Novel Online Optimal Bandwidth Search and Autotuning Techniques for Servo Motor Drives

Hsu, Chih-Jung; Lai, Yen-Shin

doi:10.1109/tia.2017.2683442

Cited by 21 publications

(10 citation statements)

References 13 publications

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“…Remark 4.1. For the practical motor speed control system, apart from the above proposed AISE for speed detection, the recursive-least-square equation (22) guarantees the optimal estimation of moment of inertia in the sense of minimum error variance, while the self-tuning equations ( 31) and ( 29) offer a balanced controller tuning law considering stability and bandwidth in the limit of drive ability (27). The moment of inertia estimated by recursive least square method is further used to adjust the parameters in AISE and the designed self-tuning law.…”

Section: Structure Of the Proposed Self-tuning Speed Loopmentioning

confidence: 99%

“…The traditional method is to re-tune the controller manually when the load inertia changes, which is often complicated and tedious, especially for those who are not familiar with this. Therefore, both offline [25,26] and online [27][28][29] methods have been investigated to auto-tune the servo controller. In general, these methods estimate the moment of inertia first by means of least square [30,31], observers [32], extended Kalman filter [33], and other methods [13,18,[34][35][36][37][38][39], after which the tuning law will be given.…”

Section: Introductionmentioning

confidence: 99%

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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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Section: Structure Of the Proposed Self-tuning Speed Loopmentioning

confidence: 99%

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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show abstract

“…Permanent magnet synchronous motors (PMSMs) have the characteristics of a fast response speed, high control accuracy, and strong anti-interference ability, and are widely used in the field of joint servo motors [1][2][3]. However, their performance is affected because it is difficult to quickly obtain the moment of inertia of PMSMs, and the control accuracy is reduced [4,5].…”

Section: Introductionmentioning

confidence: 99%

Research on Dynamic Identification of Servo Motor Load Inertia Based on the Error Gain Factor Model

Xie

2021

Energies

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Aiming at solving the problems of slow motion and positioning deviation caused by the change of the moment of inertia of the servo motor due to different loads, an identification method for the moment of inertia on the basis of the error gain factor model is introduced into the controller, so that the moment of inertia can be obtained accurately and quickly under dynamic conditions. First, the electromagnetic and motion equation of the permanent magnet synchronous motor is built, and the logical relationship between the moment of inertia, torque, speed and other physical quantities is derived, so that the moment of inertia can be dynamically acquired. Second, in order to increase the identification accuracy, an adaptive function is introduced in the inertia identification model to replace the fixed parameters as an error gain factor (EGF). Third, the accuracy parameter is defined, and the identification algorithm on the basis of the EGF model is compared with the accuracy parameters of the existing identification method, which verifies that the improved algorithm has a better accuracy and speed. Finally, on the experimental platform, the working condition of unsteady speed is simulated. It is further verified that the proposed method has a high anti-interference capability.

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“…owadays, the improvement of servo systems has brought significant changes and benefits to the modern industry. A series of controller tuning methods to maximize existing equipment's productivity have been proposed [1], [2]. The most direct way to improve machines' efficiency is to increase the controller gain, but the higher controller gain may cause other problems, like the mechanical resonance.…”

Section: Introductionmentioning

confidence: 99%

A Modified Bi-Quad Filter Tuning Strategy for Mechanical Resonance Suppression in Industrial Servo Drive Systems

Chen

Yang

Yong-ping

et al. 2021

IEEE Trans. Power Electron.

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For mechanical resonance suppression, the bi-quad filter is a powerful tool and has been widely used in industrial applications. Compared with the notch filter, the bi-quad filter has one more parameter for notch depth design, which is more suitable for servo systems with nature damping coefficients and limited resonant gains. Usually, the bi-quad filter tuning has three steps, including identification, discretization, and switching process. However, in industrial applications, these three steps still have room for improvement. In this paper, three targeted modification methods are proposed. Firstly, an identification method based on the twins-point search is proposed to find out all of the available potential elastic characteristics accurately and quickly, and get the resonant frequency, the rejection bandwidth, and the notch depth for filter design. Then, inspired by the discretization distortion correction of the notch filter, a parameter mapping Tustin method is used to achieve accurate discretization. Furthermore, considering the bi-quad filter's settling time, a 'warm-up' buffer strategy prior to the filter switch-on is proposed to smooth the switching process. In the end, the validity and effectiveness of the proposed modification strategies are verified by experimental results. 

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Novel Online Optimal Bandwidth Search and Autotuning Techniques for Servo Motor Drives

Cited by 21 publications

References 13 publications

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

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

Research on Dynamic Identification of Servo Motor Load Inertia Based on the Error Gain Factor Model

A Modified Bi-Quad Filter Tuning Strategy for Mechanical Resonance Suppression in Industrial Servo Drive Systems

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