scholarly journals Improvement of Induction Motor Torque Characteristics by Model Predictive Current Controller

2019 ◽  
Vol 8 (2) ◽  
pp. 5578-5583
Keyword(s):  
Induction Motor ◽  
Predictive Control ◽  
Complex Space ◽  
Control Variable ◽  
Current Control ◽  
Current Harmonics ◽  
Stator Current ◽  
Current Controller ◽  
Vector Modulation ◽  
Further Development

This paper describes the Model Predictive control (MPC) strategy to control the Torque of the Induction Motor (IM) according to the reference torque provided. IM fed with an Three Level Neutral Point Clamped (NPC) Inverter. MPC paves the way to replace complex Space Vector Modulation (SVM) into a simple understandable algorithm. It uses the discretized model of the IM. Stator current is used as a control variable hence called Model Predictive Current Control (MPCC). MPCC is derived from Field Oriented Control (FOC) Technique. MPCC achieves improved nominal torque compared to FOC, But current harmonics are high rather it’s simplicity encourages it’s usage and further development in MPC strategies for Embedded Drives. By the end of the paper, both FOC and MPCC controls of IM drive were discussed using MATLAB/SIMULINK.

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 Robust Current Predictive Control-Based Equivalent Input Disturbance Approach for PMSM Drive

Electronics ◽  
2019 ◽  
Vol 8 (9) ◽  
pp. 1034 ◽  
Author(s):  
Xudong Liu ◽  
Qi Zhang
Keyword(s):  
Predictive Control ◽  
Permanent Magnet Synchronous Motor ◽  
Tracking Error ◽  
Current Control ◽  
Control Technique ◽  
Current Loop ◽  
Input Disturbance ◽  
Current Controller ◽  
Simulation And Experiment ◽  
Equivalent Input Disturbance

The implementation and experimental validation of current control strategy based on predictive control and equivalent input disturbance approach is discussed for permanent magnet synchronous motor (PMSM) control system in the paper. First, to realize the current decoupling control, the deadbeat predictive current control technique is adopted in the current loop of PMSM. Indeed, it is well known that the traditional deadbeat current control cannot completely reject the disturbance and realize the zero error current tracking control. Then, according to the model uncertainties and the parameter variations in the motor, an equivalent input disturbance approach is introduced to estimate the lump disturbance in the system, which will be used in the feed-forward compensation. Thus, a compound current controller is designed, and the proposed algorithm reduces the tracking error caused by the disturbance; the robustness of the drive system is improved effectively. Finally, simulation and experiment are accomplished on the control prototype, and the results show the effectiveness of the proposed current control algorithm.

scholarly journals Current Prediction-Based Three-Vector Voltage Optimization System for the Induction Motor with Current Static Error Correction

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Li Haixia ◽  
Lin Jican
Keyword(s):  
Steady State ◽  
Model Predictive Control ◽  
Induction Motor ◽  
Predictive Control ◽  
Control Method ◽  
Tracking Error ◽  
Current Control ◽  
Static Error ◽  
Control Stability ◽  
Steady State Performance

In the present study, the current control method of the model predictive control is applied to the field-oriented control induction motor. The augmentation model of the motor is initially established based on the stator current equation, which performs the current predictive control and formulates the new cost function by means of tracking error. Then, the influence of parameter error on the current control stability in the prediction model is analysed, and the current static error is corrected according to the correlation between the input and feedback. Finally, a simple and effective three-vector control strategy is proposed. Moreover, three adjacent basic voltage vectors are utilized, and then six candidate voltage vectors are synthesized in each sector to replace eight basic voltage vectors in the conventional model predictive control (MPC). The obtained results show that synthesized vectors, which have arbitrary amplitude and direction, significantly expand the coverage of the system’s control set, reduce the torque and flux pulsation in the conventional MPC, and improve the steady-state performance of the system. Finally, the dSPACE platform is employed to validate the performed experiment. It is concluded that the proposed method can reduce the torque and flux pulse, perform the induction motor current control, and improve the steady-state performance of the system.

scholarly journals Design Of Speed Controller For Three Phase Induction Motor Using Fuzzy Logic Approach

2018 ◽  
pp. 12-25
Keyword(s):  
Induction Motor ◽  
Low Cost ◽  
Stator Current ◽  
Speed Controller ◽  
Current Controller ◽  
Three Phase ◽  
Fuzzy Logic Approach ◽  
Logic Approach ◽  
And Performance ◽  
Fuzzy Like

The use of Induction Motor (IM) has been increased becuase of it’s robust construction , simple design , and low cost . This paper presents a methodology for the application and performance of Fuzzy like PI Controller to set the frequency of Space Vector Pulse-Width modualtion (SVPWM) Inverter applied to closed loop speed control of IM. When the controller is used with current controller, the quadratic component of stator current is estimated by the controller. Instead of using current controller, this paper proposes estimating the frequency of stator voltage. The dyanamic modelling of the IM is presented by dq axis theory. From the simulation results, the superiority of the suggested controller can be observed in controlling the speed of the three-phase IM.

A new approach to minimize torque ripple and noise in model predictive control of permanent magnet synchronous motor drives

2020 ◽  
pp. 107754632093374
Author(s):  
Arumugam Sivaprakasam ◽  
Lekshmanan N Ramya
Keyword(s):  
Model Predictive Control ◽  
Cost Function ◽  
Permanent Magnet ◽  
Predictive Control ◽  
Permanent Magnet Synchronous Motor ◽  
Motor Drives ◽  
Control Technique ◽  
Current Harmonics ◽  
Stator Current ◽  
Stator Flux

Model predictive control widely advocates in the better performance control technique for permanent magnet synchronous motor drives for its exceptional flexibility of incorporating nonlinear parameters. However, the higher ripples in torque and harmonics in stator current are the major criticisms in this method. Enlightened by the idea of including nonlinear constraints in the cost function, this article proposes a novel cost function with reduced ripples in torque, stator flux, and current harmonics. The improvised cost function uses torque tracking, maximum torque per ampere, minimization of switching losses, and system constraints. This approach attains effectiveness in the minimization of the ripples in torque, stator flux, and stator current harmonics and also reduces the acoustic noise of the system. The claims of the proposed work are supported by the quantitative comparison of the simulated response with the standard model predictive torque control that uses errors in the stator flux and electromagnetic torque in its cost function. The compared simulation results prove the effectiveness of the proposed control technique.

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