A New Full‐Order Sliding Mode Observer Based Rotor Speed and Stator Resistance Estimation for Sensorless Vector Controlled Pmsm Drives

Saadaoui, Oussama; Khlaief, Amor; Abassi, Moez; Imen, Tlili; Châari, Abdelkader; Boussak, Mohamed

doi:10.1002/asjc.1812

Cited by 23 publications

(18 citation statements)

References 24 publications

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“…The present study has the peculiarity of using the GA-based control to determine the controller gains by considering the adaptive law as a minimization problem. Previous studies [6,16,17] mainly use a conventional PI controller or use a simple online compensator based on the error between measured and observed αβ axis stator currents [15]. Others propose a robust method based on the multiobjective adaptive fuzzy Luenberger observer independently on rotor resistance variation [22].…”

Section: Simulation Resultsmentioning

confidence: 99%

“…Several methods of stator resistance online estimation are presented in the literature. Among these, a full order sliding mode is developed [15] to estimate the rotor speed and the stator resistance by replacing a sign function with a sigmoid function to reduce the chattering phenomenon. In Khan and Verna [16], a P n MRAS-based resistance estimator is proposed.…”

Section: Mechan Cal Transfer Battery B D Rect Onal Dc-dc Convertermentioning

confidence: 99%

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A GA-based adaptive mechanism for sensorless vector control of induction motor drives for urban electric vehicles

Boulmane¹,

Zidani²,

Belkhayat³

et al. 2020

Turk J Elec Eng & Comp Sci

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Induction motors are more attractive to car manufacturers because they are more robust and more cost effective to maintain in comparison with other types of electric machines. The evolution of their control makes them more efficient and less expensive. However, a new control technique known as sensorless control is being used to simplify the implementation of electric machines in electric vehicles. This technique involves replacing the flux and speed sensors with an observer. The estimation of these elements is based on the measurement of currents and voltages. The main purpose of the present study is to design a novel robust structure of the sensorless vector control for an urban electric vehicle. The proposed structure aims to improve the accuracy of dynamics at low speeds, eliminate sensitivity to the machine's parameters, and maintain the stability of the system even if the variation reaches high values. The speed estimation is ensured by an enhanced PI adaptation mechanism based on the full order Luenberger observer. The proof of this stability is based on the Lyapunov theorem. Moreover, a GA-based adaptive control is used for self-tuning of the stator resistance. By combining these techniques, we can enhance the efficiency and stability of the whole system.

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Section: Simulation Resultsmentioning

confidence: 99%

Section: Mechan Cal Transfer Battery B D Rect Onal Dc-dc Convertermentioning

confidence: 99%

A GA-based adaptive mechanism for sensorless vector control of induction motor drives for urban electric vehicles

Boulmane¹,

Zidani²,

Belkhayat³

et al. 2020

Turk J Elec Eng & Comp Sci

View full text Add to dashboard Cite

show abstract

“…re f −̂e 1 + 0.05s (21) wherein del denotes the first-order angular delay and it is disabled when the frequency reaches f max ( del = 0). Hence, a flat transition from the open-loop angular information to the closeloop angular information is realised and same for corresponding control strategies.…”

Section: Smooth Transformation From Open-loop Control To Back-mentioning

confidence: 99%

An improved permanent‐magnet synchronous machine sensorless drive based on the fuzzy‐PI phase‐locked loop and the adjustable boundary‐layer FOSMO

Yao

2020

IET Power Electronics

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This study proposes a variable boundary-layer full-order sliding-mode observer (FOSMO) with a fuzzy proportional plus integral (PI) phase-locked loop (PLL) for the sensorless control of a permanent-magnet synchronous machine (PMSM). The sigmoid switching function-based FOSMO, which includes feedback speed information, is presented and considered as the conventional method. To address the contradiction between the convergence performance and the chatter-reduction ability of the sliding-mode control, a fuzzy logic controller (FLC) is introduced to adjust the boundary-layer thickness according to the estimation error. Furthermore, a real-time parameter tuning module is integrated into the PI regulator of the conventional PLL to adjust its noise bandwidth. Hence, adverse effects of disturbance and external noise, especially under transient operations, can be eliminated. An overall PMSM sensorless field-oriented control scheme incorporating the proposed method is designed, and the corresponding experimental platform is constructed. Several groups of comparative experiments reveal that system chatters are largely reduced using the proposed method under both of the high-and low-speed running conditions and the dynamic anti-interference performance can also be significantly improved under load and speed disturbances. Therefore, the feasibility and effectiveness of the proposed variable boundary-layer FOSMO + fuzzy-PI PLL method are validated.

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“…The desire to eliminate the position sensor brings the boost in the research of sensorless control [2,[9][10][11]. In this field, the back-electromotive-force(EMF)-based methods and carrier-signal-injection-based methods are two major categories.…”

Section: Introductionmentioning

confidence: 99%

“…In this field, the back-electromotive-force(EMF)-based methods and carrier-signal-injection-based methods are two major categories. However, the back-EMF-based approaches are limited by machine parameters and operating condition [9,10], while the carrier-signal-injection methods also reveal some weaknesses [12], such as having a deleterious impact on control performance, and increasing the system power loss. Besides, since the speed estimation models used in the sensorless control will rely on the accuracy and bandwidth of current detection, the elimination of the position sensor means a growing demand for high precision and high reliable current sensor, which will also increase the cost of the system.…”

Section: Introductionmentioning

confidence: 99%

High‐performance PMSM self‐tuning speed control system with a low‐order adaptive instantaneous speed estimator using a low‐cost incremental encoder

Cao

Wang

Shen

2020

Asian Journal of Control

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In practical industrial applications, the control performance in a wide speed range is hard to ensure, especially under the low-speed condition with a low-cost incremental encoder, while the unknown structure parameters may also degrade the tracking performance. This paper proposes a low-order adaptive instantaneous speed estimator (AISE) and a self-tuning control strategy to promote the speed control performance in a wide speed range with unknown inertia parameters. Together with the adaptive-Kalman-filter-based AISE, a novel measurement noise variance updating scheme, which allows more appropriate compensation in the different speed range than fixed error variance, is introduced through the theoretical analysis based on probability and stochastic process. Moreover, an easy-to-implement self-tuning law, integrated with an online recursive-least-square-based parameters identification method, is developed to tune the speed controller, while the AISE is also adjusted online to ensure the control performance with a considerable variation of load inertia.All strategies were implemented in a TMS320F28335-based permanent magnet synchronous motor (PMSM) control system with a low-cost 2500-line incremental encoder, and the results demonstrated the effectiveness of the proposed techniques. KEYWORDSadaptive Kalman Filter, instantaneous speed estimator, measurement noise adaptation, motor control, parameter self-tuning Recently, high-performance PMSM speed control system has been more and more popular in many industrial applications, such as robots, manufacturing instruments, hybrid or pure electric vehicles, due to the demand of high precision, high reliability, and user-friendliness. However, there are many obstacles to achieve high-performance PMSM speed control [1][2][3][4][5][6]. Among them, how to acquire the speed information accurately and rapidly is one of the principal challenges. In traditional PMSM applications, the methods by direct detection from the position sensors, including frequency measurement and period measurement [7,8], is widely applied. These methods are usually reliable owing to the development and progress of the sensor technology in the past decades, while there are

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A New Full‐Order Sliding Mode Observer Based Rotor Speed and Stator Resistance Estimation for Sensorless Vector Controlled Pmsm Drives

Cited by 23 publications

References 24 publications

A GA-based adaptive mechanism for sensorless vector control of induction motor drives for urban electric vehicles

A GA-based adaptive mechanism for sensorless vector control of induction motor drives for urban electric vehicles

An improved permanent‐magnet synchronous machine sensorless drive based on the fuzzy‐PI phase‐locked loop and the adjustable boundary‐layer FOSMO

High‐performance PMSM self‐tuning speed control system with a low‐order adaptive instantaneous speed estimator using a low‐cost incremental encoder

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