Non‐linear model predictive control for visual servoing systems incorporating iterative linear quadratic Gaussian

Wu, Jinhui; Jin, Zhehao; Liu, Andong

doi:10.1049/iet-cta.2019.1399

Cited by 6 publications

(4 citation statements)

References 28 publications

(30 reference statements)

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“…However, the actual manual tracking and aiming process is complex, and the LOS linear motion model will be affected by external factors. Therefore, a composite constraint Equation ( 18) is added based on the LOS judgment correction in Equation (17).…”

Section: Miss-distance Judgment Of Los Firing Controllermentioning

confidence: 99%

“…Zhong et al [16] established a passive error feature prediction equation based on the geometric dynamics of a spherical camera. Wu et al [17] proposed a nonlinear Gaussian iterative prediction model to achieve the visual servo stability control of wheeled robots. Zhang et al [18] fused the inertial measurement unit and monocular camera, and adopted the iterative extended Kalman filter.…”

Section: Introductionmentioning

confidence: 99%

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Prediction and Control of Small Deviation in the Time-Delay of the Image Tracker in an Intelligent Electro-Optical Detection System

et al. 2023

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A small deviation in the time-delay of the image tracker is essential for improving the tracking precision of an electro-optical system, and for future advances in actuator technology. The core goal of this manuscript is to address issues such as tracking the controller time-delay compensation and the precision of an electro-optical detection system using an advanced filter design, a fire control modeling, and an anti-occlusion target detection system. To address this problem, a small deviation in the time-delay prediction and control method of the image tracker is proposed based on the principle of linear motion transformation. The time-delay error formation is analyzed in detail to reveal the scientific mechanism between the tracking controller feedback and the line-of-sight position correction. An advanced N-step Kalman filtering controller model is established by combining a line-of-sight firing control judgment and a single-sample training anti-occlusion DSST target tracking strategy. Finally, an actuator platform with three degrees of freedom is used to test the optical mechatronics system. The results show that the distribution probability of the line-of-sight measuring error in a circle with a radius of 0.15 mrad is 72%. Compared with the traditional control method, the tracking precision of the optimal method is improved by 58.3%.

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Section: Miss-distance Judgment Of Los Firing Controllermentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Prediction and Control of Small Deviation in the Time-Delay of the Image Tracker in an Intelligent Electro-Optical Detection System

et al. 2023

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“…They use an novel automated recognition of configuration transitions and construct the iterative LIE framework relies on some assumptions to predict binding affinities in data interaction. In 2020, Wu [28] proposes a non-linear predictive control (NMPC) to deal with the system point stabilization for an image-based visual servoing (IBVS), which acquired the effectiveness of iLQG model in non-linear processing. In 2020, Li [29] gets a adaptive iterative learning consensus control for a multiple orders embed on brain and computer with non-linear state.…”

Section: Related Workmentioning

confidence: 99%

The Energy-Efficient Resource Allocation of Multi-Modal Perception for Affective Brain-Computer Interactions Based on Non-Linear Iterative Prediction Scheme

Zhou¹,

Zhou²,

Chen³

et al. 2023

Journal of Internet Technology

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<p>For the whole environmental settings in this research, the conventional affective brain-computer interactions can not build a good performance on energy-efficient resource of network’s forwarding ports and routing paths due to its poor allocation function of cognitive radio networks, based on the novel interactive networking architecture, the model of non-linear iterative prediction scheme in interaction was successively proposed. This research proposes a modified LSTM algorithm with a structure of non-linear iterative in complexity prediction, joins the multiple k modes selection and multi-agent systems, maximizes EERA of forwarding and routing while maintaining the communication quality. Firstly, considering whether this affective brain-computer interactions need the networking communication in system. Secondly, adjusting the forwarding and routing factors of energy-efficient resource allocation by selecting the best optimal energy-efficient resource for the links through the non-linear iterative prediction in a multi-modal perception. The simulation results show that compared with the other models and algorithms, the proposed scheme for affective brain-computer interactions, which has a nice performance on a higher EERA and channel utilization of a networking architecture of brain-computer interactions.</p> <p> </p>

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“…With the development of electronic technology, the movement speed and real‐time control performance of AMRs coordinated motion have higher requirements [1]. However, considering the nonlinear characteristic of the AMR system with nonholonomic constraints, it is difficult to establish an effective cooperative tracking control model for the AMR and UAV, which increases the complexity of the real‐time control strategy designing [2]. Besides, the external disturbances often exist in AMR and UAV simultaneously in the form of multiple harmonics, which affects the maneuverability of the AMR and UAV cooperative tracking control performance.…”

Section: Introductionmentioning

confidence: 99%

Air–ground trajectory tracking for autonomous mobile robot based on model predictive hybrid tracking control and multiple harmonics time‐varying disturbance observer

Xiong

Chen

Wei

et al. 2022

IET Control Theory & Appl

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This paper studies a model predictive hybrid tracking control scheme under a multiple harmonics time-varying disturbance observer for a discrete-time dynamics nonholonomic autonomous mobile robot (AMR) with disturbance. To solve the robust tracking control problem of the AMR and unmanned aerial vehicle (UAV) air-ground cooperative, a hybrid tracking control strategy combined with improved model predictive control (MPC) method is presented. First, a time-varying air-ground cooperative tracking control model based on the nonholonomic constraints AMR and UAV is established by polar coordinate transformation. Second, to estimate disturbances of the time-varying model, a multiple harmonics disturbance observer with time-varying gains is designed. A hybrid tracking control scheme for the AMR based on the estimated states and MPC method with relaxing factor and kinematics constraints is proposed. Finally, experimental results show the effectiveness of the proposed control strategy.

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Non‐linear model predictive control for visual servoing systems incorporating iterative linear quadratic Gaussian

Cited by 6 publications

References 28 publications

Prediction and Control of Small Deviation in the Time-Delay of the Image Tracker in an Intelligent Electro-Optical Detection System

Prediction and Control of Small Deviation in the Time-Delay of the Image Tracker in an Intelligent Electro-Optical Detection System

The Energy-Efficient Resource Allocation of Multi-Modal Perception for Affective Brain-Computer Interactions Based on Non-Linear Iterative Prediction Scheme

Air–ground trajectory tracking for autonomous mobile robot based on model predictive hybrid tracking control and multiple harmonics time‐varying disturbance observer

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