Compensating Unknown Time-Varying Delay in Opto-Electronic Platform Tracking Servo System

Xie, Ruzhen; Zhang, Tao; Li, Jiaquan; Dai, Ming

doi:10.3390/s17051071

Cited by 7 publications

(4 citation statements)

References 36 publications

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“…It means that the amplification of the errors at the medium frequency is limited. Moreover, actually, 1 − Q 1 e −jτω 2 cannot reach the boundary value in Equation (18) and approaches 0 when ω is big enough.…”

Section: The Design Of Q 1 and The Performance Improvement With Eobmentioning

confidence: 98%

“…Unfortunately, it was difficult to get the trajectory of the target and extract the disturbance signals. A predictive tracking method combining the boresight error with angular sensor for synthesizing the target trajectory was proposed to compensate the errors caused by time delay [17,18]. However, an additional position sensor was required, which was only suitable for the condition with low measurement noise.…”

Section: Introductionmentioning

confidence: 99%

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Feedforward Control Based on Error and Disturbance Observation for the CCD and Fiber-Optic Gyroscope-Based Mobile Optoelectronic Tracking System

et al. 2018

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In the mobile optoelectronic tracking system (MOTS) based on charge-coupled device (CCD) and fiber-optic gyroscope (FOG), the tracking performance (TP) and anti-disturbance ability (ADA) characterized by boresight error are of equal importance. Generally, the position tracking loop, limited by the image integration time of CCD, would be subject to a non-negligible delay and low-sampling rate, which could not minimize the boresight error. Although the FOG-based velocity loop could enhance the ADA of the system, it is still insufficient in the case of some uncertain disturbances. In this paper, a feedforward control method based on the results of error and disturbance observation was proposed. The error observer (EOB) based on the CCD data and model output essentially combined the low-frequency tracking feedforward and closed-loop disturbance observer (DOB), which could simultaneously enhance the low-frequency TP and ADA. In addition, in view of the poor low-frequency performance of the FOG due to drift and noise that may result in the inaccuracy of the observed low-frequency disturbance, the FOG-based DOB was used to improve the relatively high-frequency ADA. The proposed method could make EOB and DOB complementary and help to obtain a high-precision MOTS, for in practical engineering, we give more attention to the low-frequency TP and full-band ADA. Simulations and experiments demonstrated that the proposed method was valid and had a much better performance than the traditional velocity and position double-loop control (VPDC).

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Section: The Design Of Q 1 and The Performance Improvement With Eobmentioning

confidence: 98%

Section: Introductionmentioning

confidence: 99%

Feedforward Control Based on Error and Disturbance Observation for the CCD and Fiber-Optic Gyroscope-Based Mobile Optoelectronic Tracking System

et al. 2018

View full text Add to dashboard Cite

show abstract

“…This methodology combines angular feedback signals in either the carrier frame or the geographical frame with the off-target deviation to derive an equivalent angular position command for the target. Kalman filtering is employed to estimate the target's velocity, and this estimate is then applied to the control system through feedforward methods [17][18][19][20]. These control methods effectively mitigate the impact of delay on the system.…”

Section: Introductionmentioning

confidence: 99%

Objective Prediction Tracking Control Technology Assisted by Inertial Information

Leng,

Zhong

2023

JMSE

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This paper addresses the challenge of reduced tracking accuracy in maritime electro-optical tracking equipment when dealing with high-mobility targets like speedboats and aircraft due to off-target error delays. We propose an innovative technique that leverages inertial navigation data to enhance target prediction and tracking control. Our approach involves the real-time integration of high-frequency inertial navigation-derived attitude information into the tracking system. By combining off-target error information with angular measurements from the tracking mechanism, we project the vector of the tracked target into multiple coordinate systems, including the imaging coordinate system, carrier coordinate system, and geographic coordinate system. Subsequently, we model and predict the target’s motion trajectory in the relatively slow-changing geographic coordinate system. This transformation process increases the update frequency and real-time performance of the tracking control position loop command angle. Unlike traditional control methods that heavily rely on the model of the controlled object, our approach significantly improves tracking accuracy and engineering applicability. It offers a technology-based optimization of tracking and control performance through an interdisciplinary theoretical fusion, deeply integrating inertial navigation technology with tracking control technology. Experimental results with maritime electro-optical tracking equipment demonstrate that our proposed control technique increases tracking accuracy for high-speed targets by approximately threefold compared to traditional methods. Under the same experimental conditions, the off-target error statistics are reduced from 1.8 mrad to 633 μrad.

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“…In order to balance the robustness under uneven time-delay disturbances and the computational cost, a robust controller is investigated [ 33 , 34 , 35 , 36 , 37 , 38 ]. There are some successful applications of robust control in vehicle stability control.…”

Section: Introductionmentioning

confidence: 99%

Hierarchical Lateral Control Scheme for Autonomous Vehicle with Uneven Time Delays Induced by Vision Sensors

Liu

et al. 2018

Sensors

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Vision-based sensors are widely used in lateral control of autonomous vehicles, but the large computational cost of the visual algorithms often induces uneven time delays. In this paper, a hierarchical vision-based lateral control scheme is proposed, where the upper controller is designed by robust H∞-based linear quadratic regulator (LQR) algorithm to compensate sensor-induced delays, and the lower controller is based on logic threshold method, in order to achieve strong convergence of the steering angle. Firstly, the vehicle lateral model is built, and the nonlinear uncertainties induced by time delays are linearized with Taylor expansion. Secondly, the state space of the system is augmented to describe such uncertainties with polytopic inclusions, which is controlled by an H∞-based LQR controller with a low cost of online computation. Then, a lower controller is designed for the control of the steering motor. According to the results of the vehicle experiment as well as the hardware-in-the-loop (HIL) experiment, the proposed control scheme shows good performance in vehicle’s lateral control task, and exhibits better robustness compared with a conventional LQR controller. The proposed control scheme provides a feasible solution for the lateral control of autonomous driving.

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Compensating Unknown Time-Varying Delay in Opto-Electronic Platform Tracking Servo System

Cited by 7 publications

References 36 publications

Feedforward Control Based on Error and Disturbance Observation for the CCD and Fiber-Optic Gyroscope-Based Mobile Optoelectronic Tracking System

Feedforward Control Based on Error and Disturbance Observation for the CCD and Fiber-Optic Gyroscope-Based Mobile Optoelectronic Tracking System

Objective Prediction Tracking Control Technology Assisted by Inertial Information

Hierarchical Lateral Control Scheme for Autonomous Vehicle with Uneven Time Delays Induced by Vision Sensors

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