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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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Condition Monitoring for Railway Point Machines Based on Sound Analysis and Support Vector Machine

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Chinese Journal of Electronics 2020年第4期29卷 786-792页

作者： SUN Yongkui CAO Yuan XIE Guo WEN Tao School of Electronic and Information Engineering Beijing Jiaotong University National Engineering Research Center of Rail Transportation Operation and Control System Beijing Jiaotong University Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology

Railway point machines(RPMS) are one of the key equipments in the railway system to switch different routes for the *** monitoring for RPMs is a vital measure to keep train operation safe and *** convenience and low cost into consideration, a novel intelligent condition monitoring method for RPMs based on sound analysis is ***-domain and frequency-domain features are obtained,and normalized using z-score standardization method to eliminate the influences of different *** particle swarm optimization(BPSO) is utilized to select the most significant discrimination feature *** effects of the selected optimal features are verified using Support vector machine(SVM), 1-Nearest neighbor(1 NN), Random forest(RF), and Naive Bayes(NB).Experiment results indicate SVM performs best on identification accuracy and computing cost compared with the other three *** identification accuracies on normal switching and reverse switching processes reach100% and 99.67%, respectively, indicating the feasibility of the proposed method.

关键词： Condition monitoring Sound analysis Railway point machines(RPMs) Binary particle swarm optimization(BPSO) Support vector machine(SVM)

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Status and Application of Artificial Intelligence-Based Cooperative Positioning and Navigation Technology for UAV Clusters 1

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3rd International Conference on Autonomous Unmanned systems, ICAUS 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 Intelligent Science and Technology Academy Limited of CASIC Beijing100041 China

ISBN: (数字)9789819710911

ISBN: (纸本)9789819710904

Aiming at the UAV cluster cooperative navigation, this paper tries to summarize the development experience and existing results on two issues, namely, the application of filtering and artificial intelligence in UAV cluster cooperative navigation. The application of filtering in UAV cluster cooperative navigation briefly describes the application of Kalman filtering and extended Kalman filtering, traceless Kalman filtering and other nonlinear filters, intelligent optimization algorithms combined with particle filtering in cooperative navigation. Artificial Intelligence Methods in Cooperative Navigation of UAV Clusters describes the application of deep feed-forward networks, brain-like information fusion methods based on integrated learning, multivariate interpolation of radial-based neural networks and Kalman filtering combined in the field of cooperative navigation. The results of existing applications of filtering and artificial intelligence in UAV cluster cooperative navigation are analyzed and summarized, and the future development of the field is outlooked. © Beijing HIWING Scientific and Technological Information Institute 2024.

关键词： Kalman filters

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Method for Evaluating the Performance of Aircraft Collaborative Decision-Making Based on Dynamic Bayesian Network

Method for Evaluating the Performance of Aircraft Collaborat...

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2024 International Conference on Electronics and Devices, Computational Science, ICEDCS 2024

作者： Zhang, Wenbo Yu, Boxiao Tong, Jiahui Li, Jing Beijing Electro-Mechanical Engineering Institute National Key Laboratory of Complex System Control and Intelligent Agent Cooperation Beijing China Beijing Institute of Technology School of Computer Science and Technology Beijing China

ISBN: (纸本)9798331527624

This research addresses the challenge of assessing equipment decision-making effectiveness in environments characterized by uncertainty and multiple influencing factors. We propose a novel approach involving the creation and optimization of a dynamic Bayesian network-based model tailored for equipment decision-making processes. The model facilitates a systematic evaluation of decision-making effectiveness by incorporating various factors, including equipment performance, environmental conditions, and enemy defensive capabilities. A comprehensive assessment system has been developed to simulate the penetration capabilities of different equipment through enemy defenses. Moreover, this study identifies potential errors in the effectiveness evaluation model by analyzing its performance in typical scenarios, pinpointing areas for enhancement. © 2024 IEEE.

关键词： Decision-making Dynamic Bayesian networks Equipment Simulation Uncertainty Management

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Improved ICCP Algorithm and Its Application in Gravity Matching Aided Inertial Navigation system 33

Improved ICCP Algorithm and Its Application in Gravity Match...

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第三十三届中国控制会议

作者： LIU Meiqi WANG Bo DENG Zhihong FU Mengyin School of Automation and National Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology

ISBN: (纸本)9789881563842

Considering two disadvantages in traditional gravity matching aided inertial navigation system,low matching accuracy and error accumulation,we propose an improved gravity matching algorithm and aided method for inertial navigation *** of using the sequence sampling,the single point sampling is applied to improve the structure of proposed algorithm,enhancing the matching speed and *** the aided navigation system method,we use combination of Sage-Husa adaptive filter and strong-tracked Kalman filter to make further optimal estimation of the matching *** results show the effectiveness of the real-time ICCP algorithm and the combined filter *** to the traditional methods,proposed method provides higher matching and navigation accuracy.

关键词： gravity aided navigation,single-point sampling,combined filter

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Aircraft Middle and Final Stage Attitude control on Fully Actuated system Theory

Aircraft Middle and Final Stage Attitude Control on Fully Ac...

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Fully Actuated system Theory and Applications (CFASTA), Conference on

作者： Xinyu Liu Mingrui Hao Yu Fan Yan Zhen Wendi Sun National Key Laboratory of Complex System Control and Intelligent Agent Cooperation Beijing China

ISBN: (数字)9798350373691

ISBN: (纸本)9798350373707

This paper takes the attitude control of the middle and final stages of the aircraft as the research background, and explores a new nonlinear control method for the strong nonlinearity, strong coupling, fast time-varying and uncertainty characteristics of the aircraft. A second-order fully actuated system model of the aircraft is constructed, which is starting from the six degree of freedom mathematical model, including aerodynamic coupling and control coupling. It is a nonlinear model, including roll, yaw and pitch full three channels. Also, the paper designed an attitude controller on fully actuated system, which is based on the PD control method, and proved the stability of the controller through Lyapunov stability analysis method. Then, the controller is integrated into the aircraft simulation, and mathematical simulation verification is carried out under benchmark conditions, achieving good attitude control effect.

关键词： Couplings Attitude control Atmospheric modeling Benchmark testing Mathematical models Stability analysis Aircraft manufacture

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Novel Terminal Guidance Law for Blended Aero and Reaction-Jet Missile Based on Nonlinear Disturbance Observer 1

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International Conference on Autonomous Unmanned systems, ICAUS 2021

作者： Zhao, Hui Xu, Cheng Qin, Hehong Wang, Hao Hu, Ying Institute of Mechanical and Electrical Engineering Beijing100072 China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100072 China

ISBN: (数字)9789811694929

ISBN: (纸本)9789811694912

In this paper, an effective terminal guidance law is proposed for intercepting large maneuvering targets for the reaction jet control (RCS) missile. The guidance law takes the real dynamic characteristics of the control system into account, not only including the second order bandwidth filtering response of the autopilot, but also containing the discrete reaction jet force characteristics. For the target maneuver in the guidance loop, a new nonlinear disturbance observer (NDO) with fast convergence is presented on the premise of not obtaining the prior information of the target. Target acceleration and other uncertainties are estimated and compensated in the guidance law as a feed-forward input. Then the global stability of the system is proved by the appropriate Lyapunov function. The simulation results show that the guidance law can effectively intercept the maneuvering target and obtain good guidance precision. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Lyapunov functions

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A LSTM-based method for simulation execution validity evaluation 33

A LSTM-based method for simulation execution validity evalua...

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33rd European Modeling and Simulation Symposium, EMSS 2021

作者： Wang, YuLun Li, Wei Li, Jing Control and Simulation Center Harbin Institute of Technology Harbin150080 China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China

This paper improves the concept of simulation execution validity and a methodology to assess the complex simulation system. As the complexity of the simulation system gradually rises, the magnitude of the simulation data obtained continues to increase, which makes it extremely difficult for experts to provide expert knowledge to evaluate the execution validity of the simulation system. More precisely, the essence of execution validity is to dig out the hidden relationships in the simulation time series data and complete the classification task whether it is valid. Considering that machine learning can better complete the two tasks of mining data features and classification, this paper adopts long short-term memory, a neural network used to process time series data, to evaluate the execution validity. Finally, an experiment is conducted on a simulation system, and the results show that the evaluation method based on LSTM can accurately evaluate the validity of the simulation system, and can greatly improve the efficiency of evaluation. © 2021 The Authors.

关键词： Long short-term memory

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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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Robust composite control of telescopic wing morphing aircraft with control allocation

Robust composite control of telescopic wing morphing aircraf...

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2021 China Automation Congress, CAC 2021

作者： Wang, Zijian Hou, Mingzhe Hao, Mingrui Center for Control Theory and Guidance Technology Harbin Institute of Technology Harbin China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China

ISBN: (纸本)9781665426473

In this paper, the problem of anti-disturbance, anti-saturation and fixed-time control for a class of telescopic wing morphing aircraft is studied. The telescopic wing morphing aircraft treats the variable wingspan as an extra control input to construct the dynamic model of the morphing-aided maneuver. According to the model characteristics, the controller design is divided into two loops: the speed loop and the attitude loop. Through a fixed-time continuous feedback control scheme, fixed time of the tracking reference trajectory is ensured. By combining the integral sliding mode control (ISMC) method with super-twisting control (STC), the uncertainties of aerodynamic coefficients and external disturbances are overcome. In addition, the anti-saturation problem of the aircraft actuator is solved by the initial solution correction method based on Null-space augmented solutions. The simulation result shows that the designed algorithm has great tracking performance, while the robustness and anti-saturation performance are guaranteed. © 2021 IEEE

关键词： Robust control

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