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Interval Type-2 Fuzzy Hierarchical Adaptive Cruise Following-control for Intelligent Vehicles

IEEE/CAA Journal of Automatica Sinica 2022年第9期9卷 1658-1672页

作者： Hong Mo Yinghui Meng Fei-Yue Wang Dongrui Wu the College of Electric and Information Engineering Changsha University of Science and TechnologyChangsha 410114China the State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190 Qingdao Academy of Intelligent Industries Qingda 266109 the Center of China Economic and Social Security University of Chinese Academy of SciencesBeijing 100190China the Ministry of Education Key Laboratory on Image Information Processing and Intelligent Control the School of Artificial Intelligence and AutomationHuazhong University of Science and TechnologyWuhan 430074China

Intelligent vehicles can effectively improve traffic congestion and road traffic *** cruise followingcontrol(ACFC)is a vital part of intelligent *** this paper,a new hierarchical vehicle-following control strategy is presented by synthesizing the variable time headway model,type-2 fuzzy control,feedforward+fuzzy proportion integration(PI)feedback(F+FPIF)control,and inverse longitudinal dynamics model of ***,a traditional variable time headway model is improved considering the acceleration of the lead ***,an interval type-2 fuzzy logic controller(IT2 FLC)is designed for the upper structure of the ACFC system to simulate the driver's operating *** reduce the nonlinear influence and improve the tracking accuracy for the desired acceleration,the control strategy of F+FPIF is given for the lower control ***,the lower control method proposed in this paper is compared with the fuzzy PI control and the traditional method(no lower controller for tracking desired acceleration)***,the proportion integration differentiation(PID),linear quadratic regulator(LQR),subsection function control(SFC)and type-1 fuzzy logic control(T1 FLC)are respectively compared with the IT2 FLC in control performance under different ***,the simulation results show the effectiveness of IT2 FLC for the upper structure and F+FPIF control for the lower structure.

关键词： Adaptive cruise following-control(ACFC) feedforward+fuzzy proportion integration(PI)feedback(F+FPIF) type-2 fuzzy control variable time headway

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A New True Random Number Generator Based on Chaotic Circuit Architecture

A New True Random Number Generator Based on Chaotic Circuit ...

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2022 International Conference on Cyber Security, Artificial intelligence, and Digital Economy, CSAIDE 2022

作者： Lv, Fei Diao, Jin School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China Key Laboratory of Image Information Processing and Intelligent Control Ministry of Education Wuhan China

ISBN: (纸本)9781510657304

In the fields of information security, the application of random numbers is becoming more and more widespread. True random numbers (TRNs) tend to have better randomness and unpredictability than pseudo random numbers (PRNs). Chaotic systems are very suitable for constructing true random number generators (TRNG) due to their periodic infinity, randomicity, long-term unpredictability, high sensitivity to initial values and parameters, etc. However, when chaotic systems are implemented by finite state machines, their dynamic characteristics will disappear, such as periodic infinity and initial value sensitivity, and there are serious safety concerns about the random number generator designed on this basis. In order to address the degradation problem of the chaotic systems, this paper proposes a true random number generator based on the chaotic circuit, implements a complete hardware system, and tests its randomness. © 2022 SPIE.

关键词： Chaotic systems

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A Time-Independent control Method for Variable-Speed Load-Bearing Walking with Suspended Backpack

A Time-Independent Control Method for Variable-Speed Load-Be...

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第43届中国控制会议

作者： Zhiyuan He Yu Cao Yifei Guo Jian Huang Hubei Key Laboratory of Brain-inspired Intelligent Systems Key Laboratory for Image Processing and Intelligent ControlSchool of Artificial Intelligence and AutomationHuazhong University of Science and Technology

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

Walking with a load brings a significant burden to human shoulders,resulting in increasing metabolic energy consumption and the risk of skeleton and muscle *** backpack has been widely conducted for load-bearing walking,but exiting time-dependent control methods and event-based control methods are unable to exploit the characteristics of human gait *** this case,a time-independent control(TIC) method capable of eliminating the time dependence and adapting to variable speed is *** on the dynamical model of human-backpack system,an assistance profile along with the parameter optimization method are introduced which allows the backpack to reduce the burden on human shoulders during load-bearing *** the simulation evaluation,the proposed TIC method is compared with an impedance controller based time-dependent method and a locked backpack,under both constant speed and variable speed *** results demonstrates that the TIC case achieves an 89.1% reduction in dynamic load on shoulder under the condition of constant speed and a 78.2% reduction under the condition of variable speed,compared with the LOCKED case.

关键词： suspended backpack load carriage time-independent control

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Two-Archive-Based Competitive Swarm Optimizer for Constrained Multiobjective Optimization 5

Two-Archive-Based Competitive Swarm Optimizer for Constraine...

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5th International Conference on Data-Driven Optimization of Complex Systems, DOCS 2023

作者： Li, Lianghao He, Cheng Lin, Jianqing Pan, Linqiang School of Artificial Intelligence and Automation Huazhong University of Science and Technology Key Laboratory of Image Information Processing and Intelligent Control of Education Ministry of China Wuhan China School of Electrical and Electronic Engineering Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9798350393521

Constrained multiobjective optimization problems (CMOPs) are prevalent in various real-world applications, presenting a formidable challenge to existing evolutionary algorithms when faced with intricate constraints. When solving CMOPs, a crucial concern is achieving a balance between convergence, diversity, and feasibility. To address these challenges, this paper proposes a two-archive-based constrained multiobjective competitive swarm optimizer. The algorithm preserves two collaborative and complementary archives to improve population convergence and feasibility. By implementing a competitive particle swarm mechanism, offspring solutions are generated by drawing upon solutions from both archives, thus capitalizing on their synergistic effect and exceptional information. An adaptive parameter is also used to adjust the bias in choosing the winner in the paired competition during the evolution. The experimental results demonstrate the effectiveness of the proposed algorithm in handling constrained multiobjective optimization problems. © 2023 IEEE.

关键词： Constraint handling

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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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Spatiotemporal distance embedded hybrid ant colony algorithm for a kind of vehicle routing problem with constraints

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Frontiers of Information Technology & Electronic Engineering 2023年第7期24卷 1062-1079页

作者： Zhenhui FENG Renbin XIAO School of Artificial Intelligence and Automation Huazhong University of Science and TechnologyWuhan 430074China Institute of Artificial Intelligence Huazhong University of Science and TechnologyWuhan 430074China Key Laboratory of Image Information Processing and Intelligent Control Ministry of EducationWuhan 430074China

We investigate a kind of vehicle routing problem with constraints(VRPC)in the car-sharing mobility environment,where the problem is based on user orders,and each order has a reservation time limit and two location point transitions,origin and *** is a typical extended vehicle routing problem(VRP)with both time and space *** consider the VRPC problem characteristics and establish a vehicle scheduling model to minimize operating costs and maximize user(or passenger)*** solve the scheduling model more accurately,a spatiotemporal distance representation function is defined based on the temporal and spatial properties of the customer,and a spatiotemporal distance embedded hybrid ant colony algorithm(HACA-ST)is *** algorithm can be divided into two ***,through spatiotemporal clustering,the spatiotemporal distance between users is the main measure used to classify customers in categories,which helps provide heuristic information for problem ***,an improved ant colony algorithm(ACO)is proposed to optimize the solution by combining a labor division strategy and the spatiotemporal distance function to obtain the final scheduling *** analysis is carried out based on existing data sets and simulated urban *** with other heuristic algorithms,HACA-ST reduces the length of the shortest route by 2%–14%in benchmark *** VRPC testing instances,concerning the combined cost,HACA-ST has competitive cost compared to existing VRP-related ***,we provide two actual urban scenarios to further verify the effectiveness of the proposed algorithm.

关键词： Vehicle routing problem with constraints(VRPC) Spatiotemporal distance function Labor division strategy Ant colony algorithm(ACO)

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Path Planning Method of Unmanned Surface Vessel Based on Strategy Integration 23rd

Path Planning Method of Unmanned Surface Vessel Based on Str...

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23rd IFToMM China International Conference on Mechanism and Machine Science and Engineering, IFToMM CCMMS 2022

作者： Yang, Caipei Zhao, Yingqi Liu, Jie Zhou, Kaibo MOE Key Laboratory of Image Information Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China School of Civil and Hydraulic Engineering Huazhong University of Science and Technology Wuhan430074 China

ISBN: (纸本)9789811993978

In the task of path planning, the unmanned surface vessels (USV) are required to reach the destination while avoiding obstacle. However, it is difficult for USV to prioritize the two sub-target tasks of destination arrival and obstacle avoidance in a complex dynamic environment using traditional path planning methods. Based on the above considerations, a path planning method for USVs based on strategy integration is proposed. Firstly, the path planning scenario containing dynamic obstacles and two sub-target scenarios are set up. In order to strengthen its ability to reach the destination and avoid dynamic obstacles, the dynamic obstacles and the destination are removed separately in the two sub-target scenarios. Furthermore, the model for strategy selection is trained on action decisions in sub-target scenarios through double deep Q-Network with prioritized experience replay. Finally, a framework for strategy integration is designed to optimize strategy selection for USV. The simulation results show that the proposed method achieves a good overall performance and a higher path planning success rate than the traditional path planning method. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Motion planning

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Energy Management Strategies for PEMFC-Lithium Battery Hybrid Power Systems Based on Pt Degradation 42

Energy Management Strategies for PEMFC-Lithium Battery Hybri...

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42nd Chinese control Conference, CCC 2023

作者： Guo, Ziang Li, Beijia Zeng, Linghong Fu, Jun Sheng, Chuang Li, Xi Huazhong University of Science and Technology School of Artificial Intelligence and Automation Key Laboratory of Image Processing and Intelligent Control of Education Ministry Hubei Wuhan430074 China Shenzhen Huazhong University of Science and Technology Research Institute Shenzhen518055 China

ISBN: (纸本)9789887581543

Proton Exchange Membrane Fuel Cells(PEMFCs) are prone to decreased lifespan due to the degradation of the plat-inum(Pt) catalyst during operation. In this study, we have established a one-dimensional model to investigate the effects of different voltage conditions on Pt degradation. High potential is found to be the most significant factor affecting the degradation. Prolonged exposure to high potentials will significantly reduce the PEMFC's lifespan, and frequent voltage changes will exac-erbate the problem. To mitigate this issue, we have designed three energy management strategies with different limitations and simulated their performance in the operating scenario of a fuel-cell hybrid electric vehicle(FCHEV). The results demonstrate that strategies restricting high potential occurrences and voltage variations can effectively alleviate Pt degradation. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Proton exchange membrane fuel cells (PEMFC)

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Dual-mode predictive control of a rotor suspension system

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Science China(Information Sciences) 2020年第1期63卷 178-189页

作者： Yue WU Gui-Ping REN Hai-Tao ZHANG Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and AutomationHuazhong University of Science and Technology State Key Laboratory of Digital Manufacturing Equipments and Technology

Rotor active magnetic bearing(rotor-AMB) systems are frequently used to alleviate vibrations for various applications such as in national defense, manufacturing industries, IC production, and aerospace engineering. One obstacle to improve machining efficiency and quality is the open-loop instability of rotorAMB systems during the machining process. We built a closed-loop processing platform using a spindle rotor installed with AMBs and thereby developed a rotor-AMB suspension system embedded with a dual-mode predictive controller(DMPC). The performance of the system is thus substantially improved. In the proposed DMPC, both model-based prediction and receding horizon optimization are utilized to guarantee the closedloop stability of the rotor-AMB suspension systems with input constraints. Finally, the effectiveness and superiority of the proposed method are examined through substantial levitation experiments on a machining platform with installed AMBs.

关键词： dual-mode predictive control system identification optimization control model predictive control suspension control

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TMMM: Transformer in Multimodal Sentiment Analysis under Missing Modalities

TMMM: Transformer in Multimodal Sentiment Analysis under Mis...

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International Joint Conference on Neural Networks (IJCNN)

作者： Huanyu Wu Siyang Li Dongrui Wu Ministry of Education Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China

ISBN: (数字)9798350359312

ISBN: (纸本)9798350359329

The cross-task gap presents a significant challenge for multimodal models because of the differences in input-output workflows. For instance, multimodal pre-trained transformers may encounter uni-modal data during testing. To mitigate the gap, this paper introduces a Transformer in Multimodal Sentiment Analysis under Missing Modalities (TMMM) aims to perform well using missing-modal data during testing. TMMM uses a missing multimodal training approach to prevent accuracy degradation in testing. At the same time, a new network architecture allows the model to reconstruct missing modalities during testing. Classification token fusion and Mixture-of-Experts structures further enhance the model’s performance. A pre-training method utilizing contrastive learning, which can construct negative samples with positive samples, is proposed to overcome insufficient labeled data. Our experiments demonstrated the effectiveness of TMMM on two datasets with no modalities missing, i.e., it consistently achieved the highest classification accuracy and Macro-F1, which outperformed the best state-of-the-art baseline on each dataset by about 2% and 2.5%. Additionally, TMMM usually performs better than other baselines on datasets with missing modalities during testing.

关键词： Training Sentiment analysis Accuracy Contrastive learning Network architecture Transformers Brain modeling

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