Periodic adaptive learning control of PMSM servo system with LuGre model-based friction compensation

Zhang, Wenjing; Li, Mengyue; Gao, Yaping; Chen, YangQuan

doi:10.1016/j.mechmachtheory.2021.104561

Cited by 31 publications

(16 citation statements)

References 36 publications

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“…Secondly, when the desired signal is a periodic function, our iterative learning control method only requires to know the upper and lower bounds of the parameters in LuGre model, and can achieve the asymptotic tracking, while the existing iterative learning method requires to know the accurate values of the parameters in the dynamical equation of LuGre model and only achieves the asymptotic tracking in the sense of L 2 -norm. 17 It is clear that the determination of the upper and lower bounds of the parameters is much easier than that of the accurate values of the parameters. Finally, when the desired signal is constant, the LuGre model parameters of the system are completely unknown in this study, that is, even the upper and lower bounds of the parameters are not required to be known.…”

Section: Introductionmentioning

confidence: 99%

“…The dual‐observer consists of two observers, which estimate the same state variable of LuGre model. In Reference 17, the iterative learning control method based on dual‐observer is presented, which can ensure that the tracking error converges to zero in the sense of

L_{2}

‐norm. In References 12,18‐20, the adaptive control methods based on projection observer are proposed, which can achieve asymptotic tracking 12,18,20 or approximate tracking 19 .…”

Section: Introductionmentioning

confidence: 99%

“…The accurate values of these parameters are difficult to be determined. Secondly, when the desired signal is a periodic function, our iterative learning control method only requires to know the upper and lower bounds of the parameters in LuGre model, and can achieve the asymptotic tracking, while the existing iterative learning method requires to know the accurate values of the parameters in the dynamical equation of LuGre model and only achieves the asymptotic tracking in the sense of

L_{2}

‐norm 17 . It is clear that the determination of the upper and lower bounds of the parameters is much easier than that of the accurate values of the parameters.…”

Section: Introductionmentioning

confidence: 99%

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Adaptive friction compensation for a class of mechanical systems based on LuGre model

Chen

Liu

Yan

2022

Intl J Robust & Nonlinear

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This paper deals with the problem of friction compensation for a class of uncertain mechanical systems based on LuGre model. The objective is to develop control laws such that the position variable of the system tracks a periodic desired signal or a constant desired signal. Since the friction behavior of the system with periodic desired signals is largely different from that of the system with constant desired signals, two different adaptive control methods are presented for the two cases, respectively. For the case of periodic desired signals, an adaptive repetitive learning control method is presented, and for the case of constant desired signals, an adaptive dynamic state feedback control method is presented. Both the control laws can guarantee that all the signals in the closed loop system are bounded and the tracking errors converge to zero.Several numerical simulations are carried out to show effectiveness of the proposed control algorithms.

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Section: Introductionmentioning

confidence: 99%

L_{2}

‐norm. In References 12,18‐20, the adaptive control methods based on projection observer are proposed, which can achieve asymptotic tracking 12,18,20 or approximate tracking 19 .…”

Section: Introductionmentioning

confidence: 99%

L_{2}

‐norm 17 . It is clear that the determination of the upper and lower bounds of the parameters is much easier than that of the accurate values of the parameters.…”

Section: Introductionmentioning

confidence: 99%

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Adaptive friction compensation for a class of mechanical systems based on LuGre model

Chen

Liu

Yan

2022

Intl J Robust & Nonlinear

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“…Friction is the main factor affecting the performance of the speed loop. The mainstream friction compensation method is model-based [14], [15]. However, these methods require parameter identification, and highprecision friction models often have more model parameters.…”

mentioning

confidence: 99%

“…However, these methods require parameter identification, and highprecision friction models often have more model parameters. Zhang [14] proposed a compensation method that combines adaptive control and model reference adaptive learning control based on the LuGre model, which works well for periodic tasks. Yue [15] proposed a modified LuGre model for the photoelectric tracking system to estimate friction disturbance and achieved certain results.…”

mentioning

confidence: 99%

A New Composite Control Strategy of Space Laser Pointing Mechanism Based on Active Disturbance Rejection Controller

et al. 2023

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The satellite laser communication pointing system driven by a permanent magnet synchronous motor (PMSM) should have high-precision fixed-point pointing and tracking performance. However, the system motor parameter perturbation and friction disturbances affect the performance of the system. A composite control strategy for the space laser pointing mechanism based on an active disturbance rejection controller (ADRC) is proposed to solve these problems. In order to mitigate the adverse effects of current loop parameter perturbation and speed loop friction disturbance on control performance, the improved current controller and speed controller based on ADRC are designed. On these bases, an improved feedforward position controller is designed. The proposed control strategy can effectively suppress the parameter perturbation of the current loop and the friction disturbance of the speed loop, thus improving the position tracking accuracy of the pointing mechanism for the laser communication system. Experiments are carried out based on the laser pointing mechanism platform to demonstrate the correctness and effectiveness of the proposed strategy.INDEX TERMS Laser pointing system, active disturbance rejection controller (ADRC), parameter perturbation, friction disturbance, feedforward position controller I. INTRODUCTIONCompared with radio frequency communications, laser communication has a higher transmission rate, larger communication capacity, advantages of small size, lightweight, and high confidentiality [1], which has attracted widespread attention. As a critical part of space laser communication, the pointing mechanism for the laser communication system is responsible for the acquisition, tracking, and targeting (ATP), which determines whether a reliable communication link can be established [2]. The composition block diagram is shown in Figure 1, and the main equipment is a high-precision servo based on PMSM.The driving object of the ATP system is a narrow laser beam, and its beam divergence angle is usually about 50 μrad. Therefore, the laser pointing system requires higher fixed-point pointing and stable tracking accuracy. However, temperature changes and magnetic field interference exist in the space working conditions. As the

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An observer-based IT2 TSK FLS compensation controller for PMSM servo systems: design and evaluation

Liu

Wang

2022

Neural Comput & Applic

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Periodic adaptive learning control of PMSM servo system with LuGre model-based friction compensation

Cited by 31 publications

References 36 publications

Adaptive friction compensation for a class of mechanical systems based on LuGre model

Adaptive friction compensation for a class of mechanical systems based on LuGre model

A New Composite Control Strategy of Space Laser Pointing Mechanism Based on Active Disturbance Rejection Controller

An observer-based IT2 TSK FLS compensation controller for PMSM servo systems: design and evaluation

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