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A blast furnace fault monitoring algorithm with low false alarm rate:Ensemble of greedy dynamic principal component analysis-Gaussian mixture model

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Chinese Journal of Chemical Engineering 2023年第5期57卷 151-161页

作者： Xiongzhuo Zhu Dali Gao Chong Yang Chunjie Yang State Key Laboratory of Industrial Control Technology College of Control Science and EngineeringZhejiang UniversityHangzhou 310027China

The large blast furnace is essential equipment in the process of iron and steel manufacturing. Due to the complex operation process and frequent fluctuations of variables, conventional monitoring methods often bring false alarms. To address the above problem, an ensemble of greedy dynamic principal component analysis-Gaussian mixture model(EGDPCA-GMM) is proposed in this paper. First, PCA-GMM is introduced to deal with the collinearity and the non-Gaussian distribution of blast furnace data.Second, in order to explain the dynamics of data, the greedy algorithm is used to determine the extended variables and their corresponding time lags, so as to avoid introducing unnecessary noise. Then the bagging ensemble is adopted to cooperate with greedy extension to eliminate the randomness brought by the greedy algorithm and further reduce the false alarm rate(FAR) of monitoring results. Finally, the algorithm is applied to the blast furnace of a large iron and steel group in South China to verify performance.Compared with the basic algorithms, the proposed method achieves lowest FAR, while keeping missed alarm rate(MAR) remain stable.

关键词： Chemical processes Principal component analysis Gaussian mixture model Process monitoring Ensemble Process control

A novel motion coordination method for variable-sized multi-mobile robots

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Frontiers of Information technology & Electronic Engineering 2023年第4期24卷 521-535页

作者： Zichao XING Xingkai WANG Shuo WANG Weimin WU Ruifen HU State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and ControlZhejiang UniversityHangzhou 310027China

Multi-mobile robot systems(MMRSs)are widely used for transportation in industrial scenes such as manufacturing and warehousing.In an MMRS,motion coordination is important as collisions and deadlocks may lead to losses or system stagnation.However,in some scenarios,robot sizes are different when loaded and unloaded,which means that the robots are variable-sized,making motion coordination more difficult.The methods based on zone control need to first divide the environment into disjoint zones,and then allocate the zones statically or dynamically for motion coordination.The zone-control-based methods are not accurate enough for variable-sized multi-mobile robots and reduce the efficiency of the system.This paper describes a motion coordination method based on glued nodes,which can dynamically avoid collisions and deadlocks according to the roadmap structure and the real-time paths of robots.Dynamic features make this method directly applicable to various scenarios,instead of dividing a roadmap into disjoint zones.The proposed method has been applied to many industrial projects,and this study is based on some manufacturing projects for experiments.Theoretical analysis and experimental results show that the proposed algorithm is effective and efficient.

关键词： Multi-mobile robot system Collision avoidance Deadlock avoidance Glued nodes Motion coordination

Spherical robot: A novel robot for exploration in harsh unknown environments

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IET Cyber-Systems and Robotics 2023年第4期5卷 1-15页

作者： Wei Ren You Wang Haoxiang Liu Song Jin Yixu Wang Yifan Liu Ziang Zhang Tao Hu Guang Li State Key Laboratory of Industrial Control Technology Institute of Cyber Systems and ControlZhejiang UniversityHangzhouChina

The authors propose a complete software and hardware framework for a novel spherical robot to cope with exploration in harsh and unknown environments.The proposed robot is driven by a heavy pendulum covered by a fully enclosed spherical shell,which is strongly protected,amphibious,anti-overturn and has a long-battery-life.Algorithms for location and perception,planning and motion control are comprehensively designed.On the one hand,the authors fully consider the kinematic model of a spherical robot,propose a positioning algorithm that fuses data from inertial measurement units,motor encoder and Global Navigation Satellite System,improve global path planning algorithm based on Hybrid A*and design an instruction planning controller based on model predictive control(MPC).On the other hand,the dynamic model is built,linear MPC and robust servo linear quadratic regulator algorithm is improved,and a speed controller and a direction controller are designed.In addition,based on the pose and motion charac-teristics of a spherical robot,a visual obstacle perception algorithm and an electronic image stabilisation algorithm are designed.Finally,the authors build physical systems to verify the effectiveness of the above algorithms through experiments.

关键词： mobile robots robot control robot perception robot planning

基于暗通道先验的单幅图像快速去雾算法（英文）

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Frontiers of Information technology & Electronic Engineering 2019年第8期20卷 1109-1119页

作者： Bo-xuan YUE Kang-ling LIU Zi-yang WANG Jun LIANG State Key Laboratory of Industrial Control Technology Zhejiang University

在雾气中,可见光的散射降低了图像可见度。目前,去雾仍是图像处理应用的一个挑战。为实现去雾,提出一种基于单个像素的去雾加速算法。不同于基于区块的方法,所提方法分别估计每个区域的变换矩阵和大气光参数,其中加速的关键在于所有参... 详细信息

在雾气中,可见光的散射降低了图像可见度。目前,去雾仍是图像处理应用的一个挑战。为实现去雾,提出一种基于单个像素的去雾加速算法。不同于基于区块的方法,所提方法分别估计每个区域的变换矩阵和大气光参数,其中加速的关键在于所有参数能在一次遍历中获得。然后,对传输映射进行双边过滤,恢复像素之间的关系。通过线性模糊模型恢复后,对恢复的图像进行调整,以提高对比度、光照强度和饱和度,尤其是补偿由相应波长引起的不同通道的光强误差。实验结果表明,该方法在处理速率方面优于已有的最先进去雾算法。与其他去雾方法比较和引入定量准则(峰信噪比、可检测边际速率、信息熵差)验证该方法有效。

关键词：去雾暗通道先验雾图像模型双边滤波

Multi-objective optimization for 10-kW rated power dynamic wireless charging systems of electric vehicles

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Science China(Information Sciences) 2022年第10期65卷 178-195页

作者： Ze ZHOU Zhitao LIU Hongye SU Liyan ZHANG State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University School of Automation Wuhan University of Technology

In this paper, we propose a method to optimize the output power, efficiency, and cost of the dynamic wireless charging(DWC) system of electric vehicles by using the transmitting coil spacing as the decision variable. In a set of transmitting equipment, we adopt a structure with two transmitting networks in parallel and derive loss models. The expressions of the output power and efficiency of the DWC system are obtained by data fitting. In addition, combined with the proposed cost function, we construct a multiobjective optimization problem on output power, efficiency, and cost. Due to the complexity of the objective function, it is difficult to solve the problem by the analytic method, and thus we propose a constrained adaptive particle swarm optimization(CAPSO) algorithm with high accuracy to solve the problem. Finally,the simulation results verify the feasibility of the proposed model. The advantages of the proposed CAPSO algorithm and the optimization results under different weight combinations are presented.

关键词： dynamic wireless charging electric vehicles multi-objective optimization constrained adaptive particle swarm optimization

Identification of important factors influencing nonlinear counting systems

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Frontiers of Information technology & Electronic Engineering 2022年第1期23卷 123-133页

作者： Xinmin ZHANG Jingbo WANG Chihang WEI Zhihuan SONG State Key Laboratory of Industrial Control Technology College of Control Science and EngineeringZhejiang UniversityHangzhou310027China

Identifying factors that exert more influence on system output from data is one of the most challenging tasks in science and engineering.In this work,a sensitivity analysis of the generalized Gaussian process regression(SA-GGPR)model is proposed to identify important factors of the nonlinear counting system.In SA-GGPR,the GGPR model with Poisson likelihood is adopted to describe the nonlinear counting system.The GGPR model with Poisson likelihood inherits the merits of nonparametric kernel learning and Poisson distribution,and can handle complex nonlinear counting systems.Nevertheless,understanding the relationships between model inputs and output in the GGPR model with Poisson likelihood is not readily accessible due to its nonparametric and kernel structure.SA-GGPR addresses this issue by providing a quantitative assessment of how different inputs affect the system output.The application results on a simulated nonlinear counting system and a real steel casting-rolling process have demonstrated that the proposed SA-GGPR method outperforms several state-of-the-art methods in identification accuracy.

关键词： Important factors Nonlinear counting system Generalized Gaussian process regression Sensitivity analysis Steel casting-rolling process

A minimal thrust vectoring rotor with six degree of freedom:Design and analysis

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IET Cyber-Systems and Robotics 2021年第1期3卷 89-102页

作者： Wei Qiu Chao Xu State Key Laboratory of Industrial Control Technology Zhejiang UniversityHangzhouChina

This article presents a minimal thrust vectoring rotor(mTVR)with 6-DoF motion ability.The mTVR is equipped with only three tiltable thrust units that deploy the coaxial counter-propellers design for generating pure thrusts.Thus,the mTVR is able to perform 6-DoF flight with decoupled translation and rotation based on the full rank Jacobian matrix.The geometry of the mTVR is optimised first,by studying the condition number of the Jacobian matrix that contains five geometry parameters.The overall system is then carefully modelled based on the actual hardware configuration of the mTVR prototype,including the coaxial counter-propeller thruster,the high-voltage servo for tilting,and the detailed multi-rigid body motion dynamics of the vehicle.Next,the output envelop and dynamic response of the 6-DoF actuator performance are evaluated.A 6-DoF motion controller with disturbance rejection is designed and tested on a specialised multifunctional software platform developed for the mTVR.The controller shows good stability in regular,even aggressive operation of the vehicle.

关键词： hardware thrust equipped

Augmented industrial Data-Driven Modeling Under the Curse of Dimensionality

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IEEE/CAA Journal of Automatica Sinica 2023年第6期10卷 1445-1461页

作者： Xiaoyu Jiang Xiangyin Kong Zhiqiang Ge the State Key Laboratory of Industrial Control Technology College of Control Science and EngineeringZhejiang UniversityHangzhou 310027China the Peng Cheng laboratory Shenzhen 518000China

The curse of dimensionality refers to the problem o increased sparsity and computational complexity when dealing with high-dimensional data.In recent years,the types and vari ables of industrial data have increased significantly,making data driven models more challenging to develop.To address this prob lem,data augmentation technology has been introduced as an effective tool to solve the sparsity problem of high-dimensiona industrial data.This paper systematically explores and discusses the necessity,feasibility,and effectiveness of augmented indus trial data-driven modeling in the context of the curse of dimen sionality and virtual big data.Then,the process of data augmen tation modeling is analyzed,and the concept of data boosting augmentation is proposed.The data boosting augmentation involves designing the reliability weight and actual-virtual weigh functions,and developing a double weighted partial least squares model to optimize the three stages of data generation,data fusion and modeling.This approach significantly improves the inter pretability,effectiveness,and practicality of data augmentation in the industrial modeling.Finally,the proposed method is verified using practical examples of fault diagnosis systems and virtua measurement systems in the industry.The results demonstrate the effectiveness of the proposed approach in improving the accu racy and robustness of data-driven models,making them more suitable for real-world industrial applications.

关键词： Index Terms—Curse of dimensionality data augmentation data-driven modeling industrial processes machine learning

Command filter-based I&I adaptive control for MIMO uncertain systems with input saturation and disturbances

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Science China(Information Sciences) 2023年第12期66卷 64-79页

作者： Qi HAN Zhitao LIU Hongye SU Xiangbin LIU State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and ControlZhejiang University School of Electronic Information Engineering Beijing Jiaotong University

This paper develops a control strategy based on immersion and invariance(I&I) adaptive methodology for a class of multi-input multi-output(MIMO) systems in the presence of parametric uncertainty, input saturation, and external disturbance. To avoid the analytic calculation in the backstepping process, a highgain auxiliary system is constructed to compensate for the effect of command filter error. The first-order command filters are also employed in the construction procedure of the I&I adaptive law to simplify its design and remove the structural conditions on the regressors. A filter-based disturbance observer is developed to counteract the effect of the external disturbance produced by a partially known exogenous system.To overcome the input saturation nonlinearity, a smooth function is introduced to approximate the input saturation with an extended state and a bounding estimation law. Stringent analysis guarantees the stability of closed-loop system. Finally, simulated examples confirm the effectiveness of the suggested method.

关键词： adaptive control command filtered backstepping disturbance observer immersion and invariance MIMO systems