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IEEE International Conference on Unmanned systems (ICUS)

作者： Danting Sheng Jin Cheng Fengyi Li Mingrui Hao Beijing Electro-mechanical Engineering Institute CASIC Beijing China HIWING Technology Academy of CASIC CASIC Beijing China National Key Laboratory of Complex System Control and Intelligent Agent Cooperation CASIC Beijing China

ISBN: (数字)9798350384185

ISBN: (纸本)9798350384192

In practical applications of cooperative navigation algorithms based on Kalman filtering, noise is often colored noise, which does not meet the requirement of Gaussian white noise for Kalman filtering. Therefore, an algorithm is proposed to identify and compensate for colored noise online using a BP neural network. Firstly, a cooperative navigation model based on Kalman filtering is established. Then, by studying the update process of Kalman filtering, the neural network is incorporated into the prediction calculation of the observations, following the online learning and updating of the Kalman filter. Mathematical simulations show that under conditions of colored noise, the results of the Kalman filter diverge. However, after correction by the BP neural network, the filtering converges, providing high reference value for improving the accuracy of cooperative navigation.

关键词： Accuracy Filtering Navigation Neural networks Collaboration White noise Mathematical models Kalman filters Colored noise Convergence

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Edge-guided image estimation for array Gm-APD Lidar in smoky environment using multi-scale depth images 6

Edge-guided image estimation for array Gm-APD Lidar in smoky...

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6th Optics Young Scientist Summit, OYSS 2023

作者： Zhang, Yinbo Li, Sining Sun, Jianfeng Jiang, Peng Zhang, Hailong Liu, Zhihui Zhu, Yuebing National Key Laboratory of Science and Technology on Tunable Laser Institute of Opto-Electronic Harbin Institute of Technology Heilongjiang Harbin150001 China Zhengzhou Research Institute of Harbin Institute of Technology Henan Zhengzhou450000 China Science and Technology on Complex System Control Intelligent Agent Cooperation Laboratory Beijing100074 China Sichuan Jiuzhou Electrical Group Company Limited Sichuan Mianyang621000 China

ISBN: (纸本)9781510672642

Limited statistical frame number and strong backscatter interference from smoke result in a photon-starved regime, severely limiting the depth imaging capability of array Gm-APD lidar in smoky environment. Here, we propose a depth image estimation algorithm that can significantly improve the integrity of targets in dense smoke environments when signal photons are starved. At the signal level, the algorithm improves the accuracy of extracting signal photons by constructing multi-scale superpixels. At the image level, using edge information of depth images at different scales to guide and fill the original scale depth image achieves efficient noise reduction and improves target integrity. It has been successfully demonstrated under different attenuation lengths and statistical frame numbers. Compared with other state-of-the-art methods, the proposed algorithm has maximum target recovery and structural similarity, especially for the attenuation length (AL) is 3.6 and statistical frame number is 1500 (imaging time is 75ms). This study is of great significance for the fast depth imaging of dynamic targets by array Gm-APD lidar in dense smoke environments. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Optical radar

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ICP algorithm point cloud registration method based on a new improved Harris Hawk algorithm

ICP algorithm point cloud registration method based on a new...

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2021 China Automation Congress, CAC 2021

作者： Wang, Chen Jiao, Shangbin Gao, Rui Li, Yuxing School of Automation and Information Engineering 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 School of Electronic and Electrical Engineering Baoji University of Arts and Sciences Baoji China Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology Baoji China

ISBN: (纸本)9781665426473

To address shortcomings of ICP algorithm, which is sensitive to the initial position and easy to fall into local optimum, we propose a Harris Hawks Optimizer (HHO) point cloud registration method combining PCA preprocessing and parallel population initialization. The PCA method is used to align the point clouds with the main axes and perform the main axes correction. Since the six input variables in the population initialization stage of HHO point cloud registration are different and independent, the initial population of HHO algorithm is initialized by the parallel initialization method. The results show that the improved algorithm is able to successfully overwhelm the fault of ICP algorithm, and its global seek performance and optimization accuracy are more advantageous, and the algorithm operates efficiently, with high registration accuracy and robustness. © 2021 IEEE

关键词： PCA HHO Parallel Computing ICP

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Event-triggered Consensus control of Heterogeneous Multi-agent systems: Model- and Data-based Analysis

arXiv

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arXiv 2022年

作者： Wang, Xin Sun, Jian Wang, Gang Chen, Jie The School of Automation The Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology Beijing10081 China The Beijing Institute of Technology Chongqing Innovation Center Chongqing401120 China The Department of Control Science and Engineering Tongji University Shanghai201804 China The State Key Lab of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing100081 China

This article deals with model- and data-based consensus control of heterogenous leader-following multi-agent systems (MASs) under an event-triggering transmission scheme. A dynamic periodic transmission protocol is developed to significantly alleviate the transmission frequency and computational burden, where the followers can interact locally with each other approaching the dynamics of the leader. Capitalizing on a discrete-time looped-functional, a model-based consensus condition for the closed-loop MASs is derived in form of linear matrix inequalities (LMIs), as well as a design method for obtaining the distributed controllers and event-triggering parameters. Upon collecting noise-corrupted state-input measurements during open-loop operation, a data-driven leader-following MAS representation is presented, and employed to solve the data-driven consensus control problem without requiring any knowledge of the agents' models. This result is then extended to the case of guaranteeing an H∞ performance. A simulation example is finally given to corroborate the efficacy of the proposed distributed event-triggering scheme in cutting off data transmissions and the data-driven design method. Copyright © 2022, The Authors. All rights reserved.

关键词： Linear matrix inequalities

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Scheduling optimization of silicon single crystal production process based on adaptive improved particle swarm optimization

Scheduling optimization of silicon single crystal production...

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2021 China Automation Congress, CAC 2021

作者： Kang, Lu Liu, Ding Wu, Yali Ping, Guozheng School of Automation and Information Engineering Xi'an University of Technology National and Local Joint Engineering Research Center of Crystal Growth Equipment and System Integration Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an710048 China School of Automation and Information Engineering Xi'an University of Technology National and Local Joint Engineering Research Center of Crystal Growth Xi'an University of Technology Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an710048 China School of Automation and Information Engineering Xi'an University of Technology Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an710048 China

ISBN: (纸本)9781665426473

Aiming at the potential safety hazards of silicon single crystal production enterprises in the process of multi-furnace silicon single crystal production, and considering the maximum power load requirements in actual enterprises, a silicon single crystal production process scheduling model with the goal of minimizing the maximum completion time was established. Based on this model, an adaptive improved particle swarm optimization algorithm (Adaptive GPSO) is proposed to solve it. The algorithm retains the individual optimal value and global optimal value of the particle swarm algorithm, and introduces the crossover operation and mutation operation in the genetic algorithm to improve the new individual generation mechanism. At the same time, it performs dynamic iterative calculations on the mutation probability and crossover probability to avoid the algorithm fall into the local optimum, and improve the diversity and convergence of the algorithm. By solving different scales scheduling problems of silicon single crystal production process, the experiments on real-world data shows that the feasibility and effectiveness of the proposed algorithm. © 2021 IEEE

关键词： Genetic algorithms

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Primal-dual Accelerated Mirror-Descent Method for Constrained Bilinear Saddle-Point Problems

arXiv

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arXiv 2024年

作者： Li, Weijian Zeng, Xianlin Pavel, Lacra The Department of Electrical and Computer Engineering University of Toronto TorontoONM5S 3G4 Canada The Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing100081 China

We develop a first-order accelerated algorithm for a class of constrained bilinear saddle-point problems with applications to network systems. The algorithm is a modified time-varying primal-dual version of an accelerated mirror-descent dynamics. It deals with constraints such as simplices and convex set constraints effectively, and converges with a rate of O(1/t2). Furthermore, we employ the acceleration scheme to constrained distributed optimization and bilinear zero-sum games, and obtain two variants of distributed accelerated algorithms. Copyright © 2024, The Authors. All rights reserved.

关键词： Mirrors

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Parameter estimation of time fractional heat conduction equation for monocrystalline silicon

Parameter estimation of time fractional heat conduction equa...

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2021 China Automation Congress, CAC 2021

作者： Shi, Shuyan Liu, Ding Zhao, Zhongdan Local Joint Engineering Research Center of Crystal Growth Equipment and System Integration Shananxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology Xi'an710048 China

ISBN: (纸本)9781665426473

In this paper, a time-fractional heat conduction model is established to describe the heat transfer process of monocrystalline silicon in the Czochralski method. The numerical solution of the fractional-order model is obtained by using implicit difference scheme. In addition, an improved grey wolf algorithm is proposed to estimate the parameters of the fractional heat conduction model using the experimental temperature data. The numerical experiment results show that the time-fractional heat conduction model has a higher explanatory ability, compared with the classical heat conduction model. The Improved Grey Wolf algorithm proposed in this paper is effective in solving the parameter estimation problem of the time-fractional heat conduction equation. © 2021 IEEE

关键词： Heat conduction

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Constraint-Following Based Adaptive Robust control for Underactuated Mechanical systems

Constraint-Following Based Adaptive Robust Control for Under...

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International Conference on control, Automation, Robotics and Vision (ICARCV)

作者： Cui Wei Ye-Hwa Chen Yanling Wei Institute of Intelligent Manufacturing Nanjing Tech University Nanjing China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing China George W. Woodruff School of Mechanical Engineering Georgia Institute of Technology Atlanta GA USA Key Laboratory of Measurement and Control of Complex System of Engineering School of Automation Southeast University Nanjing China

ISBN: (数字)9798331518493

ISBN: (纸本)9798331518509

This paper introduces an adaptive robust control approach tailored for underactuated mechanical systems encountering matched and mismatched uncertainty, employing a constraint-following methodology. The control strategy unfolds in two phases: initially, a nominal control scheme is devised neglecting uncertainty and deviations in initial conditions from constraints. Subsequently, uncertainty is categorized into matched and mismatched components, ensuring that mismatched uncertainties remain unobservable. Leveraging the structural characteristics of the uncertainty bound, a novel segmented adaptive law is proposed and seamlessly integrated into the adaptive robust control framework. By employing the Lyapunov minimax approach, the method ensures uniform boundedness and uniform ultimate boundedness simultaneously, thereby ensuring approximate adherence to constraints for underactuated mechanical systems facing both matched and mismatched uncertainties alongside initial condition deviations.

关键词： Robust control Uncertainty Adaptive systems Costs Automation Nonlinear dynamical systems Mechanical systems Closed loop systems Robots

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Inverse Problem Estimation of Heat Conduction using Parameters Adaptive PID Algorithm

Inverse Problem Estimation of Heat Conduction using Paramete...

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第34届中国控制与决策会议

作者： Huang Weichao Li Jiahao Liu Ding Faculty of automation and Information Engineering Xian University of Technology Shannxi Key Laboratory of Complex System Control and Intelligent Information Processing

A boundary inverse problem estimation method for heat conduction system based on a parameters adaptive PID algorithm is proposed in the *** method can solve the boundary heat flux estimation problem of onedimensional heat conduction model based on the inverse heat conduction *** reduce the error between the temperatures of the measurement points and the calculation values constantly by using feedback control of PID *** parameters of PID algorithm is optimized by Whale optimization *** is enhances the rapidity and stability of the system and solves the problem that PID parameters are difficult to *** experimental results show that,the method that proposed in the paper can realize the inverse estimation of thermal boundary conditions accurately and quickly while ensuring the stability and convergence of the system.

关键词： Inverse heat conduction problem PID algorithm Finite difference method Whale optimization algorithm

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Time series generator adversarial network with stochastic process for the degradation generation and prediction

Time series generator adversarial network with stochastic pr...

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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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