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A population randomization-based multi-objective genetic algorithm for gesture adaptation in human-robot interaction

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Science China(Information Sciences) 2021年第1期64卷 188-200页

作者： Luefeng CHEN Wanjuan SU Min LI Min WU Witold PEDRYCZ Kaoru HIROTA School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Department of Electrical and Computer Engineering University of Alberta Tokyo Institute of Technology

In recent years, vision-based gesture adaptation has attracted great attention from many experts in the field of human-robot interaction, and many methods have been proposed and successfully applied, such as particle swarm optimization and genetic algorithm. However, the reduction of the error and energy consumption of a robot while paying attention to more subtle attitude changes is very important and *** view of these problems, we propose a population randomization-based multi-objective genetic *** gesture signal is processed with a slight change by imitating the biological evolution mechanisms. In the proposed algorithm, a random out-of-order matrix is added in the process of population evolution synthesis to prevent the premature grouping convergence of the new population. The weights of the objective function and the elite retention strategy are adopted, and the most adaptable individuals in each generation are inherited directly in the next generation without any recombination or mutation. To verify the effectiveness of the algorithm, preliminary application experiments are performed on the gesture adaptation of a robotic arm. The results are compared with the original signal, and the comparison shows that by using the proposed method, the energy consumption is reduced, and the end error is decreased to less than 3 mm while ensuring the tracking effect of the robotic arm. These obtained results meet the communication requirements for human-robot interactions such as handshakes. Moreover, the proposed method has better performance, uses less energy, and has a smaller tracking error than the particle swarm optimization, the single-objective genetic algorithm, and the traditional multi-objective genetic algorithm. A preliminary application experiment indicates that the robotic arm can adapt to human gestures in real time.

关键词： multi-objective genetic algorithm gesture adaptation human-robot interaction

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Asynchronous Fault Detection for Fuzzy systems Based on Dynamic Event-Triggered Mechanism 42

Asynchronous Fault Detection for Fuzzy Systems Based on Dyna...

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42nd Chinese control Conference, CCC 2023

作者： Wang, Yuxi Wan, Xiongbo School of Automation China University of Geosciences 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)9789887581543

This article investigates the asynchronous fault detection (FD) problem for fuzzy systems with event-triggered mechanism (ETM). A new dynamic ETM (DETM) is adopted to further reduce the waste of network resources. Considering the impact of asynchronous premise variables brought by ETM, a design criterion for fuzzy FD filter (FDF) is derived. A reasonable residual evaluation function is constructed and an appropriate threshold is set. To ensure the error dynamics be asymptotically stable with a prescribed H∞ performance, we construct a new Lyapunov function that contains an internal dynamic variable in the ETM. A sufficient condition satisfying the proposed performance index is derived. Finally, we provide a numerical simulation to verify the effectiveness of the proposed asynchronous FD strategy under dynamic event-triggered (ET) communication. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Fault detection

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Energy-Aware Coverage control of Multi-Agent systems with control Barrier Function 42

Energy-Aware Coverage Control of Multi-Agent Systems with Co...

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42nd Chinese control Conference, CCC 2023

作者： Qu, Chengkai Zhai, Chao School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Ministry of Education Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan430074 China

ISBN: (纸本)9789887581543

Geo-hazards have become one of the main disasters endangering the safety of people's lives and property in the world. In order to improve the early warning of disasters, a persistent monitoring method of multi-agent systems is proposed in this work. To ensure that the agent's energy is never exhausted, the set invariance constraint is included in the optimization problem. The goal is to minimize the difference between the actual control input of the robot and the nominal control input corresponding to the task to be performed. Moreover, the control barrier function (CBF) is used to transform the forward invariance of a subset of the robot state space into a control input constraint. The coverage control method in an uncertain environment is verified by numerical simulation. This work provides new insights into effective monitoring and early warning of geo-hazards. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Multi agent systems

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Research on the Application of Big Data in Transient Stability Simulation of Power systems 4

Research on the Application of Big Data in Transient Stabili...

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4th International Conference on Energy, Power and Electrical Engineering, EPEE 2024

作者： Zhang, Jie Guo, Haiping Zhao, Yanjun Huang, Libin Hu, Binjiang Luo, Hui Zhang, Jingyue State Key Laboratory of Hvdc Electric Power Research Institute China Southern Power Grid Guangzhou510663 China National Energy Power Grid Technology R&d Centre Guangzhou510663 China Guangdong Provincial Key Laboratory of Intelligent Operation and Control for New Energy Power System Guangzhou510663 China Csg Key Laboratory for Power System Simulation Electric Power Research Institute China Southern Power Grid Guangzhou5106633 China

ISBN: (纸本)9798331518066

With the rapid expansion of smart grids, there is a growing complexity in power system dynamics, which increases the availability of real-time operational data and underscores the need for advanced transient stability simulations. Traditional transient stability analysis methods are constrained by their computational demands and may compromise accuracy. Furthermore, deep learning-based methods often focus on the application of a single algorithm, lacking a systematic consideration of the entire simulation process. To address these challenges, this study proposes a novel approach that leverages big data to enhance transient stability simulations. By integrating deep learning and ensemble learning techniques, the model significantly improves the accuracy and efficiency of predicting transient instabilities. The methodology utilizes a multi-source data acquisition and fusion scheme to ensure data comprehensiveness and a distributed storage architecture to handle large-scale datasets effectively. Advanced visualization technologies are also employed to enhance the interpretability of the simulation results. This comprehensive framework aims to support the safe and stable operation of power systems amid increasing complexity and data availability. © 2024 IEEE.

关键词： Transient stability

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A Novel intelligent Method for Extracting the Multi-Domain Features of Ground Penetrating Radar Data

A Novel Intelligent Method for Extracting the Multi-Domain F...

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2023 China Automation Congress, CAC 2023

作者： Zhang, Run Gan, Chao Cao, Weihua School of Automation China University of Geosciences 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)9798350303759

Ground Penetrating Radar (GPR) features are vital for accurately predicting the formation environment in the tunnel engineering. In this paper, a novel intelligent method for extracting the multi-domain (time domain, time frequency domain, and spatial domain) features of ground penetrating radar data is proposed. Firstly, the GPR exploration data is read to obtain the relative amplitude matrix. Secondly, multi-domain features are obtained using the following methods. The relative amplitude matrix of GPR is averaged by rows to obtain the time domain feature called the average relative amplitude(ARA). The S-transform is used to extract the time frequency domain feature called the average maximum weight frequency(AMWF) of the electromagnetic waves. And the events of the GPR images are highlighted by using Gaussian filtering and edge detection, and the spatial domain feature called the maximum event length(M EL) is obtained through contour detection. Finally, the three extracted multi-domain features are stored in the GPR feature database. Compared simulation results verify the effectiveness of the proposed method. © 2023 IEEE.

关键词： Matrix algebra

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Improved Kalman Filtering Algorithm Based Multi-Sensor Integration for Silicon Single Crystal Growth Process

Improved Kalman Filtering Algorithm Based Multi-Sensor Integ...

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International Symposium on Autonomous systems (ISAS)

作者： Ruidong Xie Pei Zhu Wenle Ma Zheqi Zhang Yingmin Yi Zheng Guo Key Lab of Manufacturing Equipment of Shaanxi Province Xi’an University of Technology Xi’an China Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi’an University of Technology Xi’an China

ISBN: (数字)9798350363173

ISBN: (纸本)9798350363180

The study primarily delves into addressing the data filtering challenge inherent in the silicon single crystal growth process by proposing a multi-sensor integrated detection approach. This approach is designed to alleviate the diminished filtering accuracy resulting from the reliance on a single sensor and the conventional Kalman filtering algorithm. By utilizing an enhanced adaptive Kalman filtering algorithm and the maximum likelihood estimation criterion to incorporate the innovation variance directly into the gain calculation of the Kalman filter, dynamic adjustment of the estimation model is achieved while interference from system noise and measurement noise is reduced. Finally, simulation-based comparative experiments between the adaptive and conventional Kalman filtering algorithms are performed. The results show that the performance of the adaptive Kalman filtering algorithm is superior to that of the conventional Kalman filtering algorithm in terms of accuracy and stability when detecting signals from multiple sensors. The research findings furnish dependable data support for refining the decision-making process in crystal growth technology, augmenting the precision and scientific integrity of crystal safety production scheduling and decision-making endeavors.

关键词： Crystal growth Filtering Noise Decision making Crystals Production Filtering algorithms

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Event-Triggered control of Networked system Considering Denial of Service Attack 42

Event-Triggered Control of Networked System Considering Deni...

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42nd Chinese control Conference, CCC 2023

作者： Zhang, Ting-Wei Fan, Yu-Long Zhang, Chuan-Ke School of Automation Chinese University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology of Geo-Exploration Ministry of Education Wuhan430074 China

ISBN: (纸本)9789887581543

This paper presents an improved stability criterion and controller design scheme condition for a networked control system under denial of service (DoS) attack. Firstly, the DoS attack interval is divided into attack interval and no attack interval, therefore, a switching-like event-triggered control can be established to reduce the waste of network resources and improve network efficiency. Then, the studied system is transformed into a time-delay system, and an improved stability criterion and controller design method are established by using Lyapunov-Krasovskii functional (LKF). Finally, the effectiveness of the proposed method is verified by a simulation example. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Networked control systems

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Dynamic Event-Triggered Synchronization control for complex Dynamical Networks 42

Dynamic Event-Triggered Synchronization Control for Complex ...

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42nd Chinese control Conference, CCC 2023

作者： Yang, Fuxiang Wan, Xiongbo School of Automation China University of Geosciences 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)9789887581543

This paper explores the finite-time synchronization of a class of discrete-time nonlinear singularly perturbed complex networks using a dynamic event-triggered mechanism (DETM). The DETM is designed to optimize packet transmission, aiming to conserve network resources. By constructing a Lyapunov function considering singularly perturbed parameters (SPPs) and DETM information, a sufficient condition for the dynamics of synchronization error system to be finite-time stable is given. The parameters of the synchronization controller can be determined by solving a set of matrix inequalities. The effectiveness of the proposed controller is demonstrated through a numerical example. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： complex networks

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Undersampling Ensemble and Deep Learning - Based Landslide Susceptibility Mapping Method for Geological Hazard Warning

Undersampling Ensemble and Deep Learning - Based Landslide S...

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2023 China Automation Congress, CAC 2023

作者： Fang, Yulong Gan, Chao Cao, Weihua School of Automation China University of Geosciences 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)9798350303759

Landslide is the most frequent geological hazard. Landslide susceptibility mapping (LSM) can be used to predict the possibility of landslide occurring at a certain location. In this paper, an undersampling ensemble and deep learning - based landslide susceptibility mapping method for geological hazard warning is proposed. The Zigui to Badong section of the Three Gorges Reservoir is taken as the study area. Firstly, the correlation analysis of fourteen landslide influencing factors is carried out and two unimportant factors are eliminated. Then, an EasyEnsemble - one dimensional convolutional neural network (EE-1DCNN) model is constructed with the remaining twelve factors as inputs. Finally, the proposed EE-1DCNN model is compared with two well-known methods on test data, and a landslide susceptibility map of the study area is obtained based on the EE-1DCNN model. As the experimental result shows, the proposed EE-1DCNN model achieves superior AUC, accuracy and recall of 0.909, 91.7% and 85.1%. The applicability of the proposed method is proved. © 2023 IEEE.

关键词： Landslides

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Modeling and Simulation Design of Single Crystal Silicon Growth by Czochralski Method

Modeling and Simulation Design of Single Crystal Silicon Gro...

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Mechatronics Technology and intelligent Manufacturing (ICMTIM), International Conference on

作者： Ruidong Xie Wenle Ma Zheqi Zhang Pei Zhu Yingmin Yi Key Lab of Manufacturing Equipment of Shaanxi Province Xi’an University of Technology Xi’an China Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi’an University of Technology Xi’an China

ISBN: (数字)9798350363265

ISBN: (纸本)9798350363272

Due to difficulties in observing crystal state and the high cost of crystal preparation, the teaching of the Czochralski single crystal silicon production is complex. To solve the above problem, a digital twins-inspired virtual simulation system for the growth of single crystal silicon was developed. The 3D models of the single crystal furnace, single crystal silicon rods, and other related objects were created using Blender. The nonlinear model of the single crystal silicon growth process was established based on the heat conduction during crystal growth and geometric deformation. The 3D models were then imported into the web page using ***. The PID control algorithm was used to control the temperature and pulling speed, and finally, the B/S architecture was adopted to design and implement the virtual simulation experiment system for the growth of Czochralski single crystal silicon. The virtual simulation method will help to overcome the shortcomings of on-site experiment teaching and enhance students’ understanding of the entire single crystal silicon preparation process.

关键词： Crystal growth Heating systems Solid modeling Three-dimensional displays PI control Furnaces Education

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