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Chinese Automation Congress (CAC)

作者： Dingcui Huang Jiangping Hu Zhinan Peng Bo Chen Mingrui Hao Bijoy Kumar Ghosh School of Automation Engineering University of Electronic Science and Technology of China Chengdu China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China Texas Tech University Lubbock USA

ISBN: (数字)9781728176871

ISBN: (纸本)9781728176888

Traditional aircraft control algorithms have a strong dependence on system models, and are difficult to cope with the increasingly complex battlefield environment for intelligent aircrafts. In this paper, a model-free reinforcement learning is proposed to solve an attitude stabilization problem of an aircraft based online intelligent control strategy. The attitude control problem is firstly formulated as an optimal control problem, and then an adaptive dynamic programming (ADP) technology is applied to compute the corresponding nonlinear Hamilton-Jacobi-Bellman (HJB) equation. Then, an actor-critic neural network structure is established to learn the optimal controller online not requiring the information of the aircraft dynamics. The proposed intelligent control strategy enables the aircraft to adjust its attitude according to the actual mission targets and environments under the proposed online control strategy, so that autonomous learning and intelligent operation can be realized. Finally, simulation examples are presented to validate the proposed model-free based control strategy.

关键词： Atmospheric modeling Aircraft Adaptation models Mathematical model Aerodynamics Attitude control Vehicle dynamics

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An initial alignment approach for improving the accuracy of azimuth setting

An initial alignment approach for improving the accuracy of ...

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2019 IEEE International Conference on Unmanned systems, ICUS 2019

作者： Guan, Xujun Wang, Xing Guo, Jianzhong Fu, Wenxing Meng, Lingbao Beijing Electro-Mechanical Engineering Institute Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China China Aerospace Science and Industry Corporation Beijing China

ISBN: (纸本)9781728137926

Considering the azimuth discrepancy between the main and sub-inertial navigation systems (INS) for a platform-carried unmanned aerial vehicles(UAV) in case of tilted launching at a large pitch angle, an initial alignment method for improving the accuracy of the azimuth setting is proposed. First, an algorithm for computing the azimuth discrepancy is derived. Then, a mathematical model for initial alignment is established based on azimuth setting. The simulation results show that correcting the azimuth discrepancy between the main and sub-INS can greatly improve the accuracy of azimuth setting, and therefore the initial alignment accuracy of the sub-INS. Meanwhile, the drift for the gyros in three directions can be effectively estimated. © 2019 IEEE.

关键词： Inertial navigation systems

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An adaptive fault detection strategy for Cz crystal growth process

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IEEE Transactions on Instrumentation and Measurement 2025年

作者： Mu, Lingxia Feng, Nan Zhang, Zhenhua Zhang, Youmin Zhang, Jian Xian University of Technology Crystal Growth Equipment and Systems Integration National Engineering Research Center Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xian710048 China University of Science and Technology Beijing School of Intelligence Science and Technology Beijing100083 China Concordia University Department of Mechanical Industrial and Aerospace Engineering MontrealQCH3G 1M8 Canada

The monitoring and fault detection for the Czochralski (Cz) crystal growth process is important to ensure the quality of the produced mono-crystalline silicon. The Cz process is a typical multi-modes industrial process, which makes the detection difficult in distinguish the change caused by the fault or mode switching. In this paper, an adaptive fault detection strategy for Cz crystal growth process is proposed. Firstly, quality-related variables are selected from numerous process variables, based on which the training dataset is constructed. Then, a fault detection model is built based on slowly-varying feature and statics indicator. A model switching strategy and updating algorithm are designed to handle the abnormal situation caused by the mode switching or fault occurrence. Three representative experiments are conducted to verify the performance of the proposed strategy, including numerical cases, a publicly available dataset, and Cz crystal growth process from our laboratory. © 1963-2012 IEEE.

关键词： Crystal growth from melt

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Sliding sequential CVAE with time variant socially-aware rethinking for trajectory prediction

arXiv

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arXiv 2021年

作者： Zhou, Hao Ren, Dongchun Yang, Xu Fan, Mingyu Huang, Hai National Key Laboratory of Science and Technology of Underwater Vehicle Harbin Engineering University Harbin China State Key Laboratory of Management and Control for Complex System Institute of Automation Chinese Academy of Sciences Beijing China Research Center for Autonomous Vehicles Meituan Beijing China College of Computer Science Wenzhou University Wenzhou China National Key Laboratory of Science and Technology of Underwater Vehicle Harbin Engineering University Harbin China

Pedestrian trajectory prediction is a key technology in many applications such as video surveillance, social robot navigation, and autonomous driving, and significant progress has been made in this research topic. However, there remain two limitations of previous studies. First, with the continuation of time, the prediction error at each time step increases significantly, causing the final displacement error to be impossible to ignore. Second, the prediction results of multiple pedestrians might be impractical in the prediction horizon, i.e., the predicted trajectories might collide with each other. To overcome these limitations, this work proposes a novel trajectory prediction method called CSR, which consists of a cascaded conditional variational autoencoder (CVAE) module and a socially-aware regression module. The cascaded CVAE module first estimates the future trajectories in a sequential pattern. Specifically, each CVAE concatenates the past trajectories and the predicted points so far as the input and predicts the location at the following time step. Then, the socially-aware regression module generates offsets from the estimated future trajectories to produce the socially compliant final predictions, which are more reasonable and accurate results than the estimated trajectories. Moreover, considering the large model parameters of the cascaded CVAE module, a slide CVAE module is further exploited to improve the model efficiency using one shared CVAE, in a slidable manner. Experiments results demonstrate that the proposed method exhibits improvements over state-of-the-art method on the Stanford Drone Dataset (SDD) and ETH/UCY of approximately 38.0% and 22.2%, respectively. © 2021, CC BY.

关键词： Trajectories

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Optimal Terrain Following Trajectory Regeneration Using Linear Gauss Pseudo-Spectral Method

Optimal Terrain Following Trajectory Regeneration Using Line...

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2019 IEEE International Conference on Unmanned systems, ICUS 2019

作者： Feng, Yijun Chen, Wanchun Yang, Liang Wei, Donghui Beihang University School of Astronautics Beijing China Beijing Electro-Mechanical Engineering Institute Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China

ISBN: (纸本)9781728137926

A numerical method for two-dimensional terrain following optimal trajectory regeneration is proposed in this paper, which corrects the planned optimal trajectory to avoid collision with previously unknown obstacles. The neighboring extremal problem is established near the optimal terrain following trajectory, which can be regarded as a two-point boundary-value problem (TPBVP) and solved using Linear Gauss Pseudo-Spectral (LGP) method. Compared with the classical backward sweep method for solving TPBVPs, LGP method is much faster in obtaining approximate results. Numerical simulations are provided to validate the effectiveness and demonstrate the features of the problem. © 2019 IEEE.

关键词： Numerical methods

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Monocular visual based obstacle distance estimation method for ultra-low altitude flight

Monocular visual based obstacle distance estimation method f...

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2019 IEEE International Conference on Unmanned systems, ICUS 2019

作者： Cheng, Jin Wei, Donghui Chen, Wanchun Gao, Wang Beijing Electro-Mechanical Engineering Institute Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China Beihang University School of Astronautics Beijing China

ISBN: (纸本)9781728137926

This paper focuses on the problem of ultra-low-altitude flight obstacle distance estimation for monocular vision-assisted aircraft. First, the basic error model of distance estimation using sequence images is derived and the phenomenon of "epipole dead zone" is revealed. Then the distance estimation algorithm based on pairs of coplanar points is proposed as well as its error model. This algorithm is proved to be a solution of the "epipole dead zone" problem theoretically. Finally, numerical simulations show that the proposed distance estimation algorithm can effectively improve the accuracy of distance estimation in the "epipole dead zone". © 2019 IEEE.

关键词： Vision

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Evasion strategies of a three-player lifeline game

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science China(Information sciences) 2018年第11期61卷 144-154页

作者： Fan ZHANG Wenzhong ZHA School of Automation Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex System Information Science Academy China Electronics Technology Group Corporation

This study examines a multi-player pursuit-evasion game, more specifically, a three-player lifeline game in a planar environment, where a single evader is tasked with reaching a lifeline prior to capture. A decomposition method based on an explicit policy is proposed to address the game qualitatively from two main aspects:(1) the evader's position distribution to guarantee winning the game(i.e., the escape zone),which is based on the premise of knowing the pursuers' positions initially, and(2) evasion strategies in the escape zone. First, this study decomposes the three-player lifeline game into two two-player sub-games and obtains an analytic expression of the escape zone by constructing a barrier, which is an integration of the solutions of two sub-games. This study then explicitly partitions the escape zone into several regions and derives an evasion strategy for each region. In particular, this study provides a resultant force method for the evader to balance the active goal of reaching the lifeline and the passive goal of avoiding capture. Finally,some examples from a lifeline game involving more than one pursuer are used to verify the effectiveness and scalability of the evasion strategies.

关键词： lifeline game three-player pursuit-evasion game barrier evasion strategy game of kind

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A strategy of multi-UAV cooperative path planning based on CCPSO

A strategy of multi-UAV cooperative path planning based on C...

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2019 IEEE International Conference on Unmanned systems, ICUS 2019

作者： Liu, Yuanna Lu, Hao Northwestern Polytechnical University Dept. School of Electronics and Information Xi'an China Intelligent Agent Cooperation Laboratory Dept. Science and Technology on Complex System Control Beijing China

ISBN: (纸本)9781728137926

Multi-UAV cooperative formation flying has significant advantages in broadening the scope of UAV operations and improving combat effectiveness. How to realize the cooperative path planning of multi-UAV is an open issue. In order to solve the search performance degradation as dimension increases, a strategy of multi-UAV cooperative path planning based on Cooperative Coevolution Particle Swarm Optimization (CCPSO) is proposed in this paper. Firstly, the initial Dubins path is generated for each UAV in the formation, of which the longest one is selected as the reference path. Intermediate waypoints are designed to modify the initial paths to avoid collisions with obstacles. Then, CCPSO algorithm is applied to optimize path parameters and adjust the path length to be equal to the reference path to ensure time coordination. Collision avoidance between UAVs is achieved in the collaborative evaluation phase. Finally, an formation rendezvous example and comparison with CCGA are given to explain the validity and excellent search ability of the proposed method. © 2019 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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Experimental verification of an integrated radar communication system

Experimental verification of an integrated radar communicati...

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IET International Radar Conference 2018, IRC 2018

作者： Li, Zengliang Liu, Jie Yin, Ning Wang, Youcheng Beijing Institute of Electro-Mechanical Engineering Beijing100074 China Science and Technology on Complex System Control Intelligent Agent Cooperation Laboratory Beijing100074 China

With the development of modern weapon techniques, radio frequency integrated technology has attracted widespread attention as a key technology to improve the informationalised level of missiles. Radar and communication are two typical electronic types of equipment, and their integration can support and promote the development of radio frequency integrated technology. In this study, experimental verification of an integrated radar-communication system is carried out. Firstly, the key technologies to achieve radar-communication integration are theoretically analysed. The solutions of the key issues, including signal separation, time synchronisation and frequency synchronisation, are proposed. Furthermore, a radar-communication demo is implemented and the experimental verification is carried out here to verify the feasibility of the proposed methods. © This is an open access article published by the IET under the Creative Commons Attribution License (http://***/licenses/by/3.0/)

关键词： Radar

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Policy iteration based Q-learning for linear nonzero-sum quadratic differential games

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science China(Information sciences) 2019年第5期62卷 195-213页

作者： Xinxing LI Zhihong PENG Li LIANG Wenzhong ZHA School of Automation Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex System Information Science Academy China Electronics Technology Group Corporation

In this paper, a policy iteration-based Q-learning algorithm is proposed to solve infinite horizon linear nonzero-sum quadratic differential games with completely unknown dynamics. The Q-learning algorithm, which employs off-policy reinforcement learning(RL), can learn the Nash equilibrium and the corresponding value functions online, using the data sets generated by behavior policies. First, we prove equivalence between the proposed off-policy Q-learning algorithm and an offline PI algorithm by selecting specific initially admissible polices that can be learned online. Then, the convergence of the off-policy Qlearning algorithm is proved under a mild rank condition that can be easily met by injecting appropriate probing noises into behavior policies. The generated data sets can be repeatedly used during the learning process, which is computationally effective. The simulation results demonstrate the effectiveness of the proposed Q-learning algorithm.

关键词： adaptive dynamic programming ADP Q-learning reinforcement learning RL linear nonzerosum quadratic differential games policy iteration PI off-policy

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