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Prescribed-Time Stabilization of Singularly Perturbed Systems

IEEE/CAA Journal of Automatica Sinica 2023年第2期10卷 569-571页

作者： Yan Lei Yan-Wu Wang Xiao-Kang Liu Wu Yang the School of Artificial Intelligence and Automation Huazhong University of Science and Technology(HUST)Wuhan 430074 Key Laboratory of Image Processing and Intelligent Control Ministry of EducationWuhan 430074China the School of Electrical Engineering Guangxi UniversityNanning 530004China

Dear Editor, This letter investigates the prescribed-time stabilization of linear singularly perturbed systems. Due to the numerical issues caused by the small perturbation parameter, the off-the-shelf control design techniques for the prescribed-time stabilization of regular linear systems are typically not suitable here. To solve the problem, the decoupling transformation techniques for time-varying singularly perturbed systems are combined with linear time-varying high gain feedback design techniques.

关键词： prescribed stabilization perturbed

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Dynamic load altering attack detection based on adaptive fading Kalman filter in smart grid

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IET Generation, Transmission and Distribution 2024年第2期18卷 303-313页

作者： Li, Jian Sun, Chaowei Yang, Shuxian Su, Qingyu School of Automation Engineering Northeast Electric Power University Jilin Jilin China Jilin Provincial Key Laboratory of Advanced Control Technology of Smart Energy Northeast Electric Power University Jilin Jilin China

This paper mainly studies a detection method of dynamic load altering attacks (D-LAAs) in smart grids. First, communication factors are considered, and a smart grid discrete system model under D-LAA attack is established. Second, for closed-loop D-LAAs, an adaptive fading Kalman filter (AFKF) is designed to estimate the states of smart grids with Gaussian noise in real time, and a Euclidean distance ratio detection algorithm based on AFKF is proposed to detect D-LAAs. Moreover, the proposed detection algorithm can identify D-LAAs even in the presence of noise in the measurement data, significantly enhancing the speed of attack detection. Finally, take a smart grid with three generators and six buses as an example. Its feasibility and effectiveness of the Euclidean distance ratio detection algorithm are verified by simulations. The simulations are carried out through the real-time hardware-in-the-loop simulation platform, which is mainly composed of StarSim and multi-tasking devices. © 2024 The Authors. IET Generation, Transmission & Distribution published by John Wiley & Sons Ltd on behalf of The Institution of engineering and Technology.

关键词： Cyber Physical System

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Sustainable Mining in the Era of Artificial Intelligence

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IEEE/CAA Journal of Automatica Sinica 2024年第1期11卷 1-4页

作者： Long Chen Yuting Xie Yutong Wang Shirong Ge Fei-Yue Wang IEEE the State Key Laboratory for Management and Control of Complex Systems at the Institute of Automation Chinese Academy of SciencesBeijing 100190China the National Laboratory of Pattern Recognition at the Institute of Automation and Waytous Ltd.China the School of Computer Science and Engineering Sun Yat-Sen UniversityGuangzhou 510275GuangdongChina the School of Mechanical Electronic and Information Engineering China University of Mining and Technology BeijingBejing 100083China the School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100190China

The mining sector historically drove the global economy but at the expense of severe environmental and health repercussions,posing sustainability challenges[1]-[3].Recent advancements on artificial intelligence(AI)are revolutionizing mining through robotic and data-driven innovations[4]-[7].While AI offers mining industry advantages,it is crucial to acknowledge the potential risks associated with its widespread ***-reliance on AI may lead to a loss of human control over mining operations in the future,resulting in unpredictable consequences.

关键词： Sustainable mining consequences

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GRU combined model based on multi-objective optimization for short-term residential load forecasting

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Journal of Intelligent and Fuzzy Systems 2024年第4期46卷 10423-10440页

作者： Yi, Lingzhi Peng, Xinlong Fan, Chaodong Wang, Yahui Li, Yunfan Liu, Jiangyong College of Automation and Electronic Engineering Xiangtan University Hunan Engineering Research Center of Multi-energy Cooperative Control Technology Hunan Xiangtan China School of Computer Science and Technology Hainan University Hainan China College of Electrical and Information Engineering Hunan University Changsha China

Reliable and accurate short-term forecasting of residential load plays an important role in DSM. However, the high uncertainty inherent in single-user loads makes them difficult to forecast accurately. Various traditional methods have been used to address the problem of residential load forecasting. A single load forecast model in the traditional method does not allow for comprehensive learning of data characteristics for residential loads, and utilizing RNNs faces the problem of long-term memory with vanishing or exploding gradients in backpropagation. Therefore, a gated GRU combined model based on multi-objective optimization is proposed to improve the short-term residential load forecasting accuracy in this paper. In order to demonstrate the effectiveness, GRUCC-MOP is first experimentally tested with the unimproved model to verify the model performance and forecasting effectiveness. Secondly the method is evaluated experimentally with other excellent forecasting methods: models such as DBN, LSTM, GRU, EMD-DBN and EMD-MODBN. By comparing simulation experiments, the proposed GRU combined model can get better results in terms of MAPE on January, April, July, and November load data, so this proposed method has better performance than other research methods in short-term residential load forecasting. © 2024 - IOS Press. All rights reserved.

关键词： Multiobjective optimization

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PillarMamba: A Lightweight Mamba-based Model for 3D Object Detection 4

PillarMamba: A Lightweight Mamba-based Model for 3D Object D...

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4th IEEE International Conference on Digital Twins and Parallel Intelligence, DTPI 2024

作者： Liu, Yuhang Ge, Yinji Li, Mengyue Zheng, Guixu Sun, Boyi Wang, Fei-Yue Chinese Academy of Sciences Institute of Automation Beijing China Beijing Jiaotong University School of Mechanical Electronic and Control Engineering Beijing China

ISBN: (纸本)9798350349252

Parallel LiDAR is a novel framework for constructing next-generation intelligent LiDAR systems. 3D object detection serves as a common perception task in parallel LiDAR research. However, current approaches heavily rely on CNNs or Transformers for feature interaction, placing high demands on computational resources and memory. We introduce the evolving Mamba architecture into 3D object detection to address these issues and propose a new PillarMamba network. PillarMamba utilizes a pure Mamba-based backbone composed of multiple stacked BEVMamba blocks. Our experiments on the KITTI dataset demonstrate that PillarMamba can achieve 65.41% mAP in BEV and 59.13% mAP in 3D perspectives. It paves the way for constructing more efficient and accurate detection models, holding significant value for practical applications. © 2024 IEEE.

关键词： Object recognition

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Event-Triggered Distributed Intelligent Learning control of Six-Rotor UAVs under FDI Attacks

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第7期5卷 3299-3312页

作者： Wu, Ying Chen, Mou Li, Hongyi Chadli, Mohammed Nanjing University of Aeronautics and Astronautics College of Automation Engineering Nanjing211106 China University Paris-Saclay Univ Evry IBISC Evry91020 France Guangdong University of Technology School of Automation The Guangdong Province Key Laboratory of Intelligent Decision and Cooperative Control Guangzhou510006 China

Aiming at the six-rotor unmanned aerial vehicles (UAVs) subjected to false data injection (FDI) attacks, an event-triggered-based distributed intelligent learning control strategy is proposed in this article. The reinforcement learning algorithm which is designed based on neural networks (NNs) is introduced to achieve intelligent optimal control. Under the actor-critic-identifier frame, three kinds of NNs are used to realize the control action, evaluate the system performance, and estimate the unknown dynamic, respectively. Then, an improved event-triggered strategy including a decreasing function of the consensus error is designed to reduce the waste of resources while decreasing the adverse impact on tracking control performance as far as possible, which also does not exhibit Zeno behavior. Furthermore, an adaptive compensation control scheme is given, which can effectively compensate for the negative impacts brought by the FDI attacks existing in information interaction among UAVs. Despite the impact of lumped disturbances and FDI attacks, the proposed disturbance-observer-based distributed intelligent learning control strategy can still guarantee that all signals in the closed-loop UAV systems are bounded, and all follower UAVs can track the signal of the leader UAV. Finally, some simulation verification diagrams are shown to test the feasibility of the designed control strategy. © 2020 IEEE.

关键词： Neural networks

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Tunable topological interface states via a parametric system in composite lattices with/without symmetric elements

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Applied Mathematics and Mechanics(English Edition) 2024年第12期45卷 2055-2074页

作者： Jianguo CUI Tianzhi YANG Wenju HAN Liang LI Muqing NIU Liqun CHEN School of Mechanics and Photoelectric Physics Anhui University of Science and TechnologyHuainan 232001Anhui ProvinceChina School of Mechanical Engineering and Automation Northeastern UniversityShenyang 110819China School of Aerospace Engineering North University of ChinaTaiyuan 030051China School of Science Harbin Institute of TechnologyShenzhenShenzhen 518055Guangdong ProvinceChina Shanghai Key Laboratory of Mechanics in Energy Engineering Shanghai Institute of Applied Mathematics and MechanicsSchool of Mechanics and Engineering ScienceShanghai UniversityShanghai 200444China Shanghai Institute of Aircraft Mechanics and Control Shanghai 200092China

Over the past decades, topological interface states have attracted significant attention in classical wave systems. Generally, research on the topological interface states of elastic waves is conducted in the lattices with symmetric elements. This paper proposes composite lattices with/without symmetric elements, and demonstrates the realization of tunable topological interface states of elastic waves via parametric *** quantize the topological characteristics of the bands, a modified Zak phase is defined to calculate the topological invariant by the eigenstates for the lattices with/without symmetric elements. The numerical results show that the tunable frequencies of topological interface states can be realized in composite lattices with/without symmetric elements through the modulation of the parametric excitation frequency. The tunable topological interface states can be introduced into the vibration energy harvesting to design efficient and steady energy harvesting systems.

关键词： metamaterial topological interface state parametric excitation asymmetric element modified Zak phase

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Harnessing Neural Unit Dynamics for Effective and Scalable Class-Incremental Learning 41

Harnessing Neural Unit Dynamics for Effective and Scalable C...

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41st International Conference on Machine Learning, ICML 2024

作者： Li, Depeng Wang, Tianqi Chen, Junwei Dai, Wei Zeng, Zhigang School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China School of Information and Control Engineering China University of Mining and Technology Xuzhou China

Class-incremental learning (CIL) aims to train a model to learn new classes from non-stationary data streams without forgetting old ones. In this paper, we propose a new kind of connectionist model by tailoring neural unit dynamics that adapt the behavior of neural networks for CIL. In each training session, it introduces a supervisory mechanism to guide network expansion whose growth size is compactly commensurate with the intrinsic complexity of a newly arriving task. This constructs a near-minimal network while allowing the model to expand its capacity when cannot sufficiently hold new classes. At inference time, it automatically reactivates the required neural units to retrieve knowledge and leaves the remaining inactivated to prevent interference. We name our model AutoActivator, which is effective and scalable. To gain insights into the neural unit dynamics, we theoretically analyze the model's convergence property via a universal approximation theorem on learning sequential mappings, which is under-explored in the CIL community. Experiments show that our method achieves strong CIL performance in rehearsal-free and minimal-expansion settings with different backbones. Copyright 2024 by the author(s)

关键词： Adversarial machine learning

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Trajectory Tracking control of Autonomous Vehicles based on Improved Model-free Adaptive control 3

Trajectory Tracking Control of Autonomous Vehicles based on ...

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3rd International Conference on Testing Technology and automation engineering, TTAE 2023

作者： Wang, Wanting Wang, Siming Han, Taoguo School of Automation and Electrical Engineering Lanzhou Jiaotong University Lanzhou730070 China College of Computer and control engineering Northeast Forestry University Harbin150000 China

ISBN: (纸本)9781510674769

This paper presents a novel approach to address the lateral control issue in trajectory tracking for autonomous cars. Traditional model-free adaptive control algorithms have some limitations, prompting the development of an enhanced data-driven model-free adaptive control scheme. More precisely, inside a specified trajectory, the vehicle's issue of lateral control is converted into a problem of tracking the preview-deviation-angle. A dynamic linearized data model is developed for the lateral control of autonomous cars, taking into account the input and output data. To enhance the steering angle control rate, a time-varying proportional control term is incorporated. An enhanced trajectory tracking control technique for the MFAC system is proposed, followed by a demonstration of its convergence. The simulation findings demonstrate that the IMFAC scheme exhibits a superior output response compared to both MFAC and PID in both low-speed and high-speed scenarios. Furthermore, the IMFAC system is capable of achieving autonomous vehicle path tracking. © 2024 SPIE.

关键词： Autonomous vehicles

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Odor Source Search with a Wolf Pack Algorithm via Multi-UAV in Outdoor Environment 6

Odor Source Search with a Wolf Pack Algorithm via Multi-UAV ...

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6th International Conference on Industrial Artificial Intelligence, IAI 2024

作者： Wu, Wen-Qiang Li, Ji-Gong Yang, Jing School of Automation and Electrical Engineering Tianjin University of Technology and Education Tianjin Key Laboratory of Information Sensing and Intelligent Control Tianjin China

ISBN: (纸本)9798350356618

Concerning the problem of odor source search with robots in a large outdoor environment, an odor source search method based on the improved wolf pack algorithm (IWPA) is proposed, in which each wolf corresponds to an unmanned aerial vehicle (UAV). The environment is firstly traversed by the UAVs in partitions by using rectangular wave- shaped paths. Once odor plume is detected by any UAV, the WPA is applied to guide the UAVs towards the odor source. Considering the limited number of UAVs, in order to improve the utilization rate of UAVs, the wolf pack is simplified into two roles: the alpha wolf and other wolves. Meanwhile, to avoid collisions between UAVs and enable UAVs to fully sample around the suspected target position, a besieging algorithm based on a virtual force field is designed to calculate next flight direction for the UAVs. During this period, the odor source position is determined by the alpha wolf which is constantly elected by comparing the fitness values of all wolves. Simulation results show that the IWPA method can find the odor source in short time without falling into local extremum, demonstrating good convergence and being suitable for odor source search tasks in outdoor environments. © 2024 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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