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A Novel Attitude controller for Hypersonic Aircraft Based on FR-PI2

A Novel Attitude Controller for Hypersonic Aircraft Based on...

引用

International Conference on Guidance, Navigation and control, ICGNC 2020

作者： Fan, Jiajun Li, Tianyi Guo, Xian Hao, Mingrui Sun, Mingwei College of Artificial Intelligence Nankai University Tianjin300350 China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Bejing100074 China

ISBN: (纸本)9789811581540

Due to the uncertainties and various noises of the Hypersonic Aircraft(HA), traditional method of designing attitude controllers based on accurate models faces immense challenges. To solve those proposed urgent problems effectively, in this paper, a innovative data-driven RL algorithm called FR-PI2 is proposed for the task of Hypersonic Aircraft attitude control, wherein several key techniques are introduced. Firstly, Hypersonic Aircraft attitude control is transformed into a stochastic optimal control problem, and the numerical solutions of the proposed stochastic optimal control problem are obtained with a path-integral-based method, called Policy Improvement with Path Integrals(PI2). Secondly, a model-free policy parameterization method with PID controller is integrated into the PI2 algorithm to ensure a low dependency of the Hypersonic Aircraft system model. Thirdly, a brand-new sample filtration method is proposed to guarantee rapid convergence, and an online optimization technology called rolling optimization is applied to guarantee optimality and real-time performance. Two series of experiments are carried out and analyzed to demonstrate the outstanding performance of the FR-PI2 algorithm. © 2022, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Reinforcement learning

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Active Disturbance Rejection Gain Scheduling control of Hypersonic Vehicle Based on Guardian Maps 13

Active Disturbance Rejection Gain Scheduling Control of Hype...

引用

13th IEEE Data Driven control and Learning systems Conference, DDCLS 2024

作者： Zhang, Tingyu Wang, Yongshuai Sun, Mingwei Hao, Mingrui Chen, Zengqiang College of Artificial Intelligence Nankai University Tianjin300350 China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China

ISBN: (纸本)9798350361674

This paper presented an adaptive gain scheduling algorithm for hypersonic vehicles with wide envelopes. First, the linear parameter variable parameter (LPV) model of hypersonic vehicles is established in the flight envelope. Then, the active disturbance rejection controller is considered to cope with disturbances and uncertainties, and the control gain is scheduled using the guardian maps method to adapt to the wide envelope of velocity and height. Finally, numerical simulation results show good control performance and meet the required performance indexes in all operating conditions, demonstrating the effectiveness and robustness of the proposed method. © 2024 IEEE.

关键词： Disturbance rejection

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Radar Target Selection Strategy Based on Improved Subjective Bayesian Reasoning

Radar Target Selection Strategy Based on Improved Subjective...

引用

International Conference on Autonomous Unmanned systems, ICAUS 2021

作者： Li, Wen Pei, Hucheng Qu, Guangzhou Hao, Mingrui Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China Beijing Electro-Mechanical Engineering Institute Beijing100074 China

ISBN: (纸本)9789811694912

In order to deal with the influence of dilution passive decoy jamming on target selection of UAV radar, and to enable UAV radar have more independent decision-making ability to acquire the naval ship correctly in an ocean battlefield scene containing single real ship and multiple passive decoys, a method which established the mathematical simulation model of jamming scene, and used the model as the fitness function to calculate the adequacy measurement parameters of subjective Bayesian reasoning through genetic optimization algorithm is proposed. This method is applied to UAV radar target selection, compared with traditional target selection methods using single target feature, this method can improve the accuracy of ship acquisition by comprehensive using multi-dimensional target features. Moreover, this method can further improve the joint acquisition accuracy by setting multiple adequacy measurement parameters for different radars, which prove that the method can achieve the purpose of improving the success rate of UAV radar against dilution passive decoy jamming. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Radar

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Suppression of Actuator Nonlinearities Based on the Cascade Active Disturbance Rejection Approach

Suppression of Actuator Nonlinearities Based on the Cascade ...

引用

2019 IEEE International Conference on Unmanned systems, ICUS 2019

作者： Mingjun, Wei Cheng, Xu Wanhai, Hu Hua, Ji Feng, Gao Beijing Electro-Mechanical Engineering Institute Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China Aviation Institute of Technology of CASIC Beijing China

ISBN: (纸本)9781728137926

In this paper, influences of actuator nonlinearities and their suppression methods are studied. Firstly, the influences of the dead zone and backlash characteristics of the actuator on the control performance of statically unstable missiles are analyzed in detail. Then based on the cascade control method and the active disturbance rejection control (ADRC) theory, a nonlinear "double-layer compensation" suppression method for the actuator nonlinearities is proposed. Finally, the simulation verification is carried out. Simulation results show that the "double-layer compensation" suppression method based on the cascade ADRC approach can significantly suppress the adverse effects such as system self-sustaining oscillation caused by actuator nonlinearities, and effectively improve the control performance of the statically unstable missile. © 2019 IEEE.

关键词： Disturbance rejection

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An Approach for Upper Limb Movement Intention Recognition Using EEG and sEMG Fusion based on the MCPSA-CIIM 5

An Approach for Upper Limb Movement Intention Recognition Us...

引用

5th World Robot Conference Symposium on Advanced Robotics and Automation, WRC SARA 2023

作者： Zhang, Weiming Zhang, Xiaodong Xu, Cheng Zhou, Guchuan Zhang, Teng Wang, Yu Xi'an Jiaotong University Shaanxi Key Laboratory of Intelligent Robot School of Mechanical Engineering Shaanxi Xi'an China Science and Technology on Complex System Control and Intelligent Agent Cooperative Laboratory Beijing China

ISBN: (纸本)9798350307320

The upper limb motion intention recognition method based on electroencephalography (EEG) and surface electromyography (sEMG) fusion has achieved significant results in fields such as prosthetic control. However, most existing fusion methods use manual means to select features, which cannot capture temporal and spatial features at different scales, and ignore the correlation features between the two types of signals. To address these issues, this article proposes a fusion recognition method for upper limb motion intention EEG and sEMG based on Multi-scale Convolution, Polarized Self-Attention, and Cross Intelligence Integration Module. This article extracts multidimensional temporal and spatial features of EEG and sEMG through multi-scale convolution, and introduce polarized self-attention mechanism to filter the extracted multi-scale features. Simultaneously using cross enhancement strategy to extract correlation features between EEG and sEMG. Finally, the features are input into the classification network for recognition. This method was validated on the Jeong database, and the results showed that compared with CNN-LSTM and EEGNet, the recognition accuracy of this method increased by 2.63% and 3.15%, respectively. © 2023 IEEE.

关键词： Electroencephalography

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UAV Typical Index Evaluation Method Based on Improving Evidence Theory

UAV Typical Index Evaluation Method Based on Improving Evide...

引用

International Conference on Autonomous Unmanned systems, ICAUS 2021

作者： Geng, Huapin Suo, Bin Tong, Jiahui Science and Technology on Complex System Control and Intelligent Agent Cooperative Laboratory Beijing China Beijing Electro-Mechanical Engineering Institute Beijing China Southwest University of Science and Technology Mianyang China

ISBN: (纸本)9789811694912

It is an effective way to get more accurate results of UAV performance evaluation by fusing the data of infield test and outfield test. The common Bayes multi-source data fusion method can make comprehensive use of multiple information types while ensuring the decision risk as small as possible, but there are some risks, such as insufficient data utilization and small sample data being "submerged" by large sample data in the fusion. Due to the different scale and credibility of multi-source data, a non-uniform distribution probability sampling method is proposed based on evidence theory for the same sample space to avoid the risk of small sample data being "drowned" by large sample data;meanwhile, for the situation that the fusion weight mainly depends on the evaluation of experts is not objective enough, a comprehensive weight confirmation method of multi-source test data is proposed based on credibility measurement so as to realize the comprehensive evaluation of performance indicators based on multi-source data. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Unmanned aerial vehicles (UAV)

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Adaptive optimal output regulation: A parametric Lyapunov equation approach 5

Adaptive optimal output regulation: A parametric Lyapunov eq...

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5th International Conference on control, Robotics, and intelligent system, CCRIS 2024

作者： ul Aabidin Lodhi, Zain Jiang, Huaiyuan Center for Control Theory and Guidance Technology Harbin Institute of Technology Harbin China National Key Laboratory of Complex System Control and Intelligent Agent Cooperation Harbin China

ISBN: (数字)9781510685871

ISBN: (纸本)9781510685864

This article delves into a data-driven approach for solving the adaptive optimal output regulation problem in continuous-time linear systems with uncertain dynamics. Employing a class of parametric Lyapunov equations in conjunction with a nominal system model, the initial stabilizing feedback gain is determined to initiate the iterative method. Then, by utilizing a policy-iteration-based technique, we design an optimal control policy to achieve precise output tracking and disturbance rejection. The prescribed convergence characteristics of the closed-loop system directly result from the properties embedded within the solution of the parametric Lyapunov equation. The applicability and performance of the proposed method are demonstrated through a numerical example involving an input-constrained double integrator system. © 2024 SPIE.

关键词： Continuous time systems

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Relative Position-Based Collaborative Navigation for Cluster UAVs 7th

Relative Position-Based Collaborative Navigation for Cluster...

引用

7th Chinese Conference on Swarm Intelligence and Cooperative control, CCSICC 2023

作者： Sheng, Danting Cheng, Jin Li, Fengyi Hao, Mingrui Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China Aerospace Science and Industry Group Intelligent Technology Research Institute Co. Ltd. Beijing100074 China

ISBN: (纸本)9789819733316

The inertial equipment carried by UAVs without satellite signal assistance will accumulate errors over time, which cannot meet the requirement of obtaining high-precision cluster navigation information for cluster UAVs in long-duration flights. Aiming at this problem, a scheme for cooperative navigation of cluster UAVs based on relative position assistance is proposed. Firstly, the state equations of the cooperative navigation system are established by modeling the errors of inertial devices of low-precision UAVs;secondly, the relative position information of low-precision UAVs and high-precision UAVs as well as other low-precision UAVs transmitted between UAVs through the data chain is taken as the observation equation;finally, the inertial errors of low-precision UAVs are compensated by using the traceless Kalman filtering for the error compensation, which improves the navigation accuracy. After 30 min simulation results show that the cooperative navigation scheme converges the velocity and position errors of the low-precision UAV to 0.5 m/s and 5 m, respectively, which improves the navigation accuracy greatly. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Unmanned aerial vehicles (UAV)

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Indicators and Validation Methods for Swarm Situational Awareness Assessment of Uncrewed Aerial Vehicles 1

引用

7th Chinese Conference on Swarm Intelligence and Cooperative control, CCSICC 2023

作者： Zhang, Hang Song, Chuang Li, WeiXue Hao, Mingrui School of Software Northwestern Polytechnical University Shaanxi Xi’an710072 China Science and Technology On Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China

ISBN: (数字)9789819733323

ISBN: (纸本)9789819733316

Swarm situational awareness technology for uncrewed aerial vehicles (UAVs) is a core technology for mastering environmental information and gaining decision-making advantages. However, evaluation indicators and validation methods for situational awareness technology have always been lacking. This article thoroughly investigates the evaluation methods for situational awareness technology indicators both domestically and internationally. By analyzing the application scenarios of UAV group situational awareness technology, this article proposes an evaluation indicator system and mathematical simulation validation method for situational awareness technology. Finally, the design process and actual verification results of each indicator in the evaluation indicator system are explained in detail. The effectiveness of the evaluation indicator is demonstrated through simulation and comparative research, which further proves the reliability of the validation method. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Decision making

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Generating infrared image from visible image using Generative Adversarial Networks

Generating infrared image from visible image using Generativ...

引用

2019 IEEE International Conference on Unmanned systems, ICUS 2019

作者： An, Lei Zhao, Jiajia Di, Huijun Beijing Institute of Technology School of Computer Science and Technology Beijing China Beijing Electro-Mechanical Engineering Institute Science and Technology on Complex System Control and Intelligent Agent Coorperation Laboratory Beijing China

ISBN: (纸本)9781728137926

Infrared images have properties that are unaffected by illumination compared to visible images, object can be clearly recognized at day or night. Therefore, it is a better choice to use infrared images when training deep learning algorithms in unmanned systems. However, how to obtain a large number of infrared images makes it possible to train deep learning algorithm, which is the focus of our attention. In contrast to difficulties in direct shooting, computer simulations can generate large infrared images from visible images. But models that are trained on simulated data usually do not translate well to real scenarios. To bridge the domain gap between simulated and real infrared images, we exploit recent advances in paired image-to-image translation. We extend Pixel2Pixel to generate infrared image from visible image and propose a novel way of multilayer semantic information fusion, which significantly improves the quality of generated images. Finally, the image generated by our proposed PixelPro network is almost consistent with the real image distribution, achieved the purpose of expanding the dataset. © 2019 IEEE.

关键词： Generative adversarial networks

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