Digital control strategy for scanning of moving mirror in fourier transform spectrometer

Liu, Rilong; Liu, Muhua

doi:10.1016/j.ijleo.2016.10.027

Cited by 6 publications

(5 citation statements)

References 6 publications

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“…If the moving speed of the moving mirror cannot be controlled stably, the optical-path scanning speed will fluctuate, which will change the frequency of the interferogram generated by FTIR and affect the quality of the spectrum retrieved from the interferogram [ 26 , 27 ]. According to the literature review by [ 28 ], when the mean square error of the optical-path scanning speed is less than 2%, the impact of the moving mirror speed fluctuation on the quality the of the spectrum can be ignored.…”

Section: Principles and Methodsmentioning

confidence: 99%

“…In the moving mirror control system, the steady-state velocity error of the OPD velocity is required to be as small as possible and the response speed of the speed loop is fast. In this study, the speed loop adopted the PI controller, which can achieve an ideal control effect [ 33 ]. The digital PI control algorithm can be expressed as follows:

where

is the duty cycle calculated at the moment;

and

are the proportional coefficient and the integral coefficient, respectively; and

is the error at the moment.…”

Section: Principles and Methodsmentioning

confidence: 99%

“…However, it is easy to limit the design of a low-pass filter for the disturbance observer. Li T. et al (2014) proposed a PID control algorithm adjusted by an adaptive online genetic algorithm that can better suppress the added artificial disturbance, but the algorithm is complex [ 14 ]. Xia X.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Improved Active Disturbance Rejection Double Closed-Loop Control of a Rotary-Type VCM in a Moving Mirror Control System

Zhi

Huang

Han

et al. 2022

Sensors

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Aiming to address the problem of moving mirror speed fluctuations in moving mirror control systems, an improved active disturbance rejection double closed-loop controller (IADR-DCLC) is proposed and verified by simulation to realize the high-performance control of a moving mirror control system. First, the mathematical model of a rotary-type voice coil motor (RT VCM) is established, and the relationship between the angular velocity of the RT VCM and the optical path scanning velocity is analyzed. Second, in order to suppress the model uncertainty and external disturbance of the system, an improved active disturbance rejection controller (IADRC) is proposed. Compared with a conventional ADRC, the tracking differentiator of the proposed IADRC is replaced with desired signal optimization (DSO), and the actual speed is introduced to the extended state observer (ESO). The IADRC is used in the position–speed double closed-loop control model. Finally, the simulation results show that the IADR-DCLC has not only a good tracking effect but also a good anti-interference ability and can meet the requirements of the moving mirror control system for the uniformity of optical-path scanning speed and accurate control of the position of the moving mirror.

show abstract

Section: Principles and Methodsmentioning

confidence: 99%

where

is the duty cycle calculated at the moment;

and

are the proportional coefficient and the integral coefficient, respectively; and

is the error at the moment.…”

Section: Principles and Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Improved Active Disturbance Rejection Double Closed-Loop Control of a Rotary-Type VCM in a Moving Mirror Control System

Zhi

Huang

Han

et al. 2022

Sensors

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show abstract

“…However, it is difficult for the classic PID to balance the stability and rapidity of a system, and it is difficult to achieve high-speed stability. A fuzzy PID controller was used to control a linear motor [19] and VCM [20]; an improved fuzzy controller was also proposed [21], and all achieved good results. However, there are many parameters of fuzzy PID controllers, and it is difficult to find an accurate fuzzy rule table.…”

Section: Introductionmentioning

confidence: 99%

Design of an Optical Path Scanning Control System in a Portable Fourier Transform Spectrometer Based on Adaptive Feedforward–Nonlinear Proportional-Integral Cascade Composite Control

Zhi,

Huang,

Wen

et al. 2024

Actuators

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In order to obtain highly accurate infrared spectra, the optical path scanning control system in a portable Fourier transform spectrometer (FTS) must be able to realize highly stable reciprocal scanning. To address the positional localization and speed fluctuation problems of optical path scanning control systems, an adaptive feedforward–nonlinear PI cascade composite control algorithm (AF-NLPI) is proposed. A physical model of an optical path scanning control system is established. Moreover, an adaptive feedforward compensator using a dynamic forgetting factor is proposed, and it was combined with a nonlinear PI cascade controller to form a composite controller. The control parameters were tuned using the atomic orbital search algorithm. Further, the simulation and experimental results demonstrate that the AF-NLPI can effectively improve the control accuracy and anti-interference ability of an optical path scanning control system in a portable FTS with high feasibility and practicality. By setting the scanning stroke of the system to 8 mm and scanning at 10 mm/s, the stability of the optical scanning speed reached 99.47% when controlled by the controller proposed in this paper, thus fulfilling the motion requirements for optical path scanning control systems.

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“…Proportional integral derivative (PID) was adopted to control the scanning mirror. e fuzzy PID was adopted with a relative error in the output of less than 4% [1][2][3]. We found that the iterative learning control (ILC) can achieve satisfactory results when controlling the scanning mirror in the absence of disturbances.…”

Section: Introductionmentioning

confidence: 99%

Artificial Neural Network-Based Feed-Forward and Feedback Control Design and Convergence Analysis

Chen

Liu

2022

Mathematical Problems in Engineering

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A feed-forward and feedback control scheme based on artificial neural network (ANN) and iterative learning control is proposed. Iterative learning control and ANN are combined as a feed-forward controller, which makes the output track the desired trajectory. Feedback control is introduced to reduce the effect of disturbances. To combine the feed-forward controller and the feedback controller, the ANN is employed to simulate the plant. Since the ANN can update the weights online, it is always consistent with the plant. The convergence and robustness of the system are analyzed, and the simulation shows the feasibility of the proposed control scheme.

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Digital control strategy for scanning of moving mirror in fourier transform spectrometer

Cited by 6 publications

References 6 publications

Improved Active Disturbance Rejection Double Closed-Loop Control of a Rotary-Type VCM in a Moving Mirror Control System

Improved Active Disturbance Rejection Double Closed-Loop Control of a Rotary-Type VCM in a Moving Mirror Control System

Design of an Optical Path Scanning Control System in a Portable Fourier Transform Spectrometer Based on Adaptive Feedforward–Nonlinear Proportional-Integral Cascade Composite Control

Artificial Neural Network-Based Feed-Forward and Feedback Control Design and Convergence Analysis

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