An Indirect Reference Vector-Based Model Predictive Control for a Three-Phase PMSM Motor

Niu, Shuangxia; Luo, Yixiao; Fu, Weinong; Zhang, Xiaodong

doi:10.1109/access.2020.2968949

Cited by 28 publications

(8 citation statements)

References 35 publications

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“…where R = diag(R dq , f fv ) represents the positive symmetric matrix. Integrating (11) along [0 T e ], yields:…”

Section: Passive Subsystems Feedback Decompositionmentioning

confidence: 99%

“…To improve the speed regulation, a current control approach using desired‐compensation and disturbance‐observer is developed in [10]. A control strategy‐based on Model predictive method using indirect desired vector is depicted in [11]. To increase the power devices' sensorless effectiveness, the DO‐based strategy is the preferable alternative among these methods.…”

Section: Introductionmentioning

confidence: 99%

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Experimental analysis of passivity‐based control theory for permanent magnet synchronous motor drive fed by grid power

Belkhier,

Abdelyazid,

Oubelaid

et al. 2023

IET Control Theory & Appl

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Controlling the Permanent Magnet Synchronous Motor (PMSM) can be challenging due to the nonlinearity of its dynamics, which makes it difficult to design control strategies that are both robust and effective. To address this challenge, this paper presents a novel control strategy rooted in the concept of passivity that combines field‐oriented control (FOC). This strategy compels the PMSM to accurately follow velocity and electrical torque trajectories. The approach, known as passivity‐based control (PBC), entails reshaping the inherent system energy while introducing the necessary damping to attain the desired objectives. A crucial aspect involves identifying workless force terms within the process model. Despite their presence, these terms do not impact the energy balance and stability properties. As a result, eliminating these terms is unnecessary. This simplicity in control architecture not only preserves system stability but also bolsters overall robustness. The system's overall stability and the current tracking error's exponential convergence have both been demonstrated analytically. In order to maintain stability, the controller accounts for the nonlinearities of the plant and approximates the unstructured dynamics of the PMSM. The proposed control is designed using the dq model of the PMSM, which avoids the model's structure destruction due to singularities, since the dq model does not depend explicitly on the rotor angular position. Experimental results shown further, illustrate speed and position control with a desired pair calculated by a filter or a proportional‐integral (PI) controller for speed control and a proportional‐integral‐derivative (PID) controller for position control. Also the correlation between practical and theoretical results is given as well as the robustness test in relation to the uncertainties of the PMSM's inertia moment. The results demonstrates the effectiveness of the proposed strategy in controlling the PMSM under different operating conditions, highlighting its potential for industrial applications.

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“…where R = diag(R dq , f fv ) represents the positive symmetric matrix. Integrating (11) along [0 T e ], yields:…”

Section: Passive Subsystems Feedback Decompositionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Experimental analysis of passivity‐based control theory for permanent magnet synchronous motor drive fed by grid power

Belkhier,

Abdelyazid,

Oubelaid

et al. 2023

IET Control Theory & Appl

View full text Add to dashboard Cite

show abstract

“…Vector control is one of the basic control methods in the field of motor control. In [33][34][35], the basic principle of vector control is described in detail. According to the basic theory of vector control, a new sensorless vector control system based on an improved SMO and an improved FOO is established in this paper, which is shown in Fig.…”

Section: The Proposed New Sensorless Vector Control Systemmentioning

confidence: 99%

New Sensorless Vector Control System With High Load Capacity Based on Improved SMO and Improved FOO

Lü

Zheng

et al. 2021

IEEE Access

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In the existing sensorless vector control system of permanent magnet synchronous motor (PMSM), direct differential calculation or phase-locked loop (PLL) control is often used to estimate the rotor speed, but this method has some problems of weak load capacity and slow dynamic response. A new sensorless vector control method based on an improved sliding mode observer (SMO) and improved fullorder observer (FOO) is proposed in this paper. The cut-off frequency of the low-pass filter is designed as a function of speed, the back EMF is fed back into the stator current estimation mathematical model, and the adaptive rate of feedback gains coefficient is proposed for improving the traditional SMO. The disturbance feedback matrix is introduced for improving the traditional FOO, and the estimated load torque is feedforward compensated to the given end of the quadrature current. An integrated system of corresponding algorithms is established, a test platform is built. The experimental results show that the speed and load torque estimation performance of the improved observer is better than that of the traditional observer in the process of sudden load change. The sensorless vector control system based on the proposed observer has a high dynamic response, load capacity, and reliability.INDEX TERMS Sensorless vector control system, improved sliding mode observer (SMO), improved fullorder observer (FOO), load capacity, reliability.

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“…The NPC inverter-PMSM system has the characteristics of multi-input and multi-output. The principle of finite set model predictive control (FCS-MPC) is simple and has great practical value in motor drive systems [6]. However, in FCS-MPC, only one optimal vector is selected in a local time per control period, and the basic vector of NPC inverter cannot be fully utilized, which limits the control effect.…”

Section: Introductionmentioning

confidence: 99%

Three-Level Inverter-PMSM Model Predictive Current Control Based on the Extended Control Set

et al. 2023

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In the neutral point clamped (NPC) three-level inverter-permanent magnet synchronous motor system, traditional model predictive current control (MPCC) uses the system predictive model to traverse the 27 basic voltage vectors, to achieve the d-q axis current component and neutral point voltage of the multi-objective optimal control. Finite control set model predictive control predicts the state change of the control target at future moments based on a finite number of switching states of the inverter. The control principle of this method is simple and easy to implement, but the control effectiveness of this control strategy is limited because only one basic vector can be selected as the optimum output per control period. In this paper, a model predictive current control strategy based on an extended control set (ECS-MPCC) is proposed, which can improve the control performance of the system by extending the control set to select multiple vectors in a single control period compared to the traditional strategy. In addition, to address the disadvantage of extending virtual space vectors leading to an increase in computation, this paper proposes a fast search method for optimal vector based on region reduction. The proposed method avoids the optimization process traversing all virtual space vectors, thus enabling a fast search for the optimal vector. The experimental results show that the proposed control strategy has good steady-state and dynamic performance.

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An Indirect Reference Vector-Based Model Predictive Control for a Three-Phase PMSM Motor

Cited by 28 publications

References 35 publications

Experimental analysis of passivity‐based control theory for permanent magnet synchronous motor drive fed by grid power

Experimental analysis of passivity‐based control theory for permanent magnet synchronous motor drive fed by grid power

New Sensorless Vector Control System With High Load Capacity Based on Improved SMO and Improved FOO

Three-Level Inverter-PMSM Model Predictive Current Control Based on the Extended Control Set

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