scholarly journals Predictive-Fixed Switching Current Control Strategy Applied to Six-Phase Induction Machine

Energies ◽  
2019 ◽  
Vol 12 (12) ◽  
pp. 2294 ◽  
Author(s):  
Osvaldo Gonzalez ◽  
Magno Ayala ◽  
Jesus Doval-Gandoy ◽  
Jorge Rodas ◽  
Raul Gregor ◽  
...  
Keyword(s):  
Predictive Control ◽  
Control Strategy ◽  
Control Strategies ◽  
High Harmonic ◽  
Induction Machine ◽  
Experimental Tests ◽  
Sampling Period ◽  
Current Control ◽  
Switching Frequency ◽  
Multiphase Motor

In applications such as multiphase motor drives, classical predictive control strategies are characterized by a variable switching frequency which adds high harmonic content and ripple in the stator currents. This paper proposes a model predictive current control adding a modulation stage based on a switching pattern with the aim of generating a fixed switching frequency. Hence, the proposed controller takes into account the prediction of the two adjacent active vectors and null vector in the ( α - β ) frame defined by space vector modulation in order to reduce the (x-y) currents according to a defined cost function at each sampling period. Both simulation and experimental tests for a six-phase induction motor drive are provided and compared to the classical predictive control to validate the feasibility of the proposed control strategy.

Field oriented predictive control strategy for induction machine drives

2017 ◽  
Vol 37 (1) ◽  
pp. 103-113 ◽  
Author(s):  
Xin Qi ◽  
Lin Wu ◽  
Xiaomin Zhou ◽  
Xianghua Ma
Keyword(s):  
Predictive Control ◽  
Control Strategy ◽  
Induction Machine ◽  
Sampling Frequency ◽  
Current Control ◽  
Switching Frequency ◽  
Frequency Noise ◽  
Boundary Circle ◽  
Content Type ◽  
Simulation Step

Purpose This study aims to drive the induction machine system with a low switching frequency. Design/methodology/approach An unconventional inverter control strategy – field-oriented predictive control (FOPC) – is presented. The strategy limits current distortion by setting a boundary circle. The voltage vector, which could keep current trajectories in boundary, is selected to obtain a low switching frequency. Findings A dual simulation step technique is developed to investigate the influence of sampling frequency on current distortion control and switching frequency. Current control distortion can be improved, i.e. reduced, by increasing the sampling frequency; however, the switching frequency will also increase. Such a law is discovered by the dual simulation step technique and finally verified by experiments. Originality/value A new predictive control method, FOPC, is derived from the rotor filed coordinate machine model and presented in this paper. FOPC circumvents derivative calculations, and thus avoids high-frequency noise amplification.

scholarly journals Direct Phase Angle and Voltage Amplitude Model Predictive Control of a Power Converter for Microgrid Applications

Energies ◽  
2018 ◽  
Vol 11 (9) ◽  
pp. 2254
Author(s):  
Thai-Thanh Nguyen ◽  
Hyeong-Jun Yoo ◽  
Hak-Man Kim ◽  
Huy Nguyen-Duc
Keyword(s):  
Model Predictive Control ◽  
Power Control ◽  
Phase Angle ◽  
Predictive Control ◽  
Control Strategy ◽  
Control Strategies ◽  
Operation Mode ◽  
Power Converter ◽  
Current Control ◽  
Voltage Amplitude

Several control strategies of the finite control set model predictive controls (FCS-MPC) have been proposed for power converters, such as predictive current control (PCC), direct predictive power control (DPPC), and predictive voltage control (PVC). However, for microgrid (MG) applications, the control strategy of the FCS-MPC for a power converter might be changed according to the operation mode of the MG system, which results in a transient response in the system voltage or current during the mode transition. This study proposes a new control strategy of FCS-MPC for use in both islanded and grid-connected operation modes of an MG system. Considering the characteristic of a synchronous generator, a direct phase angle and voltage amplitude model predictive control (PAC) of a power converter is proposed in this study for MG applications. In the islanded mode, the system frequency is directly controlled through the phase angle of the output voltage. In the grid-connected mode, a proportional-integral (PI) regulator is used to compensate for the phase angle and voltage amplitude of the power converter for constant power control. The phase angle of the system voltage can be easily adjusted for the synchronization process of an MG system. A comparison study on the proposed PAC method and existing predictive methods is carried out to show the effectiveness of the proposed method. The feasibility of the proposed PAC strategy is evaluated in a simulation-based system by using the MATLAB/Simulink environment.

scholarly journals Circulating Current Suppression Strategy of Modular Multilevel Converter Based on Model Predictive Control

2021 ◽  
Vol 261 ◽  
pp. 01035
Author(s):  
kang Liu ◽  
Guige Gao
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Control Strategy ◽  
Control Method ◽  
Current Control ◽  
Switching Frequency ◽  
Modular Multilevel Converter ◽  
Multilevel Converter ◽  
Modulation Wave ◽  
Circulating Current

Modular Multilevel Converter (MMC) has the characteristics of high voltage level and low switching frequency. The traditional modular multilevel converter circulating current control strategy mostly adopts the PI control principle, and the parameter setting is complicated and the accuracy is not high, and the control process is more difficult. Model predictive control strategy is the optimal control method based on the model in the existing time domain. This paper proposes a Model Predictive Control (MPC) method based on carrier phase-shifted pulse width modulation (PSC-PWM) to suppress the circulating current, and output the optimal modulation wave through model prediction. Compared with the traditional control strategy, this strategy is simple to implement, does not require complex tuning calculations, and combines with the traditional capacitor voltage equalization strategy to obtain the output modulation wave. A 7-level MMC simulation control system is built in MATLAB / SIMLINK to verify the theory, comparing with existing control methods, it can be concluded that the proposed method has high calculation efficiency, good control accuracy and strong robustness.

scholarly journals A Control Method for IPMSM Based on Active Disturbance Rejection Control and Model Predictive Control

Mathematics ◽  
2021 ◽  
Vol 9 (7) ◽  
pp. 760
Author(s):  
Fang Liu ◽  
Haotian Li ◽  
Ling Liu ◽  
Runmin Zou ◽  
Kangzhi Liu
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Duty Cycle ◽  
Control Strategy ◽  
Disturbance Rejection ◽  
Torque Ripple ◽  
Current Control ◽  
Active Disturbance Rejection Control ◽  
Active Disturbance Rejection ◽  
Disturbance Rejection Control

In this paper, the speed tracking problem of the interior permanent magnet synchronous motor (IPMSM) of an electric vehicle is studied. A cascade speed control strategy based on active disturbance rejection control (ADRC) and a current control strategy based on improved duty cycle finite control set model predictive control (FCSMPC) are proposed, both of which can reduce torque ripple and current ripple as well as the computational burden. First of all, in the linearization process, some nonlinear terms are added into the control signal for voltage compensation, which can reduce the order of the prediction model. Then, the dq-axis currents are selected by maximum torque per ampere (MTPA). Six virtual vectors are employed to FCSMPC, and a novel way to calculate the duty cycle is adopted. Finally, the simulation results show the validity and superiority of the proposed method.

Finite-Set Model-Predictive Control Strategies for a 3L-NPC Inverter Operating With Fixed Switching Frequency

2018 ◽  
Vol 65 (5) ◽  
pp. 3954-3965 ◽  
Author(s):  
Felipe Donoso ◽  
Andres Mora ◽  
Roberto Cardenas ◽  
Alejandro Angulo ◽  
Doris Saez ◽  
...  
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Control Strategies ◽  
Switching Frequency ◽  
Finite Set

scholarly journals Min-Max Predictive Control of a Five-Phase Induction Machine

Energies ◽  
2019 ◽  
Vol 12 (19) ◽  
pp. 3713
Author(s):  
Daniel R. Ramirez ◽  
Cristina Martin ◽  
Agnieszka Kowal G. ◽  
Manuel R. Arahal
Keyword(s):  
Fuzzy Logic ◽  
Predictive Control ◽  
Loss Function ◽  
Traditional Method ◽  
Induction Machine ◽  
Decision Function ◽  
Current Control ◽  
Stator Current ◽  
First Time ◽  
Selection Of

In this paper, a fuzzy-logic based operator is used instead of a traditional cost function for the predictive stator current control of a five-phase induction machine (IM). The min-max operator is explored for the first time as an alternative to the traditional loss function. With this proposal, the selection of voltage vectors does not need weighting factors that are normally used within the loss function and require a cumbersome procedure to tune. In order to cope with conflicting criteria, the proposal uses a decision function that compares predicted errors in the torque producing subspace and in the x-y subspace. Simulations and experimental results are provided, showing how the proposal compares with the traditional method of fixed tuning for predictive stator current control.

scholarly journals Model Predictive Control with a Relaxed Cost Function for Constrained Linear Systems

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
David Sotelo ◽  
Antonio Favela-Contreras ◽  
Viacheslav V. Kalashnikov ◽  
Carlos Sotelo
Keyword(s):  
Model Predictive Control ◽  
Cost Function ◽  
State Space ◽  
Predictive Control ◽  
Discrete Time ◽  
Control Strategy ◽  
Control Strategies ◽  
State Space Model ◽  
Control Technique ◽  
Space Model

The Model Predictive Control technique is widely used for optimizing the performance of constrained multi-input multi-output processes. However, due to its mathematical complexity and heavy computation effort, it is mainly suitable in processes with slow dynamics. Based on the Exact Penalization Theorem, this paper presents a discrete-time state-space Model Predictive Control strategy with a relaxed performance index, where the constraints are implicitly defined in the weighting matrices, computed at each sampling time. The performance validation for the Model Predictive Control strategy with the proposed relaxed cost function uses the simulation of a tape transport system and a jet transport aircraft during cruise flight. Without affecting the tracking performance, numerical results show that the execution time is notably decreased compared with two well-known discrete-time state-space Model Predictive Control strategies. This makes the proposed Model Predictive Control mainly suitable for constrained multivariable processes with fast dynamics.

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