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Cubature Kalman Fusion Filtering Under Amplify-and-Forward Relays With Randomly Varying Channel Parameters

IEEE/CAA Journal of Automatica Sinica 2025年第2期12卷 356-368页

作者： Jiaxing Li Zidong Wang Jun Hu Hongli Dong Hongjian Liu the Department of Applied Mathematics Harbin University of Science and Technology IEEE the Department of Computer Science Brunel University London the School of Automation Harbin University of Science and Technology the Artificial Intelligence Energy Research Institute Northeast Petroleum University the Heilongjiang Provincial Key Laboratory of Networking and Intelligent Control Northeast Petroleum University the National Key Laboratory of Continental Shale Oil of China Northeast Petroleum University the Key Laboratory of Advanced Perception and Intelligent Control of High-End Equipment Ministry of Education Anhui Polytechnic University the School of Mathematics and Physics Anhui Polytechnic University

In this paper, the problem of cubature Kalman fusion filtering(CKFF) is addressed for multi-sensor systems under amplify-and-forward(AaF) relays. For the purpose of facilitating data transmission, AaF relays are utilized to regulate signal communication between sensors and filters. Here, the randomly varying channel parameters are represented by a set of stochastic variables whose occurring probabilities are permitted to exhibit bounded uncertainty. Employing the spherical-radial cubature principle, a local filter under AaF relays is initially constructed. This construction ensures and minimizes an upper bound of the filtering error covariance by designing an appropriate filter gain. Subsequently, the local filters are fused through the application of the covariance intersection fusion rule. Furthermore, the uniform boundedness of the filtering error covariance's upper bound is investigated through establishing certain sufficient conditions. The effectiveness of the proposed CKFF scheme is ultimately validated via a simulation experiment concentrating on a three-phase induction machine.

关键词： Amplify-and-forward (AaF) relays covariance intersection fusion cubature Kalman filtering multi-sensor systems uniform boundedness

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Combined Model Predictive control for Geosynchronous Satellite Station Keeping Using Electric Propulsion 42

Combined Model Predictive Control for Geosynchronous Satelli...

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42nd Chinese control Conference, CCC 2023

作者： Shi, Heng Liu, Xiaoxiang Wang, Shuo Mai, Ji Beijing Institute of Control Engineering Beijing100094 China Science and Technology on Space Intelligence Control Laboratory Beijing100094 China Beijing Aerospace Institute for Metrology and Measurement Technology Beijing100076 China

ISBN: (纸本)9789887581543

Novel combined model predictive control method is presented, which includes long-term trajectory planning, outer-loop model predictive trajectory and angular momentum control, and inner-loop attitude control. Firstly, the influence of long-period perturbation characteristics on long term station keeping of geosynchronous satellite is fully considered, and the station keeping trajectory is optimized for 3 months to 6 months. Then, taking the long-term planning results as the reference trajectory and considering the engineering constraint model, the outer-loop control is realized within 7 days to 14 days, so that the position trajectory meets the planning expectations and meets the requirements of orbit and angular momentum optimal control. The inner loop control adopts the attitude control method considering the continuous torque effect of small thrust, so as to meet the requirements of real-time angular momentum and attitude control with higher frequency. The method has been successfully verified by on-orbit flight tests, showing the characteristics of high control accuracy, high fuel utilization efficiency, and being adaptive to various engineering constraints. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Model predictive control

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Multi-aircraft Path Planning Method for Cooperative Mission 1

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7th Chinese Conference on Swarm intelligence and Cooperative control, CCSICC 2023

作者： He, Jingwen Zhang, Miaomiao Ju, Wen Liu, Yuecheng Liu, Yemo Yun, Hongquan Beijing Aerospace Automatic Control Institute Beijing100854 China National Key Laboratory of Science and Technology on Aerospace Intelligence Control Beijing100854 China

ISBN: (数字)9789819733361

ISBN: (纸本)9789819733354

Multi-aircraft swarm and autonomous collaboration are inevitable trends in future development, and this paper mainly studies the multi-aircraft cooperative trajectory planning problem model and collaborative search algorithm. Based on the traditional single path planning method, a collaborative trajectory planning strategy is proposed. Based on the spatiotemporal requirements of collaborative tasks, a constraint model is established, and a cooperative path cost model is established by comprehensively considering path synergy and flyability, so as to complete the modeling of path planning problems for collaborative tasks. Aiming at the initial divergence problem in traditional collaborative path planning, a collaborative range model that is updated synchronously with node search is proposed, and an improved cooperative A* path planning algorithm is proposed, which realizes path planning for multi-aircraft collaborative missions. Based on the typical mission environment, the proposed method is simulated, and the feasibility and correctness of the proposed algorithm for solving the multi-aircraft cooperative trajectory planning problem under complex space-time constraints are verified. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Motion planning

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A Survey on Distributed Network Localization from a Graph Laplacian Perspective

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Journal of Systems science & Complexity 2024年第1期37卷 273-293页

作者： HAN Zhimin LIN Zhiyun FU Minyue Artificial Intelligence Institute School of AutomationHangzhou Dianzi UniversityHangzhou 310018China Shenzhen Key Laboratory of Control Theory and Intelligent Systems School of System Design and Intelligent ManufacturingSouthern University of Science and TechnologyShenzhen 518055China Peng Cheng Laboratory Shenzhen 518000China

Network localization serves as a fundamental component for enabling various position based operations in multi-agent systems,facilitating tasks like target searching and formation control by providing accurate position information for all nodes in the *** localization focuses on the challenge of determining the positions of nodes within a network,relying on the known positions of anchor nodes and internode relative *** the past few decades,distributed network localization has garnered significant attention from *** paper aims to provide a review of main results and advancements in the field of distributed network localization,with a particular focus on the perspective of graph *** to its favorable characteristics,graph Laplacian unifies various network localization,even when dealing with diverse types of internode relative measurements,into a unified protocol framework,which can be constructed by a linear method and ensure the global convergence.

关键词： Distributed network localization graph Laplaian sensor network

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Fuzzy-Model-Based Finite Frequency Fault Detection Filtering Design for Two-Dimensional Nonlinear Systems

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IEEE/CAA Journal of Automatica Sinica 2024年第10期11卷 2099-2110页

作者： Meng Wang Huaicheng Yan Jianbin Qiu Wenqiang Ji Key Laboratory of Smart Manufacturing in Energy Chemical Process Ministry of EducationSchool of Information Science and EngineeringEast China University of Science and TechnologyShanghai 200237China Research Institute of Intelligent Control and Systems School of AstronauticsHarbin Institute of TechnologyHarbin 150080China School of Artificial Intelligence Hebei University of TechnologyTianjin 300401China IEEE

This article studies the fault detection filtering design problem for Roesser type two-dimensional(2-D)nonlinear systems described by uncertain 2-D Takagi-Sugeno(T-S)fuzzy ***,fuzzy Lyapunov functions are constructed and the 2-D Fourier transform is exploited,based on which a finite frequency fault detection filtering design method is proposed such that a residual signal is generated with robustness to external disturbances and sensitivity to *** has been shown that the utilization of available frequency spectrum information of faults and disturbances makes the proposed filtering design method more general and less conservative compared with a conventional nonfrequency based filtering design ***,with the proposed evaluation function and its threshold,a novel mixed finite frequency H_(∞)/H_(-)fault detection algorithm is developed,based on which the fault can be immediately detected once the evaluation function exceeds the ***,it is verified with simulation studies that the proposed method is effective and less conservative than conventional non-frequency and/or common Lyapunov function based filtering design methods.

关键词： Fault diagnosis finite frequency specifications mixed H_(∞)/H_(-)performance two-dimensional nonlinear systems

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Digital CEOs in Digital Enterprises:Automating,Augmenting,and Parallel in Metaverse/CPSS/TAOs

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IEEE/CAA Journal of Automatica Sinica 2024年第4期11卷 820-823页

作者： Juanjuan Li Rui Qin Sangtian Guan Xiao Xue Peng Zhu Fei-Yue Wang with State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China the College of Intelligence and Computing Tianjin UniversityTianjin 300072China School of Economics and Management Nanjing University of Science and TechnologyNanjing 210094China the State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190 Faculty of Innovation Engineering Macao University of Science and TechnologyMacao 999078China

BIG models or foundation models are rapidly emerging as a key force in advancing intelligent societies[1]–[3]Their significance stems not only from their exceptional ability to process complex data and simulate advan... 详细信息

关键词： exceptional Auto advancing

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Network-Based Fast Analysis Method for Aircraft Reachable Area 1

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7th Chinese Conference on Swarm intelligence and Cooperative control, CCSICC 2023

作者： Zhang, MiaoMiao He, JingWen Ju, Wen Tian, ZhenPo Liu, YeMo National Key Laboratory of Science and Technology on Aerospace Intelligence Control Beijing100854 China Beijing Aerospace Automatic Control Institute Beijing100854 China

ISBN: (数字)9789819733408

ISBN: (纸本)9789819733392

In order to solve the issue of rapid collaborative mission planning for aircraft, a basic process for using neural networks to train intelligent prediction models to solve the reachable range is proposed. First, the idea of dichotomy is used to carry out traversal simulation experiments and the sample databases under various states is generated. Then, the neural network method is used to construct a trajectory reachable area prediction model, train and test the reachable area prediction model. Finally, the simulation analysis is carried out, and the simulation results showed that the method adopted in this paper is reasonable and feasible. The reachable area of the aircraft track is a polygonal area with upper and lower basic symmetry and left and right asymmetry. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Forecasting

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Generating Adversarial Patterns in Facial Recognition with Visual Camouflage

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Journal of Shanghai Jiaotong University (science) 2024年 1-12页

作者： Bao, Qirui Mei, Haiyang Wei, Huilin Lü, Zheng Wang, Yuxin Yang, Xin Key Laboratory of Social Computing and Cognitive Intelligence of Ministry of Education School of Control Science and EngineeringSchool of Computer Science and Technology Dalian University of Technology Liaoning Dalian116024 China Systems Engineering Institute Academy of Military Sciences Beijing100141 China

Deep neural networks, especially face recognition models, have been shown to be vulnerable to adversarial examples. However, existing attack methods for face recognition systems either cannot attack black-box models, are not universal, have cumbersome deployment processes, or lack camouflage and are easily detected by the human eye. In this paper, we propose an adversarial pattern generation method for face recognition and achieve universal black-box attacks by pasting the pattern on the frame of goggles. To achieve visual camouflage, we use a generative adversarial network (GAN). The scale of the generative network of GAN is increased to balance the performance conflict between concealment and adversarial behavior, the perceptual loss function based on VGG19 is used to constrain the color style and enhance GAN’s learning ability, and the fine-grained meta-learning adversarial attack strategy is used to carry out black-box attacks. Sufficient visualization results demonstrate that compared with existing methods, the proposed method can generate samples with camouflage and adversarial characteristics. Meanwhile, extensive quantitative experiments show that the generated samples have a high attack success rate against black-box models. © 2023, Shanghai Jiao Tong University.

关键词： Face recognition

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Thermal constraint control of reversible solid oxide cell for optimal system efficiency

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International Journal of Hydrogen Energy 2025年 134卷 198-211页

作者： Xu, Yuanwu Yin, Jie Wang, Jingjing Wu, Xiao-long Peng, Jingxuan Tang, Ruifeng Zou, Suhang Fu, Xiaowei Li, Xi School of Artificial Intelligence and Automation Wuhan University of Science and Technology Hubei Wuhan430081 China School of Artificial Intelligence and Automation Key Laboratory of Image Processing and Intelligent Control of Education Ministry Huazhong University of Science and Technology Hubei Wuhan430074 China School of Information Engineering Nanchang University Jiangxi Nanchang330031 China School of Electrical and Electronic Engineering Nanyang Technological University 639798 Singapore China-Poland Belt and Road Joint Laboratory on Measurement and Control Technology Huazhong University of Science and Technology Hubei Wuhan430074 China Shenzhen Huazhong University of Science and Technology Research Institute Shenzhen518055 China

Reversible solid oxide cell (RSOC) demonstrates considerable promise in multimodal energy conversion architectures, particularly as a technology for hydrogen-based energy storage systems. Nevertheless, under dynamic operating regimes with time-varying current inputs, realizing time-efficient and reliable transitions to steady-state operation remains difficult. This difficulty arises from the intricate coupling of thermal, electrical, and gaseous processes within the RSOC system. This study aims to address these challenges by developing a 5 kW mathematical model of the RSOC system. The proposed model enables systematic investigation of thermal safety issues arising during current switching operations while introducing a thermal constraint control strategy to enhance both system efficiency and thermal safety performance. This efficiency-driven study employs the Grid Search algorithm to identify optimal steady-state operating points for the RSOC system, ensuring strict adherence to safety constraints across varying current inputs. Furthermore, by integrating the pre-identified optimal operating points as feedforward control with Model Predictive control (MPC)-based feedback correction, this hybrid strategy effectively mitigates stack temperature gradient overshoot while synchronously ensuring optimal system efficiency throughout current transition processes. Under simulated variable current inputs, the proposed RSOC system model and control strategy demonstrate the capability to constrain stack temperature gradient overshoot within 2.3K while enhancing transient efficiency by 5 %–8 %, achieving a peak system efficiency of 85 %. It provides a novel methodology for safe and efficient working with intermittent renewable energy. © 2025 Hydrogen Energy Publications LLC

关键词： Thermal variables control

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Reinforcement Learning of space Robotic Manipulation with Multiple Safety Constraints 41

Reinforcement Learning of Space Robotic Manipulation with Mu...

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第41届中国控制会议

作者： Linfeng Li Yongchun Xie Yong Wang Ao Chen Beijing Institute of Control Engineering Science and Technology on Space Intelligent Control Laboratory

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

To execute numerous space robotic manipulation tasks(for example on-orbit capture,refueling,assembly,etc.) reliably in presence of high environment uncertainty and multi-source obstacles,it is critical to incorporate safety design into trajectory ***-based planning approaches are commxonly used in the literature,yet suffer insufficient robustness to model *** this paper,we study the sample-based,model-free learning of safe space robotic *** consider numerous practical on-orbit working conditions and propose a novel algorithm called Safe policy optimization with multiple constraints(SPOMC).It incorporates two constraints(namely energy constraint and geometric constraint) into the constrained policy optimization framework,maximizing expected total reward while maintaining a bounded expected total *** simulation on rigid robotic arm manipulation at randomized base positions shows the effectiveness of SPOMC.

关键词： Safety space robotic manipulation Sample-based trajectory optimization Reinforcement learning Constrained Markov decision processes

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