian P. Kazmierkowski; Jose Rodriguez; Ralph Kennel. 2018. "Robust Predictive Control of Three-Level NPC Back-to-Back Power Converter PMSG Wind Turbine Systems With Revised Predictions." IEEE Transactions on Power Electronics 33, no. 11: 9588-9598.
Field oriented control (FOC), direct torque control (DTC) and finite set model predictive control (FS-MPC) are different strategies for high performance electrical drive systems. FOC uses linear controllers and pulse width modulation (PWM) to control the fundamental components of the load voltages. On the other hand, DTC and FS-MPC are nonlinear strategies that generate directly the voltage vectors in the absence of a modulator. This paper presents all three methods starting from theoretic operating principles, control structures and implementation. Experimental assessment is performed to discuss their advantages and limitations in detail. As main conclusions of this work, it is affirmed that different strategies have their own merits and all meet the requirements of modern high performance drives.
Fengxiang Wang; Zhenbin Zhang; Xuezhu Mei; José Rodríguez; Ralph Kennel. Advanced Control Strategies of Induction Machine: Field Oriented Control, Direct Torque Control and Model Predictive Control. Energies 2018, 11, 120 .
AMA StyleFengxiang Wang, Zhenbin Zhang, Xuezhu Mei, José Rodríguez, Ralph Kennel. Advanced Control Strategies of Induction Machine: Field Oriented Control, Direct Torque Control and Model Predictive Control. Energies. 2018; 11 (1):120.
Chicago/Turabian StyleFengxiang Wang; Zhenbin Zhang; Xuezhu Mei; José Rodríguez; Ralph Kennel. 2018. "Advanced Control Strategies of Induction Machine: Field Oriented Control, Direct Torque Control and Model Predictive Control." Energies 11, no. 1: 120.
In this paper, a general optimum control for power converters and drives is proposed. The proposed optimum control will select an optimum voltage vector from the whole hexagonal plane, leading to the best control performance fulfilling a predefined performance index. With the proposed concept, two subsolutions, i.e., both continuous and discrete solutions, are derived and unified in the frame of optimum control. The continuous solution utilizes the averaged continuous-time model of the system and is capable of dealing with multiple system constraints, showing good performance with less calculation efforts, while the discrete solution takes the finite set of the power converter switching vectors into consideration and the state transition of the system can be predicted with a chosen vector. Both methods require less calculation efforts compared with the well-known finite-control-set model predictive control method, which makes it very suitable for practical realizations. Finally, as a case of study, the proposed concept is tested at a current-controlled 3-kW surface-mounted permanent magnet synchronous motor drive under different scenarios. The experimental results validate the effectiveness of both solutions.
Xinbo Cai; Zhenbin Zhang; Junxiao Wang; Ralph Kennel. Optimal Control Solutions for PMSM Drives: A Comparison Study With Experimental Assessments. IEEE Journal of Emerging and Selected Topics in Power Electronics 2017, 6, 352 -362.
AMA StyleXinbo Cai, Zhenbin Zhang, Junxiao Wang, Ralph Kennel. Optimal Control Solutions for PMSM Drives: A Comparison Study With Experimental Assessments. IEEE Journal of Emerging and Selected Topics in Power Electronics. 2017; 6 (1):352-362.
Chicago/Turabian StyleXinbo Cai; Zhenbin Zhang; Junxiao Wang; Ralph Kennel. 2017. "Optimal Control Solutions for PMSM Drives: A Comparison Study With Experimental Assessments." IEEE Journal of Emerging and Selected Topics in Power Electronics 6, no. 1: 352-362.
Predictive current control is described for an Induction Machine in this paper. Instead of the cascaded PI control systems, the proposed system directly generates switching vectors by evaluating the designed cost function, which reduces the tuning parameters. An observer is applied for the sensorless system, whcih has the merit of low cost. The system is verified by experimental results.
Fengxiang Wang; Xuezhu Mei; Zhenbin Zhang. Sensorless predictive control for an induction machine. 2016 IEEE International Conference on Information and Automation (ICIA) 2016, 1320 -1324.
AMA StyleFengxiang Wang, Xuezhu Mei, Zhenbin Zhang. Sensorless predictive control for an induction machine. 2016 IEEE International Conference on Information and Automation (ICIA). 2016; ():1320-1324.
Chicago/Turabian StyleFengxiang Wang; Xuezhu Mei; Zhenbin Zhang. 2016. "Sensorless predictive control for an induction machine." 2016 IEEE International Conference on Information and Automation (ICIA) , no. : 1320-1324.