Model-free predictive current control for a SynRM drive based on an effective update of measured current responses

Rù, Davide Da; Polato, Mirko; Bolognani, Silverio

doi:10.1109/precede.2017.8071279

Cited by 23 publications

(14 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…with an active speed control loop, at steady state and no load. The remarkable utilisation of sequence 6 indicates the importance of considering also that sequence, neglected in [13]. The measured quantities are reported in per unit (p.u.)…”

Section: Resultsmentioning

confidence: 99%

“…As mentioned above, a possible drawback of the model-free approach is the stagnation effect [12], [13]. It happens when one (or more) element of the LUTs are not updated for many time steps, which means that a voltage vector has not been used for several switching cycles.…”

Section: The Updating Of the Current Variations Lutsmentioning

confidence: 99%

“…The finite-set algorithm applies just one (out of seven) base voltage vector for an entire control period T c . The antistagnation solution proposed in [13], [17] uses the current variations relative to the last three periods to reconstruct all the other (older) four ones. A weak point is that the reconstructions are made for use in the prediction horizon time span, when the rotor electrical position ϑ me may have changed.…”

Section: The Updating Of the Current Variations Lutsmentioning

confidence: 99%

“…III is evaluated for the motor named SynRM 1 (TABLE II). Two model-free predictive current control methods are compared: first the one proposed in [13], then the one presented in Sec. III.…”

Section: A Anti-stagnation Capabilitymentioning

confidence: 99%

“…A smart anti-stagnation algorithm is proposed in [13], where an indirect LUTs reconstruction is presented. Current LUT update is based on the mathematical relationships that link the inverter input voltages.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

An Effective Model-Free Predictive Current Control for Synchronous Reluctance Motor Drives

Carlet

Tinazzi

Bolognani

et al. 2019

IEEE Trans. on Ind. Applicat.

Self Cite

119

View full text Add to dashboard Cite

The performances of a model predictive control (MPC) algorithm largely depend on the knowledge of the system model. A model-free predictive control approach skips all the effects of parameters variations or mismatches, as well as of model nonlinearity and uncertainties. A finite-set model-free current predictive control is proposed in this paper. The current variations predictions induced by the eight base inverter voltage vectors are estimated by means of the previous measurements stored into look-up tables. To keep the current variations information up to date, the three current measurements due to the three most recent feeding voltages are combined together to reconstruct all the others. The reconstruction is performed by taking advantage of the relationships between the three different base voltage vectors involved in the process. In particular, 210 possible combinations of three-state voltage vectors can be found, but they can be gathered together in six different groups. A light and computationally fast algorithm for the group identification is proposed in this paper. Finally, the current reconstruction for the prediction of future steps is thoroughly analysed. A compensation of the motor rotation effect on the input voltages is proposed, too. The control scheme is evaluated by means of both simulation and experimental evidences on two different synchronous reluctance motors.

show abstract

Section: Resultsmentioning

confidence: 99%

Section: The Updating Of the Current Variations Lutsmentioning

confidence: 99%

Section: The Updating Of the Current Variations Lutsmentioning

confidence: 99%

Section: A Anti-stagnation Capabilitymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

An Effective Model-Free Predictive Current Control for Synchronous Reluctance Motor Drives

Carlet

Tinazzi

Bolognani

et al. 2019

IEEE Trans. on Ind. Applicat.

Self Cite

119

View full text Add to dashboard Cite

show abstract

A solution on parameter fluctuation of integrated on‐board battery chargers based on recursive least square algorithm

Deng,

Du,

Zhu

et al. 2024

Circuit Theory & Apps

View full text Add to dashboard Cite

SummaryIntegrated on‐board battery chargers (IOBCs) are receiving increasing academic attention due to their low cost and low weight advantages. However, IOBCs suffer from periodic saturation, which causes periodic changes in inductance, which may lead to deterioration in control performance. Model‐free predictive control (MFPC) is a strongly robust control method that is suitable for solving the periodic saturation problem of IOBCs with pulsating magnetic fields. In this paper, a common single‐phase IOBC topology is used as an example, the causes of inductance fluctuations are analyzed, and finite element analysis (FEM) of motor inductance with different motor qualities is carried out. A recursive least squares (RLS)‐based solution method is proposed, and its convergence is analyzed. The feasibility of the proposed control scheme is experimentally verified.

show abstract

Nonparametric three-vector model predictive current control for permanent magnet synchronous motor

ZHANG,

WU,

YAN

et al. 2023

西北工业大学学报

View full text Add to dashboard Cite

Multi-vector model predictive control of permanent magnet synchronous motor can effectively overcome the shortcomings of conventional single-vector model predictive control such as large motor current ripples and limited control accuracy, but its control performance is more susceptible to the influence of motor parameter perturbation. To improve the robustness of the multi-vector predictive control algorithm under the motor parameter perturbation, a novel nonparametric three-vector model predictive current control method for permanent magnet synchronous motors is proposed in this paper. Through constructing an ultra-local predictive current model based on the input and output signals of the permanent magnet synchronous motor, the influence of motor parameter perturbation on current prediction is avoided, and a disturbance observer is designed to estimate the non-modeled and perturbed parts of the ultra-local model. In addition, the direct calculation method of vector duty cycles based on current error is introduced to suppress the influence of motor parameter uncertainty on the duty cycle calculation link, which further improves the system robustness. Finally, simulations and experiments of the proposed method are demonstrated to compare with the conventional parametric three-vector model predictive current control, and the results show that the proposed control strategy can effectively suppress the disturbances caused by the motor parameters and ensure the steady-state performance during motor operation.

show abstract

Model-free predictive current control for a SynRM drive based on an effective update of measured current responses

Cited by 23 publications

References 10 publications

An Effective Model-Free Predictive Current Control for Synchronous Reluctance Motor Drives

An Effective Model-Free Predictive Current Control for Synchronous Reluctance Motor Drives

A solution on parameter fluctuation of integrated on‐board battery chargers based on recursive least square algorithm

Nonparametric three-vector model predictive current control for permanent magnet synchronous motor

Contact Info

Product

Resources

About