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25th IEEE China Conference on System Simulation technology and its Application, CCSSTA 2024

作者： Meng, Qingao Tong, Jigang Yang, Sen Xie, Tian Jin, Xin Tianjin University of Technology The School of Electrical Engineering and Automation Tianjin China Avic Xi'an Flight Automatic Control Research Institute National Key Laboratory of Science and Technology on Aircraft Control Xi'an China

ISBN: (纸本)9798350366600

3D object detection is crucial for autopilot and augmented reality applications. However, accurate feature extraction is the key to achieve high-precision detection, but traditional methods face the challenges of information loss and computational inefficiency. To address this, we propose an enhanced feature extraction method. We first divide the 3D space into voxel grids of varying scales. Then, using 3D sparse convolution, we extract features which are compressed along the Z axis to form BEV (Bird's Eye View) feature images. An efficient multi-scale attention mechanism is then employed to enhance these BEV features. The refined feature map is subsequently located and classified through a CT-stacking module and RPN (Region Proposal Network). Voxel features from the proposal and 3D backbone are passed through a voxel RoI pool to directly extract RoI features from the 3D features for further refinement. Finally, a cascaded attention network refines the proposal and strengthens confidence prediction. Experiments on test set validate our method effectiveness, showing improved accuracy over traditional voxel methods. Overall, this enhanced feature extraction technique offers a promising solution for 3D target detection, particularly in scenarios demanding high real-time performance and precision. © 2024 IEEE.

关键词： Feature extraction

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An Optimization Method for the Swing of a Quadrotor Flight Suspension System 25

An Optimization Method for the Swing of a Quadrotor Flight S...

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25th IEEE China Conference on System Simulation technology and its Application, CCSSTA 2024

作者： Yang, Sen Zang, Xinlian Tong, Jigang Xie, Tian Jin, Xin Tianjin University of Technology The School of Electrical Engineering and Automation Tianjin China AVIC Xi'an Flight Automatic Control Research Institute National key laboratory of science and technology on aircraft control Xi'an China

ISBN: (纸本)9798350366600

The aim of this study is to explore optimization control methods for suspension systems during the flight of quadcopters. The traditional control method of suspension system has some problems such as oscillation and instability, so an optimization scheme based on Gaussian pseudo-general algorithm is proposed in this paper. Through numerical simulation and actual flight test, the effectiveness of the optimization algorithm in improving system stability and reducing oscillation amplitude is verified. At the same time, this study conducted a comparative analysis of the suspension system of the quadrotor vehicle and the free fall body, and the optimization algorithm is found to be feasible and can well improve the control accuracy and stability of the system, and provide strong support for the safety of the quadrotor vehicle in various application scenarios. © 2024 IEEE.

关键词： Flight testing

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Knowledge As Not Only Justified True Beliefs in Vision

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IEEE/CAA Journal of automatica Sinica 2025年第2期12卷 297-299页

作者： Wenbo Zheng Fei-Yue Wang IEEE School of Computer Science and Artificial Intelligence Wuhan University of Technology Sanya Science and Education Innovation Park of Wuhan University of Technology the State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences

COMPUTATIONAL knowledge vision [1] is emphasized as a novel perspective or field in this paper. It first proposes the visual hierarchy and its connection to knowledge, stating that knowledge is a justified true belief. To further the previous research, we concisely summarize our recent works and suggest a new direction that knowledge is also a thought framework in vision.

关键词： Computational modeling Visualization Artificial intelligence Data models Visual perception Visual databases Training data

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Distributed Economic MPC with Adaptive Terminal Weights

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IFAC-PapersOnLine 2024年第18期58卷 99-106页

作者： Matthias Köhler Matthias A. Müller Frank Allgöwer University of Stuttgart Institute for Systems Theory and Automatic Control 70569 Stuttgart Germany Leibniz University Hannover Institute of Automatic Control 30167 Hanover Germany

We develop a distributed economic model predictive control (MPC) scheme with generalized terminal constraints and self-tuning terminal weights for multi-agent systems. We state conditions on the terminal weights’ adaption such that an average performance bound holds for the closed-loop system. In addition, we discuss an update law for the terminal weights for which the best reachable equilibria need not be computed in each time step, but which depends only on suboptimal reachable equilibria, e.g. obtained by performing a few steps of a distributed optimization algorithm in each time step.

关键词： Predictive control distributed MPC economic MPC multi-agent systems nonlinear systems

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Finite-time Prescribed Performance control with RBFNN for the HFV Longitudinal Model 41

Finite-time Prescribed Performance Control with RBFNN for th...

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第41届中国控制会议

作者： Yuan Zhang Wanwei Huang Kunfeng Lu Honghao Zhong Beijing Aerospace Automatic Control Institute National Key Laboratory of Science and Technology on Aerospace Intelligent Control

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

A method for designing the finite-time prescribed performance controller with RBFNN(Radial Basis Function Networks) is proposed for the HFV(Hypersonic Flight Vehicle) longitudinal attitude systems with parameters uncertainties and time-varying ***,the appointed-time prescribed performance functions for outer-loop and inner-loop are designed respectively,which aims to restrain the transient and steady-state performance of command tracking *** with the traditional prescribed performance function,the proposed method can guarantee that the errors convergence to the set stability precision at the appointed ***,the error-transform function is applied to transform the guidance command errors into un-limited boundary,which can ensure the error satisfy the constraint condition by means of controlling the transformed ***,the virtual control law of outer-loop subsystem and the actual control law of inner-loop subsystem are designed independently,and the lumped disturbances are estimated by the RBFNN,a novel finite-time tracking differentiator is applied to avoid the 'explosion of terms' problem in the control law design ***,comparative simulations with parametric uncertainties and time-varying disturbance are performed to demonstrate that the proposed method in this paper can effectively satisfy the prescribed performance constraints.

关键词： Hypersonic flight vehicle Lumped Disturbance Finite-time control Radial Basis Function Networks Finite-time Tracking Differentiator

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Intelligent Flight control for Cruise Vehicle Based on Backstepping Design and Reinforcement Learning

Intelligent Flight Control for Cruise Vehicle Based on Backs...

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2023 China Automation Congress, CAC 2023

作者： Liu, Xiaodong Jia, Chenhui Yang, Qingjun Wu, Tiancai Zhang, Yu Beijing Aerospace Automatic Control Institute National Key Laboratory of Science and Technology on Aerospace Intelligence Control Beijing China Beijing Aerospace Automatic Control Institute Beijing China School of Automation Science and Electrical Engineering Beihang University Beijing China

ISBN: (纸本)9798350303759

Aiming at velocity/height tracking control and attitude stabilization for the longitudinal flight of cruise vehicle, the research of intelligent flight control method is carried out by combining the backstepping control theory and the deep reinforcement learning method. Firstly, the longitudinal flight control system of the vehicle is decomposed into velocity and height subsystems, and the control law is designed based on backstepping control theory. Then, aiming at the problems that the selection of the multiple control gains will directly affect the control performance of the closed-loop system and the adjustment process of control gains is cumbersome, the twin delayed deep deterministic policy gradient algorithm (TD3) will be adopted to train the cruise vehicle, so that it can determine the control gains online according to the current flight states. The numerical simulation results show that, the proposed intelligent flight control method can guarantee the high-precision tracking with respect to height and velocity commands, and also realize the attitude stability of cruise vehicle. © 2023 IEEE.

关键词： Reinforcement learning

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Unmanned Aerial Vehicle Tactical Intention Recognition Method Based on Dynamic Series Bayesian Network

Unmanned Aerial Vehicle Tactical Intention Recognition Metho...

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2023 IEEE International Conference on Unmanned systems, ICUS 2023

作者： Li, Jianguo Zhang, Pengcheng Hao, Renze North Automatic Control Technology Institute Software System Research and Development Department Taiyuan China

ISBN: (纸本)9798350316308

To solve the problem of dynamic and sequential air combat intention recognition in complex battlefield environment, a target tactical intention recognition method based on the extended multi-entities Bayesian network (EMEBN) is proposed in this paper. First the dynamic series Bayesian network (DSBN) model is established to describe the process of intention representation and reasoning, the deficiency of the multi-entities Bayesian network (MEBN) in expressing the probability inference knowledge of the planning process is analyzed. Then the probability transfer MEBN fragments (PT-MFrags) and the series relation MEBN fragments (SR-MFrags) are introduced to depict the probability transfer and series relationship of rule knowledge. Finally, the feasibility and effectiveness of this method is verified by an experimental example. © 2023 IEEE.

关键词： Bayesian networks

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Application of Grey Wolf Optimization Algorithm in Tuning controller Parameters of Hypersonic Vehicle 41

Application of Grey Wolf Optimization Algorithm in Tuning Co...

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第41届中国控制会议

作者： Can Tian Shaobo Ni Zhaolei Wang Yuan Zhang National Key Laboratory of Science and Technology on Aerospace Intelligent Control Beijing Aerospace Automatic Control Institute

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

There are many adjustable parameters in the control method of predictive sliding mode control(PSMC) law and linear extended state observer(LESO) for hypersonic vehicle speed and altitude,and the adjustable parameters influence each other on the control effect,and the speed and altitude channels of the aircraft are coupled with each other,so the controller parameters cannot be independently tuned.A method of automatically tuning controller parameters by using grey wolf optimization(GWO) algorithm is ***,the fitness function containing the desired control effect is designed,and then the appropriate number of search agent and iteration times are *** simulation results show that the control effect of the controller with GWO tuning parameters is obviously better than that of the controller with experience tuning parameters,and the expected control effect can be achieved under the condition of adding parameter deviation and actuator limitation.

关键词： predictive sliding mode control linear extended state observer Grey Wolf optimization algorithm Auto-tuning controller parameters

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Flexibility Enhancement Planning of Active Distribution Networks Considering Optimal Dispatch of Demand Response 7

Flexibility Enhancement Planning of Active Distribution Netw...

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7th IEEE International Conference on Energy Internet, ICEI 2023

作者： Fan, Ruizhe Hu, Changbin Luo, Shanna Li, Xuecheng Lu, Heng Feng, Jun School of Electrical and Control Engineering North China University of Technology Beijing China University of Duisburg-Essen Department of Automatic Control and Complex Systems Duisburg Germany

ISBN: (纸本)9798350386684

To enhance the operational flexibility of active distribution network (ADN) with high proportion renewable energy, this paper proposes a flexibility resource planning model considering the optimal dispatch of demand response. Firstly, the flexibility in supply side and demand side are analyzed. Then, a two-layer planning model of flexibility resources is established, which includes the planning layer and operating layer. The planning layer introduces the system comprehensive security index to evaluate the system security, aiming at the optimal annual comprehensive cost of the system. The operation layer introduces the flexibility insufficiency rate as the system flexibility evaluation index, and the network loss and renewable energy curtailment are counted as economic penalties, which is aiming at the optimal annual operation cost of the system. The proposed planning model is solved with particle swarm optimization algorithm. Case studies on the IEEE 33-node distribution system show that the proposed model can effectively reduce the network loss and the renewable generation curtailment. © 2023 IEEE.

关键词： Electric power distribution

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Parallel Manufacturing for Industrial Metaverses:A New Paradigm in Smart Manufacturing

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IEEE/CAA Journal of automatica Sinica 2022年第12期9卷 2063-2070页

作者： Jing Yang Xiaoxing Wang Yandong Zhao The State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190 School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China Beijing SANBODY Technology Company LtdBeijing 214000China North Automatic Control Technology Institute Taiyuan 030006China

To tackle the complexity of human and social factors in manufacturing systems, parallel manufacturing for industrial metaverses is proposed as a new paradigm in smart manufacturing for effective and efficient operations of those systems, where Cyber-Physical-Social systems(CPSSs) and the Internet of Minds(Io M) are regarded as its infrastructures and the "Artificial systems", "Computational experiments"and "Parallel execution"(ACP) method is its methodological foundation for parallel evolution, closed-loop feedback, and collaborative optimization. In parallel manufacturing, social demands are analyzed and extracted from social intelligence for product R&D and production planning, and digital workers and robotic workers perform the majority of the physical and mental work instead of human workers, contributing to the realization of low-cost, high-efficiency and zero-inventory manufacturing. A variety of advanced technologies such as Knowledge Automation(KA), blockchain, crowdsourcing and Decentralized Autonomous Organizations(DAOs) provide powerful support for the construction of parallel manufacturing, which holds the promise of breaking the constraints of resource and capacity, and the limitations of time and space. Finally, the effectiveness of parallel manufacturing is verified by taking the workflow of customized shoes as a case,especially the unmanned production line named Flex Vega.

关键词： Parallel Manufacturing Digital Workers CPSS Smart Manufacturing Industrial Metaverses

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