Comprehensive design and analysis of time-varying delayed zeroing neural network and its application to matrix inversion

Zuo, Qiuyue; Li, Xiaoxue; Li, Kenli

doi:10.1016/j.neucom.2019.10.101

Cited by 8 publications

(2 citation statements)

References 35 publications

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“…Some studies focus on tackling the time-varying matrix pseudoinversion problem with zeroing neural networks [19,20]. Hu [21] designed two zeroing neural networks to solve the inverse problem of time-varying matrices.…”

Section: Introductionmentioning

confidence: 99%

Spacecraft Attitude Measurement and Control Using VSMSCSG and Fractional-Order Zeroing Neural Network Adaptive Steering Law

Li,

Ren,

Wang

et al. 2024

Sensors

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In order to improve the accuracy and convergence speed of the steering law under the conditions of high dynamics, high bandwidth, and a small deflection angle, and in an effort to improve attitude measurement and control accuracy of the spacecraft, a spacecraft attitude measurement and control method based on variable speed magnetically suspended control sensitive gyroscopes (VSMSCSGs) and the fractional-order zeroing neural network (FO-ZNN) steering law is proposed. First, a VSMSCSG configuration is designed to realize attitude measurement and control integration in which the VSMSCSGs are employed as both actuators and attitude-rate sensors. Second, a novel adaptive steering law using FO-ZNN is designed. The matrix pseudoinverses are replaced by FO-ZNN outputs, which solves the problem of accuracy degradation in the traditional pseudoinverse steering laws due to the complexity of matrix pseudoinverse operations under high dynamics conditions. In addition, the convergence and robustness of the FO-ZNN are proven. The results show that the proposed FO-ZNN converges faster than the traditional zeroing neural network under external disturbances. Finally, a new weighting function containing rotor deflection angles is added to the steering law to ensure that the saturation of the rotor deflection angles can be avoided. Semi-physical simulation results demonstrate the correctness and superiority of the proposed method.

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Section: Introductionmentioning

confidence: 99%

Spacecraft Attitude Measurement and Control Using VSMSCSG and Fractional-Order Zeroing Neural Network Adaptive Steering Law

Li,

Ren,

Wang

et al. 2024

Sensors

View full text Add to dashboard Cite

show abstract

“…In reference [41], a varying parameter recurrent neural network is proposed for solving time-varying matrix inversion, and it has accelerated convergence time. In reference [42], a TVDZNN is designed to realize matrix inversion. In reference [43], a CVZNN is used for dynamic Moore-Penrose inverse solving, and it relaxes convex constraint of the AF.…”

Section: Introductionmentioning

confidence: 99%

Design and Analysis of Anti-Noise Parameter-Variable Zeroing Neural Network for Dynamic Complex Matrix Inversion and Manipulator Trajectory Tracking

Zhou

Tan

2022

Electronics

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Dynamic complex matrix inversion (DCMI) problems frequently arise in the territories of mathematics and engineering, and various recurrent neural network (RNN) models have been reported to effectively find the solutions of the DCMI problems. However, most of the reported works concentrated on solving DCMI problems in ideal no noise environment, and the inevitable noises in reality are not considered. To enhance the robustness of the existing models, an anti-noise parameter-variable zeroing neural network (ANPVZNN) is proposed by introducing a novel activation function (NAF). Both of mathematical analysis and numerical simulation results demonstrate that the proposed ANPVZNN model possesses fixed-time convergence and robustness for solving DCMI problems. Besides, a successful ANPVZNN-based manipulator trajectory tracking example further verifies its robustness and effectiveness in practical applications.

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Neural dynamics for adaptive attitude tracking control of a flapping wing micro aerial vehicle

Liu

Ли

2021

Neurocomputing

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Comprehensive design and analysis of time-varying delayed zeroing neural network and its application to matrix inversion

Cited by 8 publications

References 35 publications

Spacecraft Attitude Measurement and Control Using VSMSCSG and Fractional-Order Zeroing Neural Network Adaptive Steering Law

Spacecraft Attitude Measurement and Control Using VSMSCSG and Fractional-Order Zeroing Neural Network Adaptive Steering Law

Design and Analysis of Anti-Noise Parameter-Variable Zeroing Neural Network for Dynamic Complex Matrix Inversion and Manipulator Trajectory Tracking

Neural dynamics for adaptive attitude tracking control of a flapping wing micro aerial vehicle

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