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Chinese Automation Congress (CAC)

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

ISBN: (数字)9781728176871

ISBN: (纸本)9781728176888

Nonlinear control has led to several great achievements for attitude control in virtual simulation environments, where the system model can be simplified to meet the application condition of those traditional nonlinear control algorithms. However, only a few of those algorithms can be applied to a practical Hypersonic Aircraft system, which suffers from uncertainties, multi-constraints, and various noises. To solve those problems effectively, in this paper, a novel reinforcement learning framework based on PI2 is proposed, wherein three kernel techniques are introduced. Firstly, a generalized path- integral-control approach is proposed to obtain the numerical solution of a stochastic dynamic model, wherein the calculation of the gradient and matrix inversion is avoided to ensure fast and reliable training convergence. Secondly, an action smooth method is used to strengthen the ability of the controller to resist noise. Thirdly, a novel RL algorithm combined with soft constrained techniques is illustrated to address the constrained nonlinear control problem. Several experiments are carried out and analyzed to demonstrate the outstanding performance of the CS-PI2.

关键词： Training Uncertainty Attitude control Atmospheric modeling Stochastic processes Resists Aircraft

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Multi-agent Cooperative Search based on Reinforcement Learning

Multi-agent Cooperative Search based on Reinforcement Learni...

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IEEE International Conference on Unmanned systems (ICUS)

作者： Yinjiang Sun Rui Zhang Wenbao Liang Cheng Xu Beijing Electro-Mechanical Engineering Institute Beijing China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China

ISBN: (数字)9781728180250

ISBN: (纸本)9781728180267

Regional cooperative search is an important scenario for Unmanned Aerial Vehicle (UAV) fleet. It is difficult for the UAV fleet to adapt to the dynamic environment by using traditional search method, which needs pre-planning. In this paper, a reinforcement learning approach is employed to train the UAV agents to search without pre-determined strategies. By designing reward function, state and action spaces, agents can learn to make decisions all by themselves based on their own observations and cooperate with each other effectively. The proposed method is experimentally validated by numerical simulations, and the result show that the UAV fleet can complete task with a pretty high coverage and few repetitions at the same location.

关键词： Zirconium Radio frequency Hafnium Erbium

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Study on the Modeling Method of Sip Target for Uav-borne Bi-SAR

Study on the Modeling Method of Sip Target for Uav-borne Bi-...

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IEEE International Conference on Unmanned systems (ICUS)

作者： Guijie Diao Jia Huitong Hong Ni Zhe Liu Ningbo Gon Liang Yang Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing hina Beijing Electro-mechanical Engineering Institute Beijing China

ISBN: (数字)9781728180250

ISBN: (纸本)9781728180267

To solve the simulation problem of uav-borne bi-static synthetic aperture radar (SAR) for sea surface targets, a scattering signatures modeling method of sea-surface target for bi-static imaging radar is proposed, based on the coupling scattering mechanism between the ship and sea surface. A bistatic scattering signature signal model for sea-surface target in conjunction with high frequency asymptotic techniques for electromagnetic (EM) scattering calculation, the multi-path EM scattering model, the time-evolving complex reflection coefficient model and the ship motion dynamics. The time varying scattering signatures for a typical ship on time evolving sea-surface are simulated and analyzed.

关键词： Sea surface Imaging Radar imaging Radar scattering Reflection coefficient Marine vehicles Synthetic aperture radar

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Cross-cycle iterative unmanned aerial vehicle reentry guidance based on reinforcement learning

Cross-cycle iterative unmanned aerial vehicle reentry guidan...

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2019 IEEE International Conference on Unmanned systems, ICUS 2019

作者： Cheng, Yang Shui, Zunshi Xu, Cheng Feng, Tianyu Jiang, Yiyang Beijing Aerospace Technology Research Institute Beijing China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China

ISBN: (纸本)9781728137926

The traditional predictive correction algorithm requires a large number of iterative calculations for the predicted trajectory, which greatly occupies a large amount of computing resources, so that the real-time solution of the guidance command can not be guaranteed, and the guidance accuracy will have a large impact. And the prediction correction guidance requires the algorithm to have the ability of selfadaptation and intelligent learning. Therefore, this paper proposes a cross-cycle iterative hypersonic UAV predictive correction guidance method based on reinforcement learning. The parametric control variable (CVP) method is used to construct the parametric model of the guidance command. The actor-critic-based reinforcement learning method is used to solve the guidance command in real time, and the guidance information is effectively transmitted in the adjacent guidance solution cycle. The guidance error converges to within the allowable accuracy range during the cross-cycle iteration. Monte Carlo simulation shows that the proposed method has good adaptability to initial conditions and flight parameter uncertainty, and can guarantee the real-time performance of the guidance command while achieving high-precision guidance. © 2019 IEEE.

关键词： Reinforcement learning

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Aircraft Autonomous Positioning Based on a Coarse to Fine Multi-modal Image Registration Scheme

Aircraft Autonomous Positioning Based on a Coarse to Fine Mu...

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Power Electronics, Computer Applications (ICPECA), IEEE International Conference on

作者： Fangde Sun Wenxing Fu Xiaohui Lu Jing Dong Songlai Han School of Aeronautics and Astronautics Central South University Changsha China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China People’s Liberation Army 91039th Unit Beijing China Aerospace Science and Engineering National University of Defense Technology Changsha China

ISBN: (数字)9781728190044

ISBN: (纸本)9781728190051

In this paper, an autonomous positioning method based on coarse-to-fine multi-modal image matching is proposed for UAV navigation in GPS denied environment. Coarse image matching refers to roughly determining the approximate position of the real-time image in the reference image. Fine image matching refers to iterative matching around the position obtained by coarse image matching to achieve more accurate matching results. Besides, RANSAC is adopted to eliminate the outliers of image matching. After getting the result of image matching, we use PNP to estimate the position of the aircraft. The proposed position method has the advantages of high accuracy and reliability. The experimental results show that the average error of the position of the proposed method is 59%.

关键词： Image registration Image matching Aerospace electronics Real-time systems Power electronics Reliability Aircraft

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Design of Reusable Effectiveness Evaluation Model Framework

Design of Reusable Effectiveness Evaluation Model Framework

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Chinese Control and Decision Conference, CCDC

作者： Shuang Zhang Wei Li Shenglin Lin Ming Yang Jiahui Tong Control and Simulation Center Harbin Institute of Technology Harbin China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China

ISBN: (数字)9781728158556

ISBN: (纸本)9781728158563

In order to make the effectiveness evaluation models of the weapon equipment system universal and flexible, and adapt to different evaluation objects, a framework of effectiveness evaluation model is designed. Next a series of modular and reusable effectiveness evaluation models are proposed under the framework. Each type of evaluation model is built based on IDEF0, and the corresponding input and output of each model are designed. To further improve reusability, several models are mathematically described and model interface is designed based on XML.

关键词： Indexes Data models Data mining Analytical models Mathematical model Optimization Adaptation models

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Application of Neutrosophic Multiple Criteria Decision Making in Unmanned system

Application of Neutrosophic Multiple Criteria Decision Makin...

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2019 IEEE International Conference on Unmanned systems, ICUS 2019

作者： Zhong, Yu Zhao, Jiajia Northwestern Polytechnical University School of Electronics and Information Xi'an China Control and Intelligent Agent Cooperation Laboratory Science and Technology on Complex System Bejing China

ISBN: (纸本)9781728137926

The multiple criteria decision making (MCDM) is universal and applicable for plenty of unmanned systems which are widely concerned in civil and military fields due to their adaptability and safety. The contributing factors of decision making in unmanned systems are complicated due to the inhomogeneity and nondeterminacy of environment and the relative importance of criteria. Consequently, these critical factors fail to be considered felicitously in many traditional methods. In this paper, a neutrosophic MCDM approach is proposed to mitigate this matter. The neutrosophic set generated from collected information of multiple sources would be fused by the aggregation operator to obtain the decision matrix, then the weights of criteria would be obtained via the proposed method based on the decision matrix, and the decision results could be determined by the aggregation operator and defuzzification method of aggregated neutrosophic set. The application of neutrosophic set can handle numerous uncertain matters in unmanned systems. Finally, an example was provided to illustrate the reasonableness and stability of the proposed approach. © 2019 IEEE.

关键词： Decision making

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Design of a compact ultra-wideband MIMO antenna

Design of a compact ultra-wideband MIMO antenna

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IET International Radar Conference 2018, IRC 2018

作者： Youcheng, Wang Yanjiao, Yang Qingxi, Chi Hucheng, Pei Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing Electro-Mechanical Engineering Institute Beijing China

A compact ultra-wideband (UWB) multiple-input multiple-output (MIMO) antenna is presented. The MIMO antenna consists of four monopoles which are printed on FR4 substrate, whose impedance bandwidth is from 2 to 12 GHz, and the isolation of two adjacent antennas is less than−20 dB in mostly frequency band. The current distribution of the antenna is discussed by simulation, and the radiation characteristics of the antenna are improved by increasing the parasitic radiation patch and digging holes in the radiation patch. Four monopoles are placed with polarisation orthogonality, and the adjacent units are separated by slot to cut off the coupling current on the floor, thus effectively improving the isolation of the antenna. © 2019 Institution of Engineering and Technology. All rights reserved.

关键词： Electric impedance

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Failure Mode and Effects Analysis of UAV Power system Based on Generalized Dempster-Shafer Structures

Failure Mode and Effects Analysis of UAV Power System Based ...

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2019 IEEE International Conference on Unmanned systems, ICUS 2019

作者： Zhang, Zhuo Hao, Mingrui Northwestern Polytechnical University School of Electronics and Information Xian China Intelligent Agent Cooperation Laboratory Science and Technology on Complex System Control Beijing China

ISBN: (纸本)9781728137926

The unmanned aerial vehicle(UAV) power system consists of components that provide flight power for the UAV, which mainly includes three parts: motor, electronic speed controller(ESC), and battery. Since the UAV always operates in the open air, which requires high stability of the power system, the failure mode and effects analysis(FMEA) is particularly significant and it has been widely used to examine potential failures in systems or components. However, the traditional FMEA method has many unreasonable points. In order to better deal with the uncertainty and improve the stability of the UAV power system, we propose a FMEA method which is based on the generalized Dempster-Shafer structures, the failure modes are comprehensively analyzed and the risks are ranked by combining the characteristic information of risk factors with the generalized evidence theory. The new method can not only deal with the uncertainty of risk assessment, but also further improve the reliability of effects analysis. In addition, the FMEA experiment of the UAV power system is carried out in this paper. The experimental results show that the method is effective for practical applications. © 2019 IEEE.

关键词： Fuzzy set theory

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An Anti-Rolling Control Method of Rudder Fin system Based on Adrc Decoupling and Ddpg Parameter Adjustment

SSRN

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SSRN 2022年

作者： Sun, Mingxiao Zhang, Wenyu Zhang, Yongde Luan, Tiantian Yuan, Xiaoliang Li, Xiaogang School of Automation Harbin University of Science and Technology No.52 Xuefu Road Nangang District Heilongjiang Province Harbin City150080 China Heilongjiang Provincial Key Laboratory of Complex Intelligent System and Integration Harbin University of Science and Technology No.52 Xuefu Road Nangang District Heilongjiang Province Harbin City150080 China Key Laboratory of Advanced Manufacturing and Intelligent Technology Ministry of Education Harbin University of Science and Technology No.52 Xuefu Road Nangang District Heilongjiang Province Harbin City150080 China Wuxi CREG Urban Rail Transit Equipment Co. Ltd No. 1061 Jiaoshan Road Xishan Development Zone Jiangsu Province Wuxi214000 China

To achieve high-precision attitude control of ships, the output delay, state coupling, and controller parameter maladjustment of the rudder fin joint anti-rolling system are studied. A predictive anti-rolling method based on active disturbance rejection control (ADRC) and deep deterministic policy gradient (DDPG) is proposed. The external forces on the ship are analyzed, and a three-degree-of-freedom mathematical model considering rolling, yawing, and pitching is established. The model is decoupled using the idea of ADRC total disturbance for the state coupling problem, then the pitch ADRC controller and the roll-yaw predictive observer are designed respectively. In pitch ADRC, the nonlinear extended state observer (NLESO) is used to observe the total disturbance between models. And the total disturbance observations are feedforward compensated to the error control law. As a result, the rapidity of reference output tracking and robustness of total disturbance are realized. The roll-yaw predictive observer solves the output delay by feeding the predicted output back to the controller instead of the actual output. To ensure the accuracy of the prediction output, the DDPG algorithm is introduced to modify the parameters of the prediction observer in real-time. Finally, state constraints are added to solve the rudder angle and fin angle control laws. © 2022, The Authors. All rights reserved.

关键词： Controllers

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