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42nd Chinese control Conference, CCC 2023

作者： Wang, Yumei Tang, Chuancong Zhang, Hai-Tao School of Artificial Intelligence and Automation Huazhong University of Science and Technology The Engineering Research Center of Autonomous Intelligent Unmanned Systems The Key Laboratory of Image Processing and Intelligent Control The State Key Laboratory of Digital Manufacturing Equipment and Technology Wuhan430074 China

ISBN: (纸本)9789887581543

There are always some 'key' nodes in a big complex network, which can joint the most connected subgraphs. How to identify these nodes, finding a minimum set of nodes to attack for reducing the size of residual network's Largest Connected Component(LCC) to break up the original network, has become a research hotspot. Therefore, a method for determining the 'key' nodes based on reinforcement learning framework and supervised learning model is proposed. This algorithm can not only utilize the dynamic exploration ability of reinforcement learning to collect a rich training dataset, but also take advantage of the characteristics that supervised learning is adaptive and has strong generalization ability to possess high efficiency and strong robustness. In order to further improve the algorithm's performance, ϵ-greedy mechanism is used to explore more network states. The experiment results show that given the same fraction of removed nodes, our algorithm can make the residual LCC smaller in various networks which is superior to the state-of-the-art algorithms in terms of effectiveness and generalization. © 2023 Technical Committee on control Theory, Chinese Association of automation.

关键词： Complex networks

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Koopman Operator Learning control of the Piezoelectric Actuator 42

Koopman Operator Learning Control of the Piezoelectric Actua...

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42nd Chinese control Conference, CCC 2023

作者： Huang, Xiang Zhang, Hai-Tao School of Artificial Intelligence and Automation Huazhong University of Science and Technology Engineering Research Center of Autonomous Intelligent Unmanned Systems The Key Laboratory of Image Processing and Intelligent Control The State Key Laboratory of Digital Manufacturing Equipment and Technology Wuhan430074 China

ISBN: (纸本)9789887581543

The piezoelectric actuator is one kind of device that can drive nanoscale motion. However, the nonlinear hysteresis effect induced by its natural material greatly degrades its positioning accuracy. To handle this challenging issue, this work develops a Koopman model predict control (Koopman- MPC) framework for the piezoelectric actuator. Specifically, the Koopman operator theory is adapted for modeling the piezoelectric actuator dynamics. A simple yet powerful linear model spanned in a high-dimensional space is thus constructed to characterize the hysteresis dynamics. Subsequently, upon the established Koopman model, an MPC scheme is put forward for tracking control of piezoelectric actuators. Therein, by sustained optimizing a cost function containing future outputs and control increments, the control input is obtained. Moreover, extensive tracking simulations are carried out on a simulated piezoelectric actuator for verifying the feasibility and effectiveness of the Koopman- Mpc scheme. © 2023 Technical Committee on control Theory, Chinese Association of automation.

关键词： Model predictive control

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Speed Profile Optimization for Autonomous Electric Bus in Urban Area: Based on Service Route Parameter in Thailand

Speed Profile Optimization for Autonomous Electric Bus in Ur...

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2023 International Conference on Power, Energy and Innovations, ICPEI 2023

作者： Sakulphaisan, Guntinan Son-In, Sirirat Junhuathon, Nitikorn Muankhaw, Theerapol Pathumwan Institute of Technology Faculty of Science and Technology Industrial Technology and Innovation Management Bangkok Thailand Bansomdejchaopraya Rajabhat University Faculty of Engineering and Industrial Technology Electrical Engineering and Automation Control Systems Bangkok Thailand Rajamangala University of Technology Faculty of Engineering Department of Electrical Engineering Thanyaburi Pathumthani Thailand

ISBN: (纸本)9798350344585

This study conducts a comprehensive analysis of optimizing the speed profile of an AE-bus, a critical step in enhancing its operational efficiency. It encompasses three distinct case studies, each targeting specific objectives. The first case emphasizes energy consumption reduction, contributing to overall resource efficiency. The second focuses on eco-conscious speed profiles within predefined travel durations, balancing environmental sustainability and timeliness. The third case prioritizes travel time minimization for streamlined efficiency. Detailed insights into speed adjustments, bus positions, and energy consumption patterns are provided for each case. The findings reveal tailored approaches for energy conservation, speed, and travel time optimization. Additionally, emissions analysis demonstrates that electric buses significantly reduce CO2 emissions compared to conventional NGV buses, showcasing their potential for environmental benefits. © 2023 IEEE.

关键词： Electric buses

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Development of a New Bicycle Drive Hub 2nd

Development of a New Bicycle Drive Hub

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2nd International Conference of Mechanical System Dynamics, ICMSD 2023

作者： Pereira, António B. Dias, Pedro M. Ramos, António M. TEMA—Centre for Mechanical Technology and Automation Department of Mechanical Engineering University of Aveiro Campus de Santiago Aveiro3810-193 Portugal LASI—Intelligent Systems Associate Laboratory Guimarães Portugal

ISBN: (纸本)9789819980475

Drive hubs are a crucial component for any bicycle, as they are responsible for transmitting the power generated by the pedals to the bicycle wheels. There are two main types of drive hubs on the market, inboard and outboard. Inner hubs are more commonly used on city and hybrid bikes, while outer hubs are more common on road and mountain bikes. This work focuses on the freehub type internal gear drive hub. In a bicycle transmission system, the movement generated by the pedals is transmitted to the rear wheel of the bicycle through a series of gears and chain that allow the cyclist to adjust the torque and speed of the bicycle. The fundamental mechanism in this system is the rear wheel hub, which allows the rear wheel to rotate freely when there is no force applied to the pedals and accepts torque in the opposite situation. This mechanism can be either freehub or freewheel type. The way the gearing is done in the freehub is patented in two main processes, the ratchet, and the pawl. The system developed in this work is based on the ratchet scheme but contains permanent magnets instead of springs, which makes it smaller and less subject to material fatigue problems. In this design, the coupling movement is carried out by sliding in the 22 teeth axial spline on a radial toothed ring with 80 contact points, which mesh with a twin fixed to the wheel hub. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Bicycles

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Fault localization for intelligent automation systems 28

Fault localization for intelligent automation systems

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28th IEEE International Conference on Emerging Technologies and Factory automation, ETFA 2023

作者： Eros, Endre Bengtsson, Kristofer Åkesson, Knut Chalmers University of Technology Automation Research Group Electrical Engineering Systems and Control Department Gothenburg Sweden Volvo Group As Senior Researcher for Smart and Connected Operations Research and Technology Development Gothenburg Sweden

ISBN: (纸本)9798350339918

Conventional programming of explicit control code is unsuitable for flexible and collaborative production systems. A model-based approach, which focuses on defining capabilities of a system, instead of specifying how to achieve them, provides an alternative for creating complex, scalable, and reliable systems. This is accomplished through the use of behavior models, and tools such as planning, synthesis, verification, and testing. However, developing such models is not without challenges, as it is possible to overlook or incorrectly specify potential behavior and constraints. This can result in unsolvable planning problems or plans that are invalid for other reasons. When plans are unobtainable, developers receive no feedback, which makes model adjustments a difficult and time-intensive task. This paper recognizes these challenges as crucial barriers for adopting model-based development of intelligent automation systems. To facilitate the development of such systems, an approach for detecting and localizing faults in behavior models is presented. Drawing inspiration from software fault localization techniques, the proposed method involves identifying suspicious resources, variables, and operations. The effectiveness of this approach is illustrated with an example use case. © 2023 IEEE.

关键词： automation

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Description and fault diagnosis in autonomous underwater vehicles based on ontologies

Description and fault diagnosis in autonomous underwater veh...

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2022 International Conference on Ocean Studies, ICOS 2022

作者： Alexander, Timoshenko Alexander, Zuev Eduard, Mursalimov Valeria, Gribova Alexander, Inzartsev Far Eastern Federal University Institute of Marine Technology Problems Feb Ras Laboratory of Intelligent Systems for Marine Robots Department of Automation and Robotics Vladivostok Russia Institute of Automation and Control Feb Ras Laboratory of Intelligent Systems Vladivostok Russia Institute of Marine Technology Problems Feb Ras Laboratory of Control Systems Vladivostok Russia

ISBN: (纸本)9781665473729

The paper proposes new ontologies for describing and diagnosing malfunctions of subsystems of autonomous underwater vehicles (AUV) as a part of the development of a previously created approach to the intelligent diagnosis of these vehicles using knowledge bases. To implement this approach, it is proposed to use two knowledge bases, one of which describes malfunctions, features for their identification and actions necessary to adapt to the negative consequences caused by the appearance of these malfunctions. The other database contains information about the main subsystems of the AUV, devices and replaceable modules, as well as the states they may be in. Knowledge bases are used in the work of the intelligent control-emergency system (ICES) on board the AUV, which allows for comprehensive functional diagnostics of all subsystems of the device, including payload modules, as well as adaptation to the consequences of emerging malfunctions, taking into account the actual cause-and-effect relationships between them. To test the system's operability, a prototype was developed. The results of the prototype simulation showed that ICES performs the tasks and can be implemented on the onboard computers of existing AUV using well-known programming technologies. © 2022 IEEE.

关键词： Autonomous underwater vehicles

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Price-Based Residential Demand Response Management in Smart Grids:A Reinforcement Learning-Based Approach

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IEEE/CAA Journal of Automatica Sinica 2022年第1期9卷 123-134页

作者： Yanni Wan Jiahu Qin Xinghuo Yu Tao Yang Yu Kang Department of Automation University of Science and Technology of ChinaHefei 230027China Institute of Artificial Intelligence Hefei Comprehensive National Science CenterHefei 230088China School of Engineering RMIT UniversityVIC 3000Australia State Key Laboratory of Synthetical Automation for Process Industries Northeastern UniversityShenyang 110819China Department of Automation State Key Laboratory of Fire ScienceInstitute of Advanced TechnologyUniversity of Science and Technology of ChinaHefei 230027China Key Laboratory of Technology in Geo-Spatial Information Processing and Application Systems Chinese Academy of SciencesBeijing 100190China

This paper studies price-based residential demand response management(PB-RDRM)in smart grids,in which non-dispatchable and dispatchable loads(including general loads and plug-in electric vehicles(PEVs))are both *** PB-RDRM is composed of a bi-level optimization problem,in which the upper-level dynamic retail pricing problem aims to maximize the profit of a utility company(UC)by selecting optimal retail prices(RPs),while the lower-level demand response(DR)problem expects to minimize the comprehensive cost of loads by coordinating their energy consumption *** challenges here are mainly two-fold:1)the uncertainty of energy consumption and RPs;2)the flexible PEVs’temporally coupled constraints,which make it impossible to directly develop a model-based optimization algorithm to solve the *** address these challenges,we first model the dynamic retail pricing problem as a Markovian decision process(MDP),and then employ a model-free reinforcement learning(RL)algorithm to learn the optimal dynamic RPs of UC according to the loads’*** proposed RL-based DR algorithm is benchmarked against two model-based optimization approaches(i.e.,distributed dual decomposition-based(DDB)method and distributed primal-dual interior(PDI)-based method),which require exact load and electricity price *** comparison results show that,compared with the benchmark solutions,our proposed algorithm can not only adaptively decide the RPs through on-line learning processes,but also achieve larger social welfare within an unknown electricity market environment.

关键词： Demand response management(DRM) Markovian decision process(MDP) Monte Carlo simulation reinforcement learning(RL) smart grid

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Position Errors and Interference Prediction-Based Trajectory Tracking for Snake Robots

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IEEE/CAA Journal of Automatica Sinica 2023年第9期10卷 1810-1821页

作者： Dongfang Li Yilong Zhang Ping Li Rob Law Zhengrong Xiang Xin Xu Limin Zhu Edmond Q.Wu IEEE School of Electrical Engineering and Automation Fuzhou UniversityFuzhou 350108 the Sino-US Global Logistics Institute Shanghai Jiao Tong UniversityShanghai 200240 the Key Laboratory for Agricultural Machinery Intelligent Control and Manufacturing of Fujian Education Institutions Fuzhou 350108China School of Biological Science and Medical Engineering and the Key Laboratory for Biomechanics and Mechanobiology of Ministry of Education Beihang UniversityBeijing 100191China University of Macao Macao 999078China School of Automation Nanjing University of Science and TechnologyNanjing 210094China College of Intelligence Science and Technology National University of Defence TechnologyChangsha 410073China School of Mechanical Engineering Shanghai Jiao Tong UniversityShanghai 200240China Department of Automation Shanghai Jiao Tong UniversityShanghai 200240China

This work presents a trajectory tracking control method for snake *** method eliminates the influence of time-varying interferences on the body and reduces the offset error of a robot with a predetermined *** optimized line-of-sight(LOS)guidance strategy drives the robot’s steering angle to maintain its anti-sideslip ability by predicting position errors and ***,the predictions of system parameters and viscous friction coefficients can compensate for the joint torque control *** compensation is adopted to enhance the compatibility of a robot within ever-changing *** and experimental outcomes show that our work can decrease the fluctuation peak of the tracking errors,reduce adjustment time,and improve accuracy.

关键词： Anti-sideslip compensation snake robot trajectory tracking

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Sliding Mode control for Recurrent Neural Networks With Time-Varying Delays and Impulsive Effects

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IEEE/CAA Journal of Automatica Sinica 2023年第5期10卷 1319-1321页

作者： Lanfeng Hua Kaibo Shi Zheng-Guang Wu Soohee Han Shouming Zhong the School of Automation Engineering University of Electronic Science and Technology of ChinaChengdu 611731China the School of Electronic Information and Electrical Engineering Chengdu UniversityChengdu 610106China the Institute of Cyber-Systems and Control Zhejiang UniversityHangzhou 310027China the Department of Electrical Engineering and Convergence IT Engineering Pohang University of Science and TechnologyPohang 37673South Korea the School of Mathematics Sciences University of Electronic Science and Technology of ChinaChengdu 611731China

Dear Editor,This letter studies the problem of sliding mode control(SMC)design for recurrent neural networks(RNNs)with impulsive disturbances and time-varying transmission *** this end,an appropriate integral sliding ... 详细信息

关键词： impulsive letter delays

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Towards Low-Cost and High Precision: Software Enhanced Terrestrial Laser Scanner Consists of Consumer-Grade Multi-Beam LiDAR and Servo Motor

Towards Low-Cost and High Precision: Software Enhanced Terre...

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2023 China automation Congress, CAC 2023

作者： Peng, Pengfei Zhong, Xunyu Xie, Han Chen, Bushi Wang, Ningning Zhong, Xungao Xiamen University Department of Automation Xiamen China School of Electrical Engineering and Automation Xiamen University of Technology Xiamen China Xiamen Key Laboratory of Frontier Electric Power Equipment and Intelligent Control Xiamen China

ISBN: (纸本)9798350303759

3D laser scanning technology, as a rapid and non-contact measurement method, enables the acquisition of high-precision 3D data from the real world. It has been widely applied in the Architecture-engineering-Construction (AEC) industry for quality inspection, project progress management, reverse engineering, and building information modeling. However, the prevalent Terrestrial Laser Scanner (TLS) is often too expensive for widespread use. This paper proposes a low-cost TLS that combines multi-beam LiDAR with a high-precision servo motor. The LiDAR is driven by a motor to rotate, accumulating point clouds at different angles and generating dense point clouds. By employing software enhancements such as data time synchronization, calibration, and post-processing of point clouds, we improve the precision of the measurement results. Additionally, we extract planar elements (ceilings, floors, and walls) from the data obtained by the scanner in indoor environments, facilitating subsequent applications and processing. Through a series of qualitative and quantitative experiments, we have demonstrated that our system can achieve measurement data with an error average of 1 cm compared to commercial TLS while maintaining significantly lower costs. © 2023 IEEE.

关键词： Calibration

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