Current-Controller-Free Self-Commissioning Scheme for Deadbeat Predictive Control in Parametric Uncertain SPMSM

Long, Jinlin; Yang, Ming; Chen, Yangyang; Liu, Kaiyuan; Xu, Dianguo

doi:10.1109/access.2020.3043751

Cited by 12 publications

(9 citation statements)

References 32 publications

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“…Thus, the accuracy of L q is crucial for the control performance and it is essential to obtain L q at each operating point either online or offline. [26][27][28][29] have proposed different methods for L q identification using recursive least squares algorithm, model reference adaptive method and extended Kalman filter. These methods depend on the d-axis steady state voltage equation to extract the apparent FIGURE 4 Diagram of proposed L q identification method, where the low-frequency components i df and i qf are used for current control; high-frequency component I qHF is used for L q identification.…”

Section: Q-axis Inductance Identification Using Hf Injection Methodsmentioning

confidence: 99%

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An enhanced feedforward flux weakening control for high‐speed permanent magnet machine drive applications

Lang

Yang

et al. 2021

IET Power Electronics

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Permanent magnet machines have been used in the high‐speed drive applications due to their high‐efficiency, high‐power‐density, and wide‐speed range characteristics. However, control of such high‐speed permanent magnet machines machine is always challenging and proper flux‐weakening controller design is essential to achieve high performance of these machines. In this paper, an improved feedforward flux‐weakening control scheme for interior permanent magnet synchronous machine (IPMSM) drives are proposed. The proposed method identifies optimal d‐axis and q‐axis currents under different operation regions using maximum‐torque‐per‐ampere curve, voltage limit, and current limit curves with a fast Newton–Raphson algorithm. To ensure the optimal performance of the control mechanism, effects of inductance variations due to the magnetic saturation are considered and an innovative high‐frequency staircase voltage injection method is used to identify the q‐axis inductance. The experimental results show that compared with other existing flux‐weakening methods, the proposed technique can improve the DC‐link voltage utilisation without the need to tune any controller gains and can fully utilise maximum available torque with desirable transient performance.

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Section: Q-axis Inductance Identification Using Hf Injection Methodsmentioning

confidence: 99%

“…Applying the Kirchoff's voltage law to the circuit in Figure 7, the following equation can be derived: 25) to (26) and assuming that the power module of each phase leg is of the same physical characteristic (i.e. V a_dis = -V b_dis ), we have…”

Section: Analysis Of Vsi Nonlinearity Effect On Inductance Identifica...mentioning

confidence: 99%

An enhanced feedforward flux weakening control for high‐speed permanent magnet machine drive applications

Lang

Yang

et al. 2021

IET Power Electronics

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“…This improved model predictive current control method relies on an incremental model of the Permanent-Magnet Synchronous Motor. In [17] authors investigate a DPC to resolve parameters disparity problem. The proposed control permanently recognizes the inductance and resistance of the stator for changed magnetic saturation stages.…”

Section: Nomenclaturementioning

confidence: 99%

Adaptive Deadbeat Predictive Control for PMSM-based solar-powered electric vehicles with enhanced stator resistance compensation

Ben Said-Romdhane,

Skander-Mustapha,

Belhassen

2023

Sci. Tech. Energ. Transition

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This article introduces an innovative approach called Adaptive Deadbeat Predictive Control (ADPC), specifically designed to regulate the operation of a Permanent Magnet Synchronous Motor (PMSM) within a solar-powered electric vehicle (SEV). Considering the influence of factors such as magnetic saturation, material aging, and temperature fluctuations, discrepancies may arise between actual and nominal parameter values. Notably, the stator inductance, permanent magnet flux linkage, and stator resistance are crucial variables in this context. The article conducts an in-depth theoretical examination of the consequences of these parameter mismatches on the overall stability of the system. To mitigate the effects of stator resistance variability, an adaptive control methodology is proposed. This strategy hinges on real-time control adaptation, achieved by continuously estimating the resistance value through diligent consideration of the actual winding temperature. The proposed Adaptive Deadbeat Predictive Control framework is seamlessly implemented and simulated within the MATLAB Simulink environment. The simulation results eloquently validate the efficacy of the proposed control approach, showcasing its adeptness in mitigating the system’s sensitivity to stator resistance deviations, thereby fortifying the overall control resilience.

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“…However, as the individual control method could not provide a satisfactory response, many hybrid control strategies have been developed for PMSM drive system in recent years. Besides, the selection of the controller parameters, as a key factor to reach the desired response, has motivated the scientists to investigate the optimization issue [5].…”

Section: Introductionmentioning

confidence: 99%

Development of Optimized Cooperative Control Based on Feedback Linearization and Error Port-Controlled Hamiltonian for Permanent Magnet Synchronous Motor

Zhao¹,

Wang

2021

IEEE Access

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The conflict between dynamic rapidity and steady-state accuracy is a crucial factor hindering the performance improvement of motor control system. To overcome the issue, this article proposes an optimized cooperative control combining feedback linearization (FBL) and error port-controlled Hamiltonian (EPCH) for permanent magnet synchronous motor (PMSM). First, FBL and EPCH are separately designed to obtain good dynamic and steady-state performances. Then, considering the individual advantages of FBL and EPCH, a cooperative strategy based on the real-time position error is applied to realize the smooth switching between the two methods, so that each method is utilized efficiently within the corresponding operating range. In addition, the particle swarm optimization (PSO) algorithm is introduced to properly select the controller parameters. Thus, an optimized cooperative control method, which takes into account both fast dynamic response and high steady-state precision, is developed for PMSM drives. The experimental results are finally given to illustrate the effectiveness and superiority of the proposed method.

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Current-Controller-Free Self-Commissioning Scheme for Deadbeat Predictive Control in Parametric Uncertain SPMSM

Cited by 12 publications

References 32 publications

An enhanced feedforward flux weakening control for high‐speed permanent magnet machine drive applications

An enhanced feedforward flux weakening control for high‐speed permanent magnet machine drive applications

Adaptive Deadbeat Predictive Control for PMSM-based solar-powered electric vehicles with enhanced stator resistance compensation

Development of Optimized Cooperative Control Based on Feedback Linearization and Error Port-Controlled Hamiltonian for Permanent Magnet Synchronous Motor

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