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43rd Chinese control Conference, CCC 2024

作者： Lv, Ji Ding, Min Li, Quanhui Zhou, Sibei Fang, Zhijian China University of Geosciences School of Automation Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China

ISBN: (纸本)9789887581581

Accurate short-term power load forecasting is important to ensure the reliability and economy of the power grid. Convolutional neural networks are widely used, but they are difficult to capture the multi-scale temporal characteristics of load data. To address this problem, this study proposes a short-term load forecasting method based on a multi-branch CNN architecture and Bayesian optimisation. By using different sizes of convolutional kernels in different branches, different time-scale features of power load data are captured to improve the identification of rapid changes and potential long-term trends. In addition, the hyperparameters of the forecasting model are automatically adjusted by a Bayesian optimisation algorithm to achieve the best forecasting performance. In forecasting experiments on real load data, the method in this paper significantly improves the forecasting accuracy compared to baseline models. © 2024 Technical Committee on control Theory, Chinese Association of automation.

关键词： Convolutional neural networks

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A joint sparse Bayesian learning for wideband DOA estimation

A joint sparse Bayesian learning for wideband DOA estimation

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2024 Conference on Spectral Technology and Applications, CSTA 2024

作者： Zhao, Yonghong Liu, Jisong Wang, Junlong Dong, Shuxin Shannxi Key Laboratory of Complex System Control and Intelligent Information Processing Department of Automation and Information Engineering Xi'an University of Technology Shaanxi Xi'an710048 China

ISBN: (纸本)9781510683082

Wideband direction of arrival (DOA) estimation using sensor array is a noteworthy problem frequently occurring in many applications involving radar, sonar, and communication. We present a wideband DOA method based on a sparse Bayesian learning of multiple sub-bands jointly with the redundant dictionary matrix at the reference frequency. Explicitly enforcing the focusing operation and the singular value decomposition (SVD) to sensor measurements is motivated by a desire to decrease the computational complexity and storage capacity. A joint sparse Bayesian learning framework is proposed to deal with multiple sub-bands under one segment to obtain the DOA information. Moreover, the proposed method can be directly extended to multiple segments. Comparing to other wideband DOA estimation methods, the proposed method has the advantages of increased resolution, higher accuracy, and correlation of the sources, as well as not requiring the initial angles for the focusing matrix. Simulations are provided to show the effectiveness and improved performance of the proposed method. © 2024 SPIE.

关键词： Direction of arrival

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Neural-network-based stochastic linear quadratic optimal tracking control scheme for unknown discrete-time systems using adaptive dynamic programming

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control Theory and Technology 2021年第3期19卷 315-327页

作者： Xin Chen Fang Wang School of Automation China University of GeosciencesWuhan430074HubeiChina Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074HubeiChina

In this paper,a stochastic linear quadratic optimal tracking scheme is proposed for unknown linear discrete-time(DT)systems based on adaptive dynamic programming(ADP)***,an augmented system composed of the original system and the command generator is constructed and then an augmented stochastic algebraic equation is derived based on the augmented ***,to obtain the optimal control strategy,the stochastic case is converted into the deterministic one by system transformation,and then an ADP algorithm is proposed with convergence *** the purpose of realizing the ADP algorithm,three back propagation neural networks including model network,critic network and action network are devised to guarantee unknown system model,optimal value function and optimal control strategy,***,the obtained optimal control strategy is applied to the original stochastic system,and two simulations are provided to demonstrate the effectiveness of the proposed algorithm.

关键词： Stochastic system Optimal tracking control Adaptive dynamic programming Neural networks

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Phenomenological Modeling and End-Point Trajectory Tracking control of a Flexible Beam with Pneumatic Soft Actuators 6

Phenomenological Modeling and End-Point Trajectory Tracking ...

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6th International Conference on intelligent Robotics and control Engineering, IRCE 2023

作者： Sun, Xuefeng Meng, Qingxin Wu, Jundong Zhu, Mingliang School of Automation China University of Geosciences Wuhan Hubei430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan Hubei430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan Hubei430074 China

ISBN: (纸本)9798350326338

As the basic construction of flexible mechanical systems, the flexible beam and its control problem have attracted widespread attention in recent years. This paper takes a flexible beam with pneumatic soft actuators (FBPSA) as the research object and studies its phenomenological modeling and end-point trajectory tracking control strategy. Firstly, we develop an experimental platform for the FBPSA and perform tests on it, gathering its input and output data. Using these collected data, we analyzed the motion characteristics of the FBPSA. Subsequently, a phenomenological model is established to describe the motion characteristics of the system, and the parameters of this model are identified through a large amount of the collected experimental data. Then, a combined feedforward-feedback control strategy is proposed to achieve the end-point trajectory tracking control of the system. Finally, three sets of experiments are carried out to verify the accuracy of the established model and the effectiveness and superiority of the control strategy. © 2023 IEEE.

关键词： Trajectories

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Dynamic Sensing Modeling of Dielectric Elastomer Sensors Based on GRU Neural Network 6

Dynamic Sensing Modeling of Dielectric Elastomer Sensors Bas...

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6th International Conference on intelligent Robotics and control Engineering, IRCE 2023

作者： Zhang, Mingyi Huang, Peng Wang, Yawu School of Automation China University of Geosciences Wuhan Hubei430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan Hubei430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan Hubei430074 China

ISBN: (纸本)9798350326338

Dielectric elastomer sensor (DES) is a flexible sensor that can perform free bending deformation, thus it has broad application prospects in the fields of medical electronics, wearable devices, soft robots, etc. Previous studies have mostly focused on exploring the static sensing characteristics of the DES. Considering that the DES may be used in dynamic conditions, it is very meaningful to study its dynamic sensing characteristics to broaden its application ranges. In this paper, a dynamic sensing model of the DES is established based on the gate recurrent unit (GRU) neural network. Firstly, the structure of the DES and the construction of the experimental system are introduced. In addition, the dynamic sensing characteristics of the DES are analyzed by conducting several sets of experiments, which shows that the DES has significant rate-dependent hysteresis nonlinearities, multivalued mapping and memory characteristics. After that, the dynamic sensing model of the DES is built based on the GRU neural network to describe the above dynamic sensing characteristics. Next, the dynamic displacement and force sensing models of the DES are trained according to the dynamic displacement-capacitance and dynamic force-capacitance experimental data, respectively. Finally, several experiments are performed to verify the effectiveness and generalization ability of the established dynamic sensing model. © 2023 IEEE.

关键词： Capacitance

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PDM control Strategy of Extremely High Gain ICPT system Applying for Electrical Isolation Aimed at Maximum Efficiency 48

PDM Control Strategy of Extremely High Gain ICPT System Appl...

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48th Annual Conference of the IEEE Industrial Electronics Society, IECON 2022

作者： Yue, Haojiang Fang, Zhijian Xia, Yuangeng China University of Geosciences Wuhan Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems School of Automation Wuhan China

ISBN: (数字)9781665480253

ISBN: (纸本)9781665480253

In order to achieve electrical isolation, high-voltage transformers must use insulating materials. However, in some applications, such as medical treatment, transformers using insulating materials may cause problems of weight increase and flexible movement. As a result, the inductively coupled power transfer (ICPT) system are used to replace regular high transformers, with the air gap between the primary and secondary coils serving as electrical insulation. Under the SP resonance compensation structure, the ICPT system needs to achieve exceptionally high gain, which will result in the voltage gain being sensitive to frequency variations. When the frequency deviates slightly from the resonance point, more circulation and loss occurs, lowering the efficiency of the system. Therefore, this paper proposes a control strategy based on the combination of pulse-duration modulation (PDM) and maximum efficiency point tracking (MEPT) is proposed, at the first resonance point of the ICPT system based on the SP resonance compensation structure. This control method is capable of producing medium and high voltage constant voltage output, and the switch tube achieves zero current switching during operation. In the case of a wide load variation range, maximum efficiency point tracking may be obtained at the same time. Finally, a 100W high-gain ICPT experimental platform is built, and the constant voltage output with 25 times high gain is realized over the transmission distance of 11.2cm, which verifies the effectiveness of the control strategy. © 2022 IEEE.

关键词： Pulse width modulation

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Design and application of intelligent monitoring system for geological hazards 41

Design and application of intelligent monitoring system for ...

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第41届中国控制会议

作者： Yutong Pan Chengda Lu Wanke Yu Min Wu School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

With the development and utilization of natural resources,geological hazards have posed a great threat to people's life and property *** is of great significance to realize the design of distributed geological disaster monitoring experimental system aimed at a series of problems,such as ecological environmental damage and major natural ***,this paper conducts the system requirements analysis based on the Three Gorges area as an ***,the system architecture and function is designed,and the system hardware configuration and application software design are carried ***,geological hazards intelligent monitoring system is developed and has been verified in Zigui-Badong region of the Three Gorges,which can effectively improve the information utilization rate and monitoring efficiency in the process of geological hazards *** results show that the system works well and can effectively monitor the occurrence of geolo gical hazards.

关键词： Geological hazards system design hardware configuration application software the Three Gorges

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Dynamic Scheduling for Airport Special Vehicles Based on a Multi-strategy Hybrid Algorithm 41

Dynamic Scheduling for Airport Special Vehicles Based on a M...

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第41届中国控制会议

作者： Wei Quan Chen Chen Zhuang Shao Kai Meng School of Automation Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex System

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

When arriving at the airport,flight needs to be served by special *** at the dynamic time window scheduling problem of airport refueling vehicles,this paper establishes a vehicle routing problem model with time window to minimize the operating ***,a multi-strategy genetic algorithm is designed to gain the solve time window scheduling problem,which employs the crossover based on particle swarm optimization to accelerate the early search capability,and the local search method based on simulated annealing to increase the local optimization *** aiming at dynamically adjusting vehicle routes on the basis of static scheduling,a local replanning strategy based on a dynamic time window is introduced,which uses the original route matching and rescheduling *** results show that the multi-strategy hybrid algorithm can effectively reduce the number of routes and vehicles the airport *** different scales' dynamic changes of time windows,the algorithm could enable vehicles to still meet time constraints and effectively minimize the change of routes.

关键词： vehicle scheduling multi-strategy genetic algorithm dynamic scheduling local replanning strategy

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Prediction Method of Blast Furnace Fuel Ratio Based on Spectral Clustering and Extreme Learning Machine Model 41

Prediction Method of Blast Furnace Fuel Ratio Based on Spect...

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第41届中国控制会议

作者： Jingjie Liang Yan Yuan Shuqiao Wang Zhuofu Zhang School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

The blast furnace fuel ratio,as the main index reflecting the blast furnace fuel consumption,plays an important role in guiding blast furnace *** order to solve the problem of insufficient stability of the existing fuel ratio prediction model under the condition of process parameters fluctuation,a prediction method of blast furnace fuel ratio based on spectral clustering and extreme learning machine model is ***,on the basis of analyzing the influencing factors of fuel ratio,the classification results after clustering are visualized with t-SNE dimension reduction downscaling and spectral clustering method;Secondly,for the classification results after clustering,the extreme learning machine is used to establish the sub-models,and the PSO algorithm was used to optimize the input weights of hidden layer and the bias of hidden layer *** results show that the proposed method has high prediction accuracy.

关键词： Fuel Ratio Spectral Clustering Extreme Learning Machine(ELM) t-SNE Particle Swarm Optimization(PSO)

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Distributed control Algorithm for Workload Partition of Multi-agent systems with Time Delay 41

Distributed Control Algorithm for Workload Partition of Mult...

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第41届中国控制会议

作者： Pengyang Fan Chao Zhai School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

In the problem of multi-agent coverage,a group of agents are required to cover a given region or clean the workload as soon as *** workload partition can improve the work efficiency of multi-agent *** addition,the communication delays play a key role in the stability of multi-agent ***,a distributed control algorithm of workload partition with time delay is proposed in this ***,an approach based on nonlinear matrix inequality is presented to find the maximum delay of multi-agent ***,experiments are carried out to investigate the effect of delay on system stability on the ZigBee platform.

关键词： Multi-agents systems Time delay Nonlinear matrix inequality Distributed algorithm Workload partition

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