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第三十九届中国控制会议

作者： Shuqin He Xiaofeng Zong School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

This paper presents a sampled-data frequency consensus control of microgrid with additive noise based on multiagent system. The distributed generations in microgrid are regarded as the agents and form the multiagent communication network. For a continuous-time multiagent system, due to the low efficiency and high cost, we apply the sampled-data approach to analyze the frequency consensus under additive noise. Here, based on primary droop control of microgrid, Alternating Direction Multiplier Method is applied to get the optimal frequency reference set points, and the frequency consensus based on leader-following multiagent system is obtained by the mean square consensus theory. The efficiency of the proposed method for control of the multiagent-based microgrid system under the additive noise is simulated in MATLAB.

关键词： multiagent system microgrid distributed control noise sampled-data analyze

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Positioning Method of Insulator Sheds Based on Depth Information

Positioning Method of Insulator Sheds Based on Depth Informa...

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第三十九届中国控制会议

作者： Xuan Gong Xin Chen Xu Jian Wenpeng He School of Automation China University of Geoscience Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

The identification and positioning of insulator shed feature is of vital significance for insulator cleaning. However,there exist few texture features the insulator and its surface is reflective, which makes it difficult to identify and locate the convex points on the surface of the insulator shed. In order to identify and locate the insulator shed, we propose a method to extract the convex points of the insulator skirt based on the binary image of the insulator and the position of the central axis. Binocular vision technology is applied to obtain the depth change curve of the insulator on its axis, with the help of the depth threshold method and principal component analysis（PCA） method. At the same time, the pixel coordinates on the central axis are used to traverse the depth on the central axis to extract the shed bumps, thereby achieving the spatial positioning of the insulator shed bumps. The experiments show that the bumps on the insulator’s central axis can be well marked and used in the insulator cleaning robot system.

关键词： Insulator cleaning Binocular vision Principal component analysis Shed bump Cleaning robot system

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Identification of drilling stick-slip vibration conditions based on Empirical Mode Decomposition threshold denoising and Support Vector Machine

Identification of drilling stick-slip vibration conditions b...

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第三十九届中国控制会议

作者： Ke Zhang Weihua Cao Chao Gan Wenkai Hu School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

The characteristics of the normal and stick-slip vibration signals reflect the drilling conditions, which is significant in recognizing them. In this paper, a new method that combines the Empirical Mode Decomposition(EMD) threshold denoising and Support Vector Machine(SVM) is proposed to classify these characteristics. First, the EMD threshold denoising method is introduced to denoise the raw signals of the drill string vibration. Second, the features of these characteristics are selected by the Intrinsic Mode Function(IMF) energy entropy and marginal spectral energy. Last, the drilling conditions are classified and identified by the Support Vector Machine(SVM). The simulation results show that the identification accuracy of the proposed method is higher than the conventional methods.

关键词： Stick-slip Empirical Mode Decomposition Threshold denoising Intrinsic Mode Function energy entropy Marginal spectral energy Support Vector Machine

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Effective Throughput Optimization of SAG Milling Process Based on BPNN and Genetic Algorithm

Effective Throughput Optimization of SAG Milling Process Bas...

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Industrial Cyber-Physical Systems (ICPS)

作者： Zhenhong Liao Ce Xu Wen Chen Qifu Chen Feng Wang Jinhua She School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China Department of Mineral Resources Development and Utilization Changsha Research Institute of Mining and Metallurgy CO. LTD. Chagnsha China Hunan Valin Lianyuan Iron And Steel Co. Ltd. Loudi China School of Engineering Tokyo University of Technology Hachioji Tokyo Japan

Grinding is an energy-consuming process in mineral processing industry. Improving grinding processing capacity per unit power consumption is an effective means to reduce grinding production cost. In this paper, a new index for evaluating the effective processing throughput of SAG milling is proposed. The production process model is established by BP neural network (BPNN). Through combining the process mechanism and production constraints, the genetic algorithm is adopted to optimize the operating parameters of the SAG milling process to maximize the effective throughput, thus improving the grinding efficiency. The experimental results showed that through optimization of effective throughput function proposed in this paper, the SAG mill processing capacity has been increased by 4% and the operating power drawn reduced by 1.12%. It has important guiding significance for the actual production process.

关键词： Industries Power demand Neural networks Milling Throughput Minerals Materials processing

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High Precision Waveform Reproduction of Shaking Table Based on Linear Active Disturbance Rejection control

High Precision Waveform Reproduction of Shaking Table Based ...

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第三十九届中国控制会议

作者： Wang Sheng Lei Qi School of Automation Central South University Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

Seismic simulation shaking table plays a key role in many industrial structural dynamic ***-precision waveform repetition has a great impact on the experimental accuracy of structural dynamic *** equipment of seismic simulation shaker table has obvious uncertainties in the modeling process,so it is difficult to describe the seismic simulation shaker table with a more accurate mathematical ***,this paper adopt the Linear Active Disturbance Rejection control（LADRC） to achieve high-precision reproduction of the waveform of the seismic simulation *** method will all the model uncertainty and external disturbance as total disturbance,using the extended state observer（ESO） to estimate the total disturbance,and by using state feedback control law of generalized disturbance compensation,to get better performance of resistance to *** method does not rely on the model of the specimen and does not need to obtain prior knowledge of the *** this paper,the inertial and single-degree-of-freedom elastic specimens are simulated for vibration test,and the control effect of this strategy is fully verified by comparison with the traditional PID control method.

关键词： LADRC ESO seismic simulation shaking table

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Global Automatic Recognition and Localization of Multi Screws Based on Image Mosaic

Global Automatic Recognition and Localization of Multi Screw...

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第三十九届中国控制会议

作者： Hang Yin Yan Yuan Chaolong Yao Xiaoqi Wang School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

In the tuning system based on vision sensor, the object recognition and localization is very important. In order to meet the practical tuning of the microwave cavity filter by the mechanical arm, a global recognition and localization method of multiple adjustable screws is proposed, which combines image mosaic and template matching. A high-definition global image of microwave cavity filter is composed of multiple local images according to feature point registration, and then all adjustable screws in the global image are recognized by template matching algorithm based on shape feature, which solves the problem of limited field of vision of a single industrial camera. It realizes the recognition, localization and numbering of all tuning objects in the whole tuning range, and transmits the coordinate information corresponding to the number to the mechanical arm. This method can be used to tune various types of microwave cavity filters, and it has certain versatility. The experimental results show that the recognition effect of the screws is favorable when the above method is applied to the actual tuning of 12-step microwave cavity filter with the hand-eye integrated four-axis mechanical arm. And it meets the requirements of tuning accuracy.

关键词： image mosaic microwave cavity filter image localization template matching

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A New Model of Associative Memory Neural Network Based on An Improved Memristor

A New Model of Associative Memory Neural Network Based on An...

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第三十九届中国控制会议

作者： Geliang Wan Leimin Wang Huayu Zou Shan Jiang School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

In order to simulate biological associative learning, extensive studies have been conducted on associative memory networks. This paper designs a learning forgetting model with an improved forgetting memristor based on associative memory neural network and the corresponding circuit implementation is presented. The entire circuit includes a neuron module and a synapse module. The neuron module circuit has two inputs and one output. The synapse module circuit is mainly composed of resistance and memristor. In complete circuit, associative learning and the three forgetting processes together form a full functional associative memory model. Then, the new designed memory model reflects that people learn faster during secondary learning by adjusting the speed of memory. Besides, this model is able to take longer to forget during secondary forgetting,which can simulate young people's and elderly people's abilities to learn and forget. The simulation results of PSPICE show the effectiveness of the designed circuit. The memory model proposed in this article provides the possibility to better understand the memory function of human brain.

关键词： Forgetting memristor memristive neural network associative memory circuit learning forgetting model

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Outdoor 3D reconstruction method based on multi-line laser and binocular vision ⁎

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IFAC-PapersOnLine 2020年第2期53卷 9554-9559页

作者： Xu Jian Xin Chen Wenpeng He Xuan Gong School of Automation China University of Geosciences Wuhan 430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan 430074 China

Three-dimensional (3D) reconstruction of substation fittings is of great significance for live working robots. However, the key problem is that active 3D cameras cannot work in outdoor strong light environment, and the passive 3D cameras cannot extract features of weak texture targets. This paper proposes an outdoor 3D reconstruction method based on multi-line laser and binocular vision. To solve the problem that weak texture target has few features, we use multi-line laser to create artificial features. To reduce the interference of natural light on the laser in the images, the frame-difference method is proposed for natural light filtering. Then we use the gray-centroid method to position the multi-line laser accurately. Finally, the binocular vision model is used to complete 3D reconstruction of the target. The experiments show that, compared with traditional 3D reconstruction methods, our 3D reconstruction method can realize 3D reconstruction of outdoor weak texture targets effectively.

关键词： Live working robot outdoor 3D reconstruction binocular vision frame-difference method laser positioning

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Online Adaptive Critic Robust control of Discrete-Time Nonlinear Systems With Unknown Dynamics ⁎

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IFAC-PapersOnLine 2020年第2期53卷 1696-1701页

作者： Hao Fu Xin Chen Min Wu School of Automation China University of Geosciences Wuhan 430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan 430074 China

This paper concerns the optimal model reference adaptive control problem for unknown discrete-time nonlinear systems. For such problem, it is challenging to improve online learning efficiency and guaranteeing robustness to the uncertainty. To this end, we develop an online adaptive critic robust control method. In this method, a critic network and a new supervised action network are constructed to not only improve the real-time learning efficiency, but also obtain the optimal control performance. By combining the designed compensation control term, robustness is further guaranteed by compensating the uncertainty. The comparative simulation study is conducted to show the superiority of our developed method.

关键词： Approximate dynamic programming (ADP) unknown nonlinear systems neural network (NN) supervised learning model reference adaptive control (MRAC) robust control

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Fault detection for geological drilling processes using multivariate generalized Gaussian distribution and Kullback Leibler divergence ⁎

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IFAC-PapersOnLine 2020年第2期53卷 164-169页

作者： Yupeng Li Weihua Cao Wenkai Hu Chao Gan Min Wu School of Automation China University of Geosciences Wuhan 430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan 430074 China

The presence of downhole faults compromises the safety and also leads to increased maintenance costs in complex geological drilling processes. In order to achieve timely and accurate detection of downhole faults, a systematic fault detection method is proposed based on the Multivariate Generalized Gaussian Distribution (MGGD) and the Kullback Leibler Divergence (KLD). Uncorrelated components are obtained from the original drilling process signals using the principle component analysis; then, the distribution of components is estimated using the MGGD; afterwards, the KLD is calculated based on a deduced analytic formula; last, the downhole faut is detected by comparing the calculated KLD with the alarm threshold obtained from normal data. The effectiveness and practicality of the proposed method are demonstrated by application to a real drilling process.

关键词： Geological drilling processes fault detection Kullback Leibler Divergence multivariate generalized Gaussian distribution

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