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2019 IEEE International Conference on Unmanned systems, ICUS 2019

作者： Siting, Peng Qian, Zhao Yichao, Ma Cheng, Xu Beijing Electro-Mechanical Engineering Institute Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China

ISBN: (纸本)9781728137926

As an important device for target interception, The seeker is used to search, recognize and track the target autonomously. Infrared semi-strapdown seekers are widely used in applications due to their low cost and small size. However, one non-negligible disadvantage of semi-strapdown infrared seekers is that the observability of target tracking model is poor, especially for the interception of high-speed maneuvering weapons. In this paper, the target tracking model ( i.e., the filtering estimation model) based on the infrared simi-strapdown seeker is established. The observability of the target tracking model is analyzed and the evaluation method of the observability is studied. Simulation results show that the observability of the filtering estimation model can be improved by increasing the relative motion between missile and target which results in faster changes of the line-of-sight (LOS) angle. According to the results on the observability analysis, the desired trajectory is obtained through the design of proper guidance law. Nonlinear filtering algorithm is also introduced for the trajectory design. Simulation experiments are conducted for the integrated filtering and guidance, and simulation results illustrate the effectiveness of the proposed observability enhancement method. © 2019 IEEE.

关键词： Observability

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Non-Singular Fixed-Time Robust Containment control for Autonomous Surface Vehicles

SSRN

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SSRN 2023年

作者： Ma, Junda Sun, Hefang Tan, Chong Zhao, Tianyuan Liu, Ke College of Automation Harbin University of Science and Technology Harbin150000 China Provincial Key Laboratory of Complex Intelligent System and Integration Harbin150000 China College of Journalism and Communication Jilin University Changchun130000 China College of Measurement and Control Technology and Communication Engineering Harbin University of Science and Technology Harbin150000 China

For the containment control problem of autonomous surface vehicles with external disturbances, a novel non-singular fixed-time control scheme is developed, where the multi-ship system consists of real leaders and followers. In contrast with traditional containment cases studied in most of the existing literature, the real leaders are required to track the desired trajectories, and the followers need to get into the convex hull spanned by the real leaders in fixed time. The method for solving the fixed-time containment control problem is divided into the following steps: Firstly, a fixed-time disturbance observer is designed to estimate the external disturbance for the leaders and the followers, and the estimation result is used to compensate for the input of the control system;Second, combined with fixed-time stability theory and a switch function, a non-singular fixed-time trajectory tracking controller for leaders is designed, such that the position tracking error could be bounded within a fixed time;Third, to achieve formation efficiently, a non-singular fixed-time containment controller strategy incorporating with graph theory is proposed for coordinating followers, such that the fixed-time stability can be ensured. Finally, simulation examples are given to demonstrate the effectiveness of the proposed method. © 2023, The Authors. All rights reserved.

关键词： Graph theory

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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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A SINS Error Correction Approach Based on Dual-Threshold ZV Detection and Cubature Kalman Filter

A SINS Error Correction Approach Based on Dual-Threshold ZV ...

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IEEE International Conference on systems, Man and Cybernetics

作者： Ruijie Xu Shichao Chen Wenqiao Sun Yisheng Lv Jialiang Luo Ying Tang The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences College of Information Science & Technology Beijing University of Chemical Technology Beijing China The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems The Center of National Railway Intelligent Transportation System Engineering and Technology Institute of Automation Chinese Academy of Sciences China Academy of Railway Sciences Corporation Limited Beijing China China Academy of Railway Sciences Corporation Limited Transportation and Economics Research Institute and the Center of National Railway Intelligent Transportation System Engineering and Technology Beijing China The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences Beijing China The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences School of Information Engineering China University of Geosciences Beijing Beijing China Department of Electrical and Computer Engineering Rowan University Glassboro USA

Global Navigation Satellite systems (GNSS) can provide real-time positioning information for outdoor users, but cannot for indoor scenarios or heavily occluded outdoor scenarios. Strap-down Inertial Navigation system (SINS) are widely used to locate people in complex interior or heavily occluded outdoor scenarios due to its light weight and low power consumption. However, IMU of SINS are noisy, and the sampling data error is large, which is a divergence of the error with time. Therefore, it will generate a positioning accumulation error, which affects the final positioning accuracy. The problem of cumulative IMU errors is usually dealt with by Zero-Velocity Update (ZUPT). The zero-velocity detection part of basic ZUPT method usually uses a single threshold to determine the gait of pedestrian, which often has the problem of gait misjudgment and omission. To address these problems, this paper proposes a composite conditional detection method to solve the problem of misjudgment in the zero-velocity interval. In addition, we redesign the zero-velocity update algorithm and uses the Cubature Kalman filter (CKF) for pedestrian positioning error correction. The experimental results demonstrate that the proposed ZUPT method based on dual-threshold detection can better detect the interval between pedestrian motion and stationery than ones with single threshold. The zero-velocity update algorithm based on CKF has higher performance than conventional EKF and UKF methods, which constrains the cumulative error of SINS to about 0.2% of the whole walking distance.

关键词：

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A non-uniform Gauss pseudospectral method based on curvature information for dynamic optimization problem

A non-uniform Gauss pseudospectral method based on curvature...

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第32届中国过程控制会议(CPCC2021)

作者： Lu Lv Qian Zhang Jianzhong Su Wenhai Wang Jianquan Yuan Zijian Tian Zhenghui Zhang Long Xiao Zeyin Zhang Xinggao Liu Zhejiang University NGICS Platform State Key Laboratory of Industrial Control TechnologyControl DepartmentZhejiang University Tianjin Jinhang Institute of Technical Physics Science and Technology on Complex System Control and Intelligent Agent Cooperative Laboratory Mathematics Department Zhejiang University

Dynamic optimization for hypersonic reentry vehicle(HRV) is a challenge for complex nonlinear constraints during a global strike *** to the strong nonlinearity of HRV,it is difficult to guarantee the precision of complex constraints on non-collocation points with traditional Gauss pseudospectral method(GPM).A novel approach which provides an optimal control strategy considering the above challenges is then ***,an adaptive mesh refinement strategy based on curvature information is presented to improve the accuracy of GPM.A collocation point redistribution method based on error analysis is then proposed to further improve the accuracy of the ***,a detection mechanism is proposed to correct the results on-line when the path constraint is not *** proposed approaches are finally applied to a classic HRV problem and compared with other literature work in *** research results validate the effectiveness of the proposed methods.

关键词： nonlinear optimal control Gauss pseudospectral method adaptive mesh refinement hypersonic reentry vehicle

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

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

引用

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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Parameter adaptive terminal sliding mode control of flexible coupling air-breathing hypersonic vehicle

Parameter adaptive terminal sliding mode control of flexible...

引用

AIAA Scitech Forum, 2020

作者： Jin, Hengxian Chen, Haibing Lin, Wei Xu, Cheng School of Energy And Power Engineering Beihang University Beijing100191 China Airworthiness Technologies Research Center School of Transportation Science and Engineering Beihang University Beijing100191 China School of Transportation Science and Engineering Beihang University Beijing100191 China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory China

ISBN: (数字)9781624105951

ISBN: (纸本)9781624105951

Flexible air-breathing hypersonic vehicles have very wide range of flight and show significant and complex aerodynamic, scramjet propulsion system, flight dynamic and elastic coupling characteristics, which usually are highly nonlinear. These result in huge uncertainties, parameter perturbation and internal disturbance, which can no longer be ignored, and therefore, extreme difficulties for flight control design. A unique parameter adaptive nonsingular terminal sliding mode method is proposed for longitudinal control law design of a flexible coupling air-breathing hypersonic vehicle. Other than conventional adaptive terminal sliding mode control, this method uses adaptive reaching law gain instead of additional adaptive compensation term to handle the uncertainty to improve robustness. The stability of the close loop system is proved via a Lyapunov way. The longitudinal tracking control law for velocity and angle of attack is designed based on a rigid dynamic model of a flexible air-breathing hypersonic vehicle. A strong coupling model of this vehicle, considering aerodynamic-scramjet engine-flight dynamic-elastic couplings, is established as the verification platform of control law designed. The remarkable differences of flight dynamics characteristics between this strong coupling model and the rigid body model can be seen, which mean the controller needs to endure very great uncertainty, unmodeled dynamics and other internal disturbance. Simulation based on the coupling model is carried on and results demonstrate that the control law designed has good performance and acceptable robustness. © 2020, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Hypersonic vehicles

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An empirical evaluation of attention-based multi-head models for improved turbofan engine remaining useful life prediction

arXiv

引用

arXiv 2021年

作者： Ayodeji, Abiodun Wang, Wenhai Su, Jianzhong Yuan, Jianquan Liu, Xinggao State Key Laboratory of Industrial Control Technology Control Department Zhejiang University Hangzhou310027 China Tianjin Jinhang Technical Physics Institute Tianjin300192 China Science and Technology on Complex System Control and Intelligent Agent Cooperative Laboratory Beijing100074 China

A single unit (head) is the conventional input feature extractor in deep learning architectures trained on multivariate time series signals. The importance of the fixed-dimensional vector representation generated by the single-head network has been demonstrated for industrial machinery condition monitoring and predictive maintenance. However, processing heterogeneous sensor signals with a single-head may result in a model that cannot explicitly account for the diversity in time-varying multivariate inputs. This work extends the conventional single-head deep learning models to a more robust form by developing context-specific heads to independently capture the inherent pattern of each sensor reading in multivariate time series signals. Using the turbofan aircraft engine benchmark dataset (CMAPSS), an extensive experiment is performed to verify the effectiveness and benefits of multi-head fully connected neurons, recurrent networks, convolution network, the transformer-style stand-alone attention network, and their variants for remaining useful life estimation. Moreover, the effect of different attention mechanisms on the multi-head models is also evaluated. In addition, each architecture's relative advantage and computational overhead are analyzed. Results show that utilizing the attention layer is task-sensitive and model dependent, as it does not provide consistent improvement across the models investigated. The result is further compared with five state-of-the-art models, and the comparison shows that a relatively simple multi-head architecture performs better than the state-of-the-art models. The results presented in this study demonstrate the importance of multi-head models and attention mechanisms to improved understanding of the remaining useful life of industrial assets. © 2021, CC BY.

关键词： Recurrent neural networks

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Self-Tuning Attitude control Design of Hypersonic Aircraft with Multi-Constraints Based on Soft-Constrained PI2 with Action Smooth

Self-Tuning Attitude Control Design of Hypersonic Aircraft w...

引用

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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Finite Time Cooperative Guidance Law for Multiple UAVs with Intermittent Communication Topologies

Finite Time Cooperative Guidance Law for Multiple UAVs with ...

引用

2019 IEEE International Conference on Unmanned systems, ICUS 2019

作者： Lyu, Teng Xu, Cheng Li, Hongchun Hu, Song Zhang, Daochi System Control and Intelligent Agent Cooperation Laboratory Science and Technology on Complex Beijing China Beijing Electro-mechanical Engineering Institute Beijing China

ISBN: (纸本)9781728137926

To solve the problem of multiple Unmanned Aerial Vehicles (UAVs) with intermittent communication topologies simultaneously attack a stationary target, a time cooperative guidance law is studied in this paper. First, a novel time cooperative guidance model for multiple UAVs is constructed based on UAVs-target relative motion equations. Then, a cooperative guidance law is designed based on consensus theory, which can ensure multiple UAVs' impact times realize finite time consensus under intermittent topologies. After UAVs' impact times become to be the same, traditional PN guidance law is applied in all UAVs to guarantee that the UAVs can attack the target precisely without influencing the consensus of impact times. Finally, the validity of the proposed method is shown by numerical simulations. © 2019 IEEE.

关键词： Topology

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