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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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Adaptive control for Stochastic Nonlinear systems With Quantized States

Adaptive Control for Stochastic Nonlinear Systems With Quant...

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第三十九届中国控制会议

作者： Mingyuan Zhao Shiqi Zheng Feng Liu Xiang Chen Yuan Sun School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation fo Complex Systems School of Electrical and Electronic Engineering The University of Adelaide

In this paper, adaptive control problem is investigated for stochastic nonlinear systems with quantized states. Compared with the existing works, the considered system is more general which contains a deterministic nonlinear term and a stochastic disturbance in each channel. In order to handle the high order nonlinearities, we present a new technique which makes the partial derivative of virtual control law become a constant, this makes the adaptive control scheme of state quantization feasible. Then, a new adaptive law is proposed to deal with some completely unknown parameters, which includes an interesting third-order term of the parameters. Finally, simulation results demonstrate the efficacy of the proposed schemes.

关键词： adaptive control backstepping state quantization stochastic system

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A comprehensive evaluation method for states adjustment priority of drilling process ⁎

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IFAC-PapersOnLine 2020年第2期53卷 11956-11961页

作者： Yang Zhou Xin Chen Min Wu Weihua Cao 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

Drilling is an important means of obtaining resources. It is important to determine appropriate drilling states adjustment priority to guide operation of the drilling. However, the priority of drilling states adjustment is difficult to determine because of the influence of multiple parameters. In this paper, a priority comprehensive evaluation method is developed to solve this problem. Firstly, support vector regression (SVR) method and long short-term memory (LSTM) neural network are introduced to build rate of penetration (ROP) prediction model and mud pit volume (MPV) prediction model, respectively. Then, the comprehensive evaluation vector is obtained by fuzzy comprehensive evaluation method based on analysis of formation drillability, rock characteristic, pump pressure variation, ROP and MPV fluctuations. Finally, the drilling states adjustment priority is determined by the principle of maximum membership and comprehensive analysis method. The simulation based on actual drilling data indicates that the proposed method can determine the adjustment priority and guide the operation of the drilling process.

关键词： Drilling process adjustment priority fuzzy comprehensive evaluation

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Multimodal Information-Based Broad and Deep Learning Model for Emotion Understanding

Multimodal Information-Based Broad and Deep Learning Model f...

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第40届中国控制会议

作者： Min Li Luefeng Chen 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 Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Department of Electrical and Computer Engineering University of Alberta Tokyo Institute of Technology

Multimodal information-based broad and deep learning model（MIBDL） for emotion understanding is proposed, in which facial expression and body gesture are used to achieve emotional states recognition for emotion understanding. It aims to understand coexistence multimodal information in human-robot interaction by using different processing methods of deep network and broad network, which obtains the features of depth and width dimensions. Moreover, random mapping in the initial broad learning network could cause information loss and its shallow layer network is difficult to cope with complex tasks. To address this problem, we use principal component analysis to generate the nodes of the broad learning, and the stacked broad learning network is adapted to make it easier for the existing broad learning networks to cope with complex tasks by creating deep variations of the existing network. To verify the effectiveness of the proposal, experiments completed on benchmark database of spontaneous emotion expressions are developed, and experimental results show that the proposal outperforms the state-of-theart methods. According to the simulation experiments on the FABO database, by using the proposed method, the multimodal recognition rate is 17,54%, 1.24%, and 0.23% higher than those of the temporal normalized motion and appearance features（TN）,the multi-channel CNN（MCCNN）, and the hierarchical classification fusion strategy（HCFS）, respectively.

关键词： Convolution neural network broad learning emotion understanding facial expression body gesture

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Adaptive Backstepping Sliding Mode control for Fractional Order systems

Adaptive Backstepping Sliding Mode Control for Fractional Or...

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第三十九届中国控制会议

作者： Xiang Chen Shiqi Zheng Feng Liu Xiongliang Zhang Yuan Sun School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation fo Complex Systems School of Electrical and Electronic Engineering The University of Adelaide

This paper concentrates on the control problem of a class of fractional order nonlinear systems. A new adaptive backstepping sliding mode control is proposed, which inherits both the advantages of backstepping and sliding mode ***, a fractional order sliding mode disturbance observer is proposed to estimate unknown external disturbances. Meanwhile, RBF neural network is adopted to approximate unknown nonlinear terms. Finally, an illustrative simulation result based on a practical fractional order permanent magnet synchronous motor model is presented to verify the validity of proposed controller.

关键词： Fractional order systems adaptive sliding mode control disturbance observer backstepping

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Nearest-Better Network for Fitness Landscape Analysis of Continuous Optimization Problems

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IEEE Transactions on Evolutionary Computation 2024年

作者： Diao, Yiya Li, Changhe Zeng, Sanyou Yang, Shengxiang Coello, Carlos A. Coello China University of Geosciences School of Automation Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Ministry of Education Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan China Anhui University of Sciences and Technology School of Artificial Intelligence Hefei China China University of Geosciences School of Mechanical Engineering and Electronic Information Wuhan China De Montfort University School of Computer Science and Informatics LeicesterLE1 9BH United Kingdom Department of Computer Science CINVESTAV-IPN 07360 Mexico Tecnologico de Monterrey Faculty of Excellence The School of Engineering and Sciences N.L. Monterrey Mexico

Fitness landscape analysis (FLA) is quite important in evolutionary computation. In this paper, we propose a novel FLA method, the nearest-better network (NBN), which uses the nearest-better relationship to simplify the original fitness landscape of continuous optimization problems. We introduce an efficient algorithm to calculate NBN for continuous problems. We also propose four numerical measurements and a 3D visualization method based on NBN. Experiments show that compared to the other main FLA methods, the four numerical measurements proposed here can effectively measure the four intended features: neutrality, ruggedness, modality, and basin of attraction, respectively, and common features of the fitness landscape can be maintained in 3D NBN visualization, regardless of the scale of the problem. NBN also provides a view of how algorithms search in high-dimensional problems with the help of the 3D NBN visualization. © 1997-2012 IEEE.

关键词： Optimization algorithms

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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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A dulcimer keys positioning method based on improved Roberts operator

A dulcimer keys positioning method based on improved Roberts...

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Chinese automation Congress (CAC)

作者： De Tang Ziying Zhang Xin Chen Zhe Xiao Mengxi Qin School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Ministry of Education Engineering Research Center of Intelligent Technology for Geo-Exploration School of Arts and Communication China University of Geosciences Wuhan China

ISBN: (纸本)9781665426480

It is important for the dulcimer robot to obtain the spatial coordinates of the dulcimer phonemes. However, the traditional manual positioning method is both inefficient and does not meet the intelligence requirements of modern robot. A visual positioning method based on improved Roberts operator is proposed in this paper on account of solving these problems, which can obtain the 3D coordinates of the dulcimer keys in a short time. First, an improved Roberts edge detection operator is designed, which fully detects the edge information of the target by transforming the scale. Further, this paper proposes a dulcimer keys positioning method by fusing RGB and depth image information. This method has a better positioning effect for dulcimer keys with complex background and small size. The experimental results show that the visual positioning method proposed in this paper can effectively identify and locate the dulcimer keys, and it has better robustness to the lighting environment.

关键词： Visualization Three-dimensional displays Robot kinematics Image edge detection Measurement uncertainty Lighting Manuals

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Fast ADMM algorithm with efficient communication for distributed optimization of multi-agent systems

Fast ADMM algorithm with efficient communication for distrib...

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Chinese automation Congress (CAC)

作者： Shuang Cao Xiaowei Jiang Ming Chi Xianhe Zhang School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation of Complex Systems Engineering Research Center of Intelligent Geodetection Technology Ministry of Education Wuhan China School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China School of Electrical Engineering and Automation Hubei Normal University Huangshi China

ISBN: (纸本)9781665426480

This paper proposes a distributed optimization algorithm based on alternating direction method of multipliers (ADMM) for the distributed optimization problem of multi-agent systems, called ADMM with adaptive penalty terms and conditional communication (for short, AAPCC), by using the local information of agents to update the adaptive penalty terms to speed up the convergence speed while by restricting the communication conditions of agents to reduce the communication cost of agents in the iterative process. Thus, the communication cost of the system is reduced while the convergence speed is ensured. Numerical simulation experiments show that in a multi-agent system, compared with the classical ADMM, AAPCC can better balance the convergence speed and communication cost, suitable for multi-agent systems that require fast convergence speed and less communication cost.

关键词： Costs automation Numerical simulation Convex functions Stability analysis Iterative algorithms Optimization

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Fixed-Time Synchronization of Fifth-Order Memristor Chaotic systems

Fixed-Time Synchronization of Fifth-Order Memristor Chaotic ...

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Chinese automation Congress (CAC)

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

ISBN: (数字)9781728176871

ISBN: (纸本)9781728176888

Based on the classical Chua's circuit, a chaotic circuit is constructed including double magnetron memristors. To study the fixed-time synchronization problem about the fifth-order memristor chaotic systems, a sliding-mode surface is proposed firstly. Then, a suitable controller is devised by using the sliding-mode control method. The sliding-mode surface is reached, then the stability on the surface also can be achieved within a fixed time thereafter. Moreover, the settling time for system synchronization is estimated, and numerical simulations confirm the correctness of the theory.

关键词： Synchronization Chaotic communication Memristors automation Sliding mode control Magnetic circuits Convergence

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