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Data Driven control and Learning systems (DDCLS)

作者： Anqi Shangguan Nan Feng Lingxia Mu Rong Fei Xinhong Hei Guo Xie Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology Xi'an China School of computer science and Engineering Xi'an University of Technology Xi'an China

Since the cumbersome collection process and high cost, the collected degradation of the product is basically small samples, which will affect the accuracy of reliability evaluation. It is necessary to expand the degradation to improve the accuracy of later reliability assessment. Therefore, a degradation generation and prediction method is proposed combining the time series generator adversarial network (TimeGAN) and stochastic process. Firstly, the input degradation is expanded by the sliding window to improve the later training accuracy; Then, the construction of the generator in TimeGAN is linked with the stochastic process to make the generation data more realistic. Finally, the results of degradation prediction by the Gated Recurrent Unit (GRU) can be obtained. Two datasets and different generation methods are adopted to evaluate the effectiveness of the proposed method. The results shows that the Kullback-Leibler(KL) divergence is the smallest, and the prediction error is the smallest compared with the other methods. So, the proposed method is proved that it is valid in the degradation generation and prediction, and can be used for the further reliability assessment of the product in the industrial system.

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Distributed stochastic projection-free solver for constrained optimization

arXiv

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arXiv 2022年

作者： Jiang, Xia Zeng, Xianlin Xie, Lihua Sun, Jian Chen, Jie Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing100081 China The Beijing Institute of Technology Chongqing Innovation Center Chongqing401120 China Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing100081 China The School of Electrical and Electronic Engineering Nanyang Technological University Singapore639798 Singapore The School of Electronic and Information Engineering Tongji University Shanghai200082 China

This paper proposes a distributed stochastic projection-free algorithm for large-scale constrained finite-sum optimization whose constraint set is complicated such that the projection onto the constraint set can be expensive. The global cost function is allocated to multiple agents, each of which computes its local stochastic gradients and communicates with its neighbors to solve the global problem. Stochastic gradient methods enable low computational cost, while they are hard and slow to converge due to the variance caused by random sampling. To construct a convergent distributed stochastic projection-free algorithm, this paper incorporates a variance reduction technique and gradient tracking technique in the Frank-Wolfe update. We develop a sampling rule for the variance reduction technique to reduce the variance introduced by stochastic gradients. Complete and rigorous proofs show that the proposed distributed projection-free algorithm converges with a sublinear convergence rate and enjoys superior complexity guarantees for both convex and non-convex objective functions. By comparative simulations, we demonstrate the convergence and computational efficiency of the proposed algorithm. © 2022, CC BY.

关键词： Stochastic systems

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Incipient Gradual Fault Detection via Transformed Component and Dissimilarity Analysis

Incipient Gradual Fault Detection via Transformed Component ...

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Industrial Cyber-Physical systems (ICPS)

作者： Lingxia Mu Wenzhe Sun Youmin Zhang Nan Feng Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology Xi'an China Department of Mechanical Industrial & Aerospace Engineering Concordia University Montreal Canada

This paper proposes a novel method named recursive transformed component dissimilarity analysis (RTCDA) combining dissimilarity analysis algorithm and traditional sliding window technique for detecting incipient gradual faults. Firstly, orthogonal transformed components (TCs) corresponding to a new set of data in the sliding window are obtained using a recursive algorithm based on rank-one modification. Then, to quantitatively estimate the distribution difference of TCs, the dissimilarity index between TCs of the new dataset and that of referenced dataset is calculated. The distribution of TCs changes more dramatically than that of original data after a small quantitative bias in the original data. Compared with original data, TCs are more sensitive to tiny quantitative variation of dataset. Finally, case studies on a numerical example and a practical industrial fed-batch penicillin fermentation process are carried out to evaluate the performance of RTCDA method for incipient gradual fault detection.

关键词： Fault detection Cyber-physical systems Indexes Data mining

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A non-uniform Gauss pseudospectral method based on curvature information for dynamic optimization problem

A non-uniform Gauss pseudospectral method based on curvature...

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第32届中国过程控制会议(CPCC2021)

作者： Lu Lv Qian Zhang Jianzhong Su Wenhai Wang Jianquan Yuan Zijian Tian Zhenghui Zhang Long Xiao Zeyin Zhang Xinggao Liu Zhejiang University NGICS Platform State Key Laboratory of Industrial Control TechnologyControl DepartmentZhejiang University Tianjin Jinhang Institute of Technical Physics Science and Technology on Complex System Control and Intelligent Agent Cooperative Laboratory Mathematics Department Zhejiang University

Dynamic optimization for hypersonic reentry vehicle(HRV) is a challenge for complex nonlinear constraints during a global strike *** to the strong nonlinearity of HRV,it is difficult to guarantee the precision of complex constraints on non-collocation points with traditional Gauss pseudospectral method(GPM).A novel approach which provides an optimal control strategy considering the above challenges is then ***,an adaptive mesh refinement strategy based on curvature information is presented to improve the accuracy of GPM.A collocation point redistribution method based on error analysis is then proposed to further improve the accuracy of the ***,a detection mechanism is proposed to correct the results on-line when the path constraint is not *** proposed approaches are finally applied to a classic HRV problem and compared with other literature work in *** research results validate the effectiveness of the proposed methods.

关键词： nonlinear optimal control Gauss pseudospectral method adaptive mesh refinement hypersonic reentry vehicle

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Cooperative Search Strategy of Multiple UAVs Based on Matrix Game 19

Cooperative Search Strategy of Multiple UAVs Based on Matrix...

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19th International Bhurban Conference on Applied Sciences and Technology, IBCAST 2022

作者： Song, Dalei Wang, Xiaoqian Dai, Aoliang Ma, Hongjun Wei, Donghui Shenyang University of Technology School of Information Science and Engineering Shenyang China Northeastern University School of Information Science and Engineering Shenyang China South China University of Technology School of Information Science and Engineering Guangdong China Beijing Research Institute of Mechanical & Electrical Technology Key Laboratory of Complex System Control and Intelligent Collaboration Technology Beijing100074 China

ISBN: (数字)9781665460514

ISBN: (纸本)9781665460514

For the regional search problem of multiple unmanned air vehicles (UAVs) ,a cooperative search strategy of multiple UAVs is proposed based on action matrix game (AMG) for intelligent moving targets on the ground in this paper. Based on the proposed AMG, the yaw angle and position information of the target is described in probability matrix, and the matrix is updated by Nash equilibrium and receding horizon control in every control cycle. Simulation results show that this strategy deduces the searching time for revisiting the reference target, and improves the success rate for moving targets searching. © 2022 IEEE.

关键词： Game theory

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UAV Trajectory Generation Based on Integration of RRT and Minimum Snap Algorithms

UAV Trajectory Generation Based on Integration of RRT and Mi...

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Chinese Automation Congress (CAC)

作者： Bohui Shi Youmin Zhang Lingxia Mu Jing Huang Jing Xin Yingmin Yi Shangbin Jiao Guo Xie Han Liu Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi’an University of Technology Xi’an Shaanxi China Industrial and Aerospace Engineering Concordia University Montreal Quebec Canada

ISBN: (数字)9781728176871

ISBN: (纸本)9781728176888

Aiming at the problems that carrying out forest fire monitoring and fighting missions by using the Rapidly-exploring Randomized Tree (RRT) algorithm to plan paths cannot adapt to the autonomous movement of an Unmanned Aerial Vehicle (UAV) and that high-order dynamic characteristics may mutate during the mission, this paper investigates a trajectory generation algorithm based on the integration of the RRT algorithm and the minimum snap algorithm. First, the RRT algorithm is used to generate the initial path, then the minimum snap algorithm is used to smooth the initial path and obtain a trajectory suitable for the actual flight of the UAV. However, because the UAV is considered as a particle in the simulation, during the actual flight, this trajectory may not guarantee the safe flight of the UAV and may cause the UAV to collide with an obstacle or other nearby UAVs in the cases of formation flight. To solve this problem, flight corridor concept is used to limit the UAV's flight trajectory for ensuring the safe flight of the UAV. Simulation results show that the algorithm can effectively ensure the safety, smoothness, feasibility, and trajectory of unmanned aerial vehicles.

关键词： Vegetation Forestry Path planning Unmanned aerial vehicles Heuristic algorithms Trajectory optimization Safety

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Early Forest Fire Segmentation Based on Deep Learning

Early Forest Fire Segmentation Based on Deep Learning

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2021 CAA Symposium on Fault Detection, Supervision, and Safety for Technical Processes, SAFEPROCESS 2021

作者： Li, Mengna Zhang, Youmin Xin, Jing Mu, Lingxia Yu, Ziquan Liu, Han Xie, Guo Jiao, Shangbin Yi, Yingmin Xi'an University of Technology Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Shaanxi Xi'an710048 China Concordia University Department of Mechanical Industrial and Aerospace Engineering MontrealQCH3G 1M8 Canada Nanjing University of Aeronautics and Astronautics College of Automation Engineering Nanjing211106 China

ISBN: (纸本)9781665401159

Fire segmentation is very important for fire rescue. It can make firefighters get the information on fire area, spread direction and so on, and then help them make quick and effective fire-fighting plan. Therefore, this paper proposes an early forest fire segmentation algorithm based on a deep learning model, named F-Unet, which mainly uses the architecture idea of Unet for reference. F-Unet consists of contraction path, feature fusion layer and expansion path. The contraction path is composed of the first 13 layers of VGG16, which is used to obtain feature maps with different scales. In order to improve the segmentation accuracy of the model, the feature fusion network proposed in this paper is added to the Unet architecture to fuse these feature maps with different scales. The expansion path is used for upsampling these feature maps to restore the size of the original input image and obtain the fire segmentation results. The experimental testing results on the FLAME dataset show that F-Unet can significantly improve the fire segmentation precision, and also prove that the proposed feature fusion network is effective to improve the performance of fire segmentation. © 2021 IEEE.

关键词： Deforestation

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A NSGA-Ⅱ based Peak Load Shifting Optimization Method for Customers with Distributed Generators Considering Time-of-use Price

A NSGA-Ⅱ based Peak Load Shifting Optimization Method for C...

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第37届中国控制会议

作者： Hao Zhou Min Ding Bo Hu Qingyi Wang Zhili Tan Danyun li School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex System State Grid Energy Research Institute Co. LTD.

With the extensive use of distributed generation, the traditional demand response analysis cannot meet the current *** paper proposes a NSGA-II based peak load shifting optimization method for customers with distributed generators considering time-of-use price. Firstly, a fuzzy classification method divides the daily power into three time segments,peak hours, flat hours and valley hours. Secondly, on the basis of the time-of-use price, a peak load shifting optimization model is built with constraints and the objectives of minimizing the peak load, maximizing the valley load, and minimizing the peakvalley difference. Then, a NSGA-II based optimization method solves the optimal model and obtains the optimal electricity prices of different time segments to shift the peak load and the valley load. Finally, the simulation results shows the effectiveness of the proposed method.

关键词： Distributed Generation Demand Respond Time-of-use Price Multi-objective Genetic Algorithm

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Gait Planning and Motion control Based on Vrep Simulation for Quadruped Robot

Gait Planning and Motion Control Based on Vrep Simulation fo...

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WRC Symposium on Advanced Robotics and Automation (WRC SARA)

作者： Linqi Zhou Zhihua Chen Jun Liu Zhi Liu Yumeng Chen Liting Zhang key Laboratory of Jiangxi Province for Image Processing and Pattern Recognition and MOE Key Lab of Nondestructive Testing Technology Nanchang Hangkong University Nanchang China State Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing China

Gait planning of quadruped robots plays an important role in achieving less walking, including dynamic and static gait. In this article, a static and dynamic gait control method based on center of gravity stability margin is proposed. Firstly, the robot model and kinematics modeling are introduced. Secondly, the robot’s foot static and dynamic gait were planned and the foot trajectory was designed. Finally, two types of gait of the robot were simulated using Vrep simulation software, and the differences in stability and speed between the coordinated gait with speed and stability in the static and dynamic gait of a 12 degree of freedom robot were analyzed, verifying the effectiveness of the gait control method proposed in this paper.

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A novel modeling method of T-S fuzzy system and application

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Beijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology 2010年第SUPPL. 1期30卷 103-106页

作者： Gao, Zhe Liao, Xiao-Zhong Sha, De-Shang School of Automation Beijing Institute of Technology Beijing 100081 China Key Laboratory of Complex System Intelligent Control and Decision Ministry of Education Beijing 100081 China

A novel modeling method of T-S fuzzy system for an affine nonlinear system is proposed. Based on this method, the responses of T-S fuzzy system is the same as the original nonlinear, the modeling error is avoided compared with the linearization method around the equilibrium points, and this method can be applied the nonlinear system contained the multiple nonlinear terms. T-S fuzzy model of GMAW system is established, the response characteristics of the T-S fuzzy system are not changed compared with the nonlinear GMAW system. The simulation result proves the validity of this method.

关键词： Nonlinear systems

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