Simplified model predictive control with variable weighting factor for current ripple reduction

Abbaszadeh, Alireza; Khaburi, Davood Arab; Mahmoudi, Hamid; Rodríguez, José

doi:10.1049/iet-pel.2016.0483

Cited by 32 publications

(24 citation statements)

References 33 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For (17) and (18), the orders of magnitude of A x , B x and C x (xϵ{1, 2}) are 10 -2 , 10 -7 and 10 -6 , respectively. Then comparing the magnitude of each part of (15) and (16), and ignoring the smaller parts, the approximate relationship between inductance deviation and prediction error can be obtained  …”

Section: B C B a C Bmentioning

confidence: 99%

“…In [14], the prediction errors provided by each voltage vector are added to current prediction stage with a weighting factor, which can effectively improve the prediction accuracy. The current prediction errors are various under different switching states [15], so, a variable weighting factor is presented in [16] based on the position and magnitude of reference voltage. Although the error compensation method can effectively reduce the prediction error, it does not solve the fundamental problem that causes prediction error.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Current Prediction Error Reduction Method of Predictive Current Control for Permanent Magnet Synchronous Motors

et al. 2020

View full text Add to dashboard Cite

Predictive current control (PCC) has been widely investigated in motor drive field. The PCC is a model-based control method and the motor prediction model is quite sensitive to motor parameters which may be inaccurately measured and change under different working conditions. In order to reduce the current prediction error of PCC caused by inductance mismatch, a current prediction error reduction method is proposed for permanent magnet synchronous motor (PMSM) by online inductance correction which is based on the relationship between inductance mismatch and current prediction error. Firstly, a proportional regulator is used to obtain the absolute correction value according to the relationship between inductance error and current prediction error. Secondly, the polarity of correction value is judged according to the fluctuation amplitudes of predicted current and actual current. Finally, an adaptive adjustment method for correction period is proposed to ensure the accuracy of inductance correction value. Experimental tests are carried out to verify the effectiveness of proposed method, and results show that the proposed method can obviously reduce current prediction error and improve control performance in practical applications. In addition, the proposed method is suitable for interior and surface mounted PMSMs. INDEX TERMS Current prediction error reduction, online inductance correction, permanent magnet synchronous motor (PMSM), predictive current control (PCC).

show abstract

Section: B C B a C Bmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Current Prediction Error Reduction Method of Predictive Current Control for Permanent Magnet Synchronous Motors

et al. 2020

View full text Add to dashboard Cite

show abstract

“…Because of the computational burden of the conventional FCS-MPC, the simplified FCS-MPC was proposed in [35], the predicted model of which could also be described as Equation (11). Hence, according to Equations (11) and (12), the improved FCS-MPC with error correction can be calculated as follows:…”

Section: The Improved Fcs-mpc With Error Correctionmentioning

confidence: 99%

“…Similarly, V 2 (k) should be chosen corresponding to V r2 (k). Thus, the error between V r (k) and V(k) is bounded: The following stability criteria for the Lyapunov function G(∆y(k)) are described in [29,35]:…”

Section: Robustness Analysis Of γ For the Improved Fcs-mpcmentioning

confidence: 99%

See 1 more Smart Citation

Hybrid Control Strategy of MPC and DBC to Achieve a Fixed Frequency and Superior Robustness

Zhang

et al. 2020

Energies

View full text Add to dashboard Cite

In this paper, a hybrid control strategy for power converters, based on improved deadbeat control (DBC) and improved finite control set model predictive control (MPC), is proposed. The presented control strategy employs a switched method to achieve a fixed switching frequency while maintaining a fast transient time. Moreover, the proposal incorporates error correction to achieve superior robustness. A prototype of a single-phase voltage source rectifier is established to verify the performance of the proposal. The comparative results with conventional MPC are given and illustrate the merits of the proposed control method.

show abstract

Modified model predictive torque control for induction motors with improved robustness against mutual inductance mismatching

Abbasi

Husain

Idris

et al. 2021

Int Trans Electr Energ Syst

View full text Add to dashboard Cite

Summary This article proposes a new model predictive torque control (MPTC) for induction motors to improve its robustness against parameter mismatching when current model (CM) for flux estimation is employed. The main advantages of the proposed method are the improved range of stable operation during the occurrence of mutual inductance Lm, mismatched value, lower computational burden, and reduced switching losses. The improvement in robustness is achieved via adaptation of direct torque control (DTC) features thus eliminating any additional parameter estimation mechanism. Reference transformation is used to remove torque error from the cost function to achieve weighting‐factor‐free MPTC formulation. Then, based on the estimated and reference stator flux vector positions, it is established that flux positional error is directly proportional to the torque error. The positional error is then employed to reduce the admissible voltage vectors, which decreases parameter dependence of MPTC. The simulation results are compared to two other well‐established MPTC techniques and based on the results, it is concluded that the proposed MPTC without parameter estimation and compensation technique have a wider tolerability of 56% for Lm mismatching.

show abstract

Simplified model predictive control with variable weighting factor for current ripple reduction

Cited by 32 publications

References 33 publications

Current Prediction Error Reduction Method of Predictive Current Control for Permanent Magnet Synchronous Motors

Current Prediction Error Reduction Method of Predictive Current Control for Permanent Magnet Synchronous Motors

Hybrid Control Strategy of MPC and DBC to Achieve a Fixed Frequency and Superior Robustness

Modified model predictive torque control for induction motors with improved robustness against mutual inductance mismatching

Contact Info

Product

Resources

About