SM Load Torque Observer-Based FCS-MPDSC With Single Prediction Horizon for High Dynamics of Surface-Mounted PMSM

Gong, Chao; Hu, Yihua; Ni, Kai; Liu, Jinglin; Gao, Jinqiu

doi:10.1109/tpel.2019.2929714

Cited by 44 publications

(20 citation statements)

References 23 publications

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“…In this paper, a three-phase PLL whose structure is shown in Figure 2 is employed to obtain the real-time voltage amplitude and frequency [32]. It can be noted that firstly, the measured phase voltages are transformed to the ones in the rotating reference frame, that is, the d, q-axis voltages V d and V q , respectively [33,34]:…”

Section: Fixed-parameter Vsg Control Incorporating F-p and Q-v Droop mentioning

confidence: 99%

Microgrid Frequency Fluctuation Attenuation Using Improved Fuzzy Adaptive Damping-Based VSG Considering Dynamics and Allowable Deviation

Liang

Niu

2020

Energies

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Recently, virtual synchronous generators (VSGS) are a hot topic in the area of microgrid control. However, the traditional fixed-parameter-based VSG control methods have an obvious disadvantage. Namely, if the damping value is set to be small, the amplitude of frequency deviations under external power disturbances is large, meaning that the frequency suppression capacity is insufficient, but if the damping value is large, the dynamics of the system will be greatly sacrificed. To solve the problem, taking the dynamic characteristics and the maximum allowable frequency deviation (MAFD) into account, in this paper an improved fuzzy adaptive damping-based VSG control strategy is proposed to simultaneously attenuate the microgrid frequency fluctuations and guarantee the system dynamics. Firstly, in order to address the necessity of using an adaptive damping-based VSG, the structure of a fixed-parameter VSG method that incorporates the f-p/Q-V droop controllers is introduced, based on which a small signal model is established to discuss the impacts of the virtual damping on the frequency response characteristics concerning the different penetration levels of power disturbances. Then, considering the dynamics and MAFD, a fuzzy adaptive controller is constructed relying on the well-designed membership functions, control rules and output scaling factors. The main feature of the improved fuzzy controller is that two alternative output scaling factors are employed to allow the system to be overdamped when the frequency deviation is large and undamped when the frequency deviation is small, balancing the frequency response dynamics and stability characteristics. To verify the effectiveness of the proposed fuzzy adaptive damping-based VSG technique, a computer simulation is conducted on a microgrid system in MATLAB/Simulink, and the obtained results are compared with the conventional droop control and fixed-parameter based VSGs. By using the proposed fuzzy adaptive damping-based VSG control method, the peak frequency deviations under the large power disturbances would become at least 8% lower compared to the traditional droop control and fixed-parameter VSG control, and meanwhile, the frequency response speed is fast when the disturbance stands at a low position. Consequently, it is valuable to promote the proposed techniques in engineering.

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Section: Fixed-parameter Vsg Control Incorporating F-p and Q-v Droop mentioning

confidence: 99%

Microgrid Frequency Fluctuation Attenuation Using Improved Fuzzy Adaptive Damping-Based VSG Considering Dynamics and Allowable Deviation

Liang

Niu

2020

Energies

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“…Between t k and t k+1 , the physical descriptions of the traditional FCS-MPCC implementation (as in Fig.1) can be explained as follows: At first, the measured and observed states at t k together with the candidate control voltages are substituted into (12) to calculate the slope (sl) of the tangent line of the current wave, namely, sl= f(t k ). Secondly, f(t k ) is treated as the slope of the following straight line:…”

Section: A Physical Explanations Of Traditional Fcs-mpcc Defects In mentioning

confidence: 99%

“…Finite control set (FCS) model predictive control (MPC), which is endowed with remarkable simplicity and strong constraint capability, has been widely used in different electric powertrains [11][12][13][14]. Without adopting any modulators for pulse width modulation (PWM) signal generation, FCS-MPC directly uses the output of the controller to determine the optimal switching state [15].…”

Section: Introductionmentioning

confidence: 99%

Low-Switching-Loss Finite Control Set Model Predictive Current Control for IMs Considering Rotor-Related Inductance Mismatch

Tan

et al. 2020

IEEE Access

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This paper develops a high-performance finite control set model predictive current control (FCS-MPCC) method for induction motors (IM) to ensure the system control performance over the lowswitching-frequency (LSF) range, where the switching loss is low. The new controller is based on tripartite calculations in each control period and sliding mode (SM) rotor-related inductance observer. In detail, firstly, to solve the problem that the control performance of the traditional FCS-MPCC methods is low when they are used at low frequencies, tripartite calculations are employed in each control period to improve the prediction accuracy. By dividing one control period into three equal parts and executing the prediction algorithm in each subsection, the current estimation errors become lower compared to the conventional single-step Euler-discretization controller. Then, considering that the performance of an FCS-MPCC controller highly relies on the machine parameter values, but it is hard to directly obtain the accurate rotor-related inductances (mutual inductance and rotor inductance), this paper uses an online parameter observer based on the sliding mode (SM) principle to diagnose them in real time. It needs to be mentioned that when discussing the stability of the sigmoid-function-based SM observer, a new technique called estimation-error-limitation is initially adopted in this paper to simplify the analysis process. Finally, the proposed algorithms are verified by simulation, which is conducted on a three-phase IM at LSF situations. INDEX TERMS Induction motor, finite control set model predictive control, sliding mode observer, parameter mismatch, low switching frequency.

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“…Due to the merits of the optimal control mechanism, easy parameter tuning process and quick response, model predictive control (MPC) has been broadly adopted in the area of IM control [10]. MPC controllers can be used to achieve different functions, such as model Processes 2021, 9, 710 2 of 22 predictive torque control (MPTC) [11,12], model predictive speed control (MPSC) [13] and model predictive current control (MPCC) [14,15]. By considering the modulation modes of the MPC controllers, they can be further categorized into two groups, one of which requires a modulator to generate control signals.…”

Section: Introductionmentioning

confidence: 99%

“…Instead, the cost function directly determines the optimal switching states to be applied next. As for this method, there are only finite control voltages, so it is known as a finite control set model predictive control (FCS-MPC) [12][13][14]16]. Comparatively speaking, the FCS-MPC strategy can reduce computational complexity significantly, benefiting from an offline lookup table.…”

Section: Introductionmentioning

confidence: 99%

Ripple Attenuation for Induction Motor Finite Control Set Model Predictive Torque Control Using Novel Fuzzy Adaptive Techniques

et al. 2021

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Finite control set model predictive torque control (FCS-MPTC) strategy has been widely used in induction motor (IM) control due to its fast response characteristic. Although the dynamics of the FCS-MPTC method are highly commended, its steady-state performance—ripple deserves attention in the meantime. To improve the steady-state performance of the IM drives, this paper proposes an improved FCS-MPTC strategy, based on a novel fuzzy adaptive speed controller and an adaptive weighting factor, tuning strategy to reduce the speed, torque and flux ripples caused by different factors. Firstly, a discrete predicting plant model (PPM) with a new flux observer is established, laying the ground for achieving an FCS-MPTC algorithm accurately. Secondly, after analyzing the essential factors in establishing a fuzzy adaptive PI controller, with high ripple suppression capacity, an improved three-dimensional controller is designed. Simultaneously, the implementation procedures of the fuzzy adaptive PI controller-based FCS-MPTC are presented. Considering that a weighting factor must be employed in the cost function of an FCS-MPTC method, system ripples increase if the value of the weighting factor is inappropriate. Then, on that basis, a novel fuzzy adaptive theory-based weighting factor tuning strategy is proposed, with the real-time torque and flux performance balanced. Finally, both simulation and hardware-in-loop (HIL) test are conducted on a 1.1 kW IM drive to verify the proposed ripple reduction algorithms.

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SM Load Torque Observer-Based FCS-MPDSC With Single Prediction Horizon for High Dynamics of Surface-Mounted PMSM

Cited by 44 publications

References 23 publications

Microgrid Frequency Fluctuation Attenuation Using Improved Fuzzy Adaptive Damping-Based VSG Considering Dynamics and Allowable Deviation

Microgrid Frequency Fluctuation Attenuation Using Improved Fuzzy Adaptive Damping-Based VSG Considering Dynamics and Allowable Deviation

Low-Switching-Loss Finite Control Set Model Predictive Current Control for IMs Considering Rotor-Related Inductance Mismatch

Ripple Attenuation for Induction Motor Finite Control Set Model Predictive Torque Control Using Novel Fuzzy Adaptive Techniques

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