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Mobile Internet, Cloud Computing and Information Security (MICCIS), International Conference on

作者： Ying Zhang Yifei Zhao Beijing Aerospace Automatic Control Institute National Key Laboratory of Science and Technology on Aerospace Intelligent Control Beijing

ISBN: (数字)9798350389906

ISBN: (纸本)9798350389913

Based on the inference ability of Bayesian network under uncertain conditions and the advantages of GO method modeling, the Go-Bayesian network model is constructed based on the function of hibernation wake subsystem, information flow of hibernation wake up, GoBayesian network model operator conversion principle and conversion rules. Monte Carlo simulation reliability index was established to simulate the actual process of hibernate wake subsystem failure. Finally, the reliability result of hibernate wake subsystem obtained by simulation was compared with that obtained by GO-Bayesian model. The relative error was small, which verified the feasibility of GOBayesian model in reliability analysis of hibernate wake subsystem.

关键词： Cloud computing Analytical models Monte Carlo methods Computational modeling Information security Bayes methods Reliability

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Static Unstable STT Overload control on High-order Fully Actuated System Theory 6

Static Unstable STT Overload Control on High-order Fully Act...

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6th International Symposium on Autonomous Systems, ISAS 2023

作者： Liu, Xinyu Hao, Mingrui Zhen, Yan Fan, Yu Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China

ISBN: (纸本)9798350316155

This article proposes a joint overload controller for pitch and yaw channels on the high-order fully actuated system theory for a nonlinear lateral and longitudinal static unstable STT aircraft model. Firstly, a second-order fully actuated system model for aircraft overload was derived, and an optimal control method for lateral and longitudinal overload was designed. Through mathematical simulation verification of this controller and traditional PID controller, it is shown that the PID control method has significant shortcomings in nonlinear aircraft with coupling. However, high-order fully actuated system theory control method can better adapt to nonlinear and static instability problems, achieve stable tracking of aircraft overload commands, and have better rapidity. © 2023 IEEE.

关键词： System theory

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Powered-descent landing GNC system design and flight results for Tianwen-1 mission

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Astrodynamics 2022年第1期6卷 3-16页

作者： Xiangyu Huang Chao Xu Jinchang Hu Maodeng Li Minwen Guo Xiaolei Wang Yu Zhao Baocheng Hua Yunpeng Wang Beijing Institute of Control Engineering Beijing 100094China National Key Laboratory of Science and Technology on Space Intelligent Control Beijing 100094China

The powered-descent landing(PDL)phase of the Tianwen-1 mission began with composite backshell–parachute(CBP)separation and ended with landing-rover *** main tasks of this phase were to reduce the velocity of the lander,perform the avoidance maneuver,and guarantee a soft *** PDL phase overcame many challenges:performing the divert maneuver to avoid collision with the CBP while simultaneously avoiding large-scale hazards;slowing the descent from approximately 95 to 0 m/s;performing the precise hazard-avoidance maneuver;and placing the lander gently and safely on the surface of *** architecture and algorithms of the guidance,navigation,and control system for the PDL phase were designed;its execution resulted in Tianwen-1’s successful touchdown in the morning of 15 May ***,the Tianwen-1 mission achieved a historic autonomous landing with simultaneous hazard and CBP avoidance.

关键词： Tianwen-1 powered-descent landing(PDL) guidance,navigation,and control(GNC) backshell avoidance hazard avoidance

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Modified Gaussian Sum Mixed-Degree CKF for Relative Motion Estimation of Noncooperative Spacecraft

Modified Gaussian Sum Mixed-Degree CKF for Relative Motion E...

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2022 Chinese Automation Congress, CAC 2022

作者： Zhang, Shiyuan Lu, Shan Guo, Jing Xu, Chen Liu, Licheng Shanghai Aerospace Control Technology Institute Shanghai China Institute Shanghai Key Laboratory of Aerospace Intelligent Control Technology Shanghai Aerospace Control Technology Shanghai China

ISBN: (纸本)9781665465335

To improve the capability of acquiring relative motion information between non-cooperative spacecraft in proximity capture, the problem of relative state estimation is investigated in this paper. Considering the kinematic coupling caused by the transformation matrix introduced in the observation equation when the measurable center of form does not coincide with the unknown center of mass, the dynamical and measurement models are established respectively first. Then, in the presence of a strong nonlinear model and non-Gaussian measurement noise, a modified Gaussian sum mixed-degree spherical simplex-radial cubature Kalman filter (GS-MSSRCKF) is proposed to estimate the relative motion. Furthermore, the algorithm is modified to avoid the fault of GS-MSSRCKF caused by excessive measurement outliers. Finally, when GS-MSSRCKF is compared to a few filtering methods that have been previously suggested, the simulation results show an improvement in accuracy and a decrease in calculation time. © 2022 IEEE.

关键词： Motion estimation

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Rocket Self-learning control based on Lightweight Neural Network Architecture Search

Rocket Self-learning Control based on Lightweight Neural Net...

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2022 IEEE International Conference on Unmanned Systems, ICUS 2022

作者： Wang, Zhaolei Lu, Kunfeng Yu, Chunmei Yao, Na Wang, Ludi Zhao, Jikang Beijing Aerospace Automatic Control Institute Science and Technology on Aerospace Intelligent Control Laboratory Beijing China Beijing Aerospace Automatic Control Institute China Academy of Launch Vehicle Technology Beijing China

ISBN: (数字)9781665484565

ISBN: (纸本)9781665484565

Aiming at the problem that the traditional control law design process is complex and relies heavily on accurate mathematical models, this paper uses the Deep Deterministic Policy Gradient (DDPG) reinforcement learning to realize the self-learning of continuous motion control law. However, since the performance of the DDPG algorithm depends heavily on the hyper-parameters, there is no clear design basis for the Actor-Critic framework neural network architecture. Considering that the reinforcement learning requires a large amount of computation, the repetitive manual trial and error of hyper-parameters greatly reduces the design efficiency of the algorithm and increases labor costs. On the basis of converting the network architecture design problem into a graph topology generation problem, an automatic search and optimization framework for deep reinforcement learning neural network structure is given in this paper, where the graph topology generation algorithm based on LSTM recurrent neural network, the weight sharing-based lightweight training and evaluation mechanism of deep reinforcement network parameter, and the policy gradient-based learning algorithm of graph topology generator parameter are innovatively combined. Thus, the neural network hyper-parameters in the DDPG algorithm are automatically optimized, and the control law is obtained by self-learning training. Finally, taking rocket vertical recovery control as an ex-ample, the effectiveness of the proposed method is verified. © 2022 IEEE.

关键词： Learning systems

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Online Identification of Frequency Response of Attitude control System based on Eigensystem Realization Algorithm 22

Online Identification of Frequency Response of Attitude Cont...

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2nd International Conference on control and intelligent Robotics, ICCIR 2022

作者： Peng, Yue Liu, Jiarun Science and Technology on Aerospace Intelligent Control Laboratory Beijing Aerospace Automatic Control Institute Beijing China China Academy of Launch Vehicle Technology Beijing Aerospace Automatic Control Institute Beijing China

ISBN: (纸本)9781450397179

In view of the problems that the existing attitude control system identification algorithms often rely on actively applying the excitation signal in the loop, which may lead to actuator damage, control quality degradation and long identification time, this paper studies an identification algorithm without actively applying the excitation signal - Eigensystem Realization Algorithm (ERA).The algorithm can be carried out under closed-loop conditions without affecting the stability and safety of flight *** on a simple state-space model, this paper analyzes the difference of the identification effect of the algorithm under different parameter settings, and applies the algorithm to the frequency response identification of the attitude control system of a vertical take-off and landing (VTOL) verification *** simulation results show that the identification results of the new algorithm have a certain reference value for the verification and evaluation of control system design results, and provide a new idea for the field of online identification of aircraft dynamic characteristics. © 2022 ACM.

关键词： Frequency response

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Mobile Equipment Life Prediction Optimization Method Based on Finite Incremental Learning

Mobile Equipment Life Prediction Optimization Method Based o...

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Mobile Internet, Cloud Computing and Information Security (MICCIS), International Conference on

作者： Ying Zhang Yifei Zhao National Key Laboratory of Science and Technology on Aerospace Intelligent Control Beijing Aerospace Automatic Control Institute Beijing

ISBN: (数字)9798350389906

ISBN: (纸本)9798350389913

Based on the research of WE-OSELM algorithm, a residual life prediction method and prediction model based on finite incremental learning and WE-OSELM are proposed. The LWRLP method firstly selects the optimal number of hidden layer nodes in a limited range by using the finite incremental learning method, and integrates the historical degradation data and online time series data to quickly complete the training of the IPW-OSELM algorithm. Then, the error compensation algorithm is trained by using the error data in the training process of IPW-OSELM algorithm. Finally, the mobile equipment life is determined by combining the failure threshold and the multi-step prediction results.

关键词： Training Degradation Incremental learning Time series analysis Optimization methods Information security Error compensation

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Distributed robust iterative learning control for AC microgrids with external disturbances

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science China(Information sciences) 2025年

作者： Hongyu SU Jingang LAI School of Artificial Intelligence and Automation Key Laboratory of Image Processing and Intelligent ControlMinistry of Education Huazhong University of Science and Technology

This study proposes a distributed secondary control scheme based on distributed robust iterative learning control(DRILC) for islanded alternating current(AC) microgrids subjected to external disturbances. By employing the decoupled sliding mode consensus approach, voltage regulation, frequency restoration, and accurate active power sharing can be achieved within a finite time on the proposed novel integral terminal sliding mode(ITSM) manifold. Furthermore, the appropriate iterative update law in the ITSM-based controller is utilized to learn and eliminate external disturbances as effectively as possible. In the proposed control scheme, the iterative learning control and sliding mode control are designed to function in a complementary manner, which enhances the performance of the secondary control scheme for multi-objective regulations. The stability criteria and robustness to external disturbances of the closed-loop microgrid system in the iteration and time domains are also rigorously derived with the help of the Lyapunov direct method. Finally, the effectiveness of the proposed secondary control scheme is validated by case studies of an islanded AC microgrid test system in the MATLAB/SimPowerSystems software environment.

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Adaptive Task Allocation for Multi-UAV Systems Using a Novel Dynamic Distributed Algorithm

Adaptive Task Allocation for Multi-UAV Systems Using a Novel...

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2024 China Automation Congress, CAC 2024

作者： Zhou, Cheng Li, Nuo Yang, Shuqi Yu, Lianbo Lian, Lei Wang, Dong Wang, Wei Key Laboratory of Intelligent Control and Optimization for Industrial Equipment Ministry of Education School of Control Science and Engineering Dalian University of Technology Dalian China

ISBN: (纸本)9798350368604

This paper introduces the Dynamic Efficient Distributed Performance Impact (DEDPI) algorithm for optimizing task allocation in multi-UAV systems operating in dynamic environments. The algorithm overcomes the limitations of existing approaches, specifically the suboptimal solutions of dynamic task algorithms and the computational inefficiencies of extending static algorithms to dynamic contexts, by dynamically adjusting task queues and employing a novel objective function to enhance resource allocation and responsiveness. Experimental results demonstrate that DEDPI significantly increases the number of completed tasks while reducing the average task execution cost, providing an effective solution for real-time, mission-critical UAV operations. © 2024 IEEE.

关键词： Resource allocation

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Robust Fixed-time Composite controller Design with the Unknown System Dynamics Estimator for Nonlinear Robotic Manipulator Systems 24

Robust Fixed-time Composite Controller Design with the Unkno...

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2nd International Conference on Frontiers of intelligent Manufacturing and Automation, CFIMA 2024

作者： Li, Siyan Xing, Yashan Na, Jing Li, Qi Faculty of Mechanical and Electrical Engineering Yunnan Key Laboratory of Intelligent Control and Application Kunming University of Science and Technology Yunnan China

ISBN: (纸本)9798400710681

In this paper, a robust fixed-time composite control scheme based on an Unknown System Dynamics Estimator (USDE) is proposed. The proposed control method guarantees the tracking error convergence in a fixed-time for nonlinear robotic manipulators with unknown dynamics and disturbance. To address the existence of uncertainties, first, a simple structure of USDE by a low-pass filtering operation is constructed without using acceleration signals, Which is adjusted for only one filter coefficient. Then, the USDE compensate the estimated value into the robust fixed-time composite controller. The composite controller contains a fixed time control term, a robust control term, and a computed torque control term. By the fixed-time control term, the upper bound on the convergence time is independent of the initial conditions of the system, which ensures fast-tracking tasks for the robot manipulator. And the robust control term is used to reduce the impact of USDE estimation errors. The stability of the closed-loop system is demonstrated through Lyapunov criteria. The validity of the proposed method is verified by simulation. © 2024 Copyright held by the owner/author(s).

关键词： Stability criteria

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