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Min Wu
China University of Geosciences, China

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Journal article
Published: 25 August 2021 in IEEE Transactions on Industrial Electronics
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Synchronization control is an essential technique in networked multi-axis motion systems (NMAMSs). However, the compound disturbances caused by the delay-induced uncertainty and external disturbances such as system coupling and load mutation have great influence on performance of the motion control systems. The purpose of this paper is to propose an equivalent-input-disturbance (EID) Based position synchronization control strategy for NMAMSs to solve the influence of compound disturbances on synchronization control performance in NMAMSs. First, a position synchronization error model is established for the NMAMSs, and the delay-induced uncertainty is treated as a network disturbance (ND). Next, the EID is designed to suppress the overall effect. Then, an EID-based synchronization controller is designed to achieve both position synchronization and disturbance rejection. The effect of the compound disturbances in the synchronization performance is significantly reduced. Finally, simulations and experiments on a position synchronization control platform of a four-motor system are presented to demonstrate the effectiveness and superiority of the proposed method.

ACS Style

Yao-Wei Wang; Xiang Wu; Wen-An Zhang; Min Wu. Equivalent-Input-Disturbance Based Position Synchronization Control of Networked Multi-axis Motion System. IEEE Transactions on Industrial Electronics 2021, PP, 1 -1.

AMA Style

Yao-Wei Wang, Xiang Wu, Wen-An Zhang, Min Wu. Equivalent-Input-Disturbance Based Position Synchronization Control of Networked Multi-axis Motion System. IEEE Transactions on Industrial Electronics. 2021; PP (99):1-1.

Chicago/Turabian Style

Yao-Wei Wang; Xiang Wu; Wen-An Zhang; Min Wu. 2021. "Equivalent-Input-Disturbance Based Position Synchronization Control of Networked Multi-axis Motion System." IEEE Transactions on Industrial Electronics PP, no. 99: 1-1.

Article
Published: 27 July 2021 in International Journal of Control, Automation and Systems
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Unlike a fully-actuated manipulator, the position-posture control of a planar underactuated manipulator (PUM) is more difficult, but the research on it is significant due to the wide practical applications. The existing control methods consider no external disturbance and are involved in the staged control idea, bringing the problems of nonsmooth control torque and time-consuming. A novel one-stage control approach is proposed in this paper for the position-posture control of a three-link PUM with the first free joint under the external disturbance. By analyzing the coupling relationship between its active joints and free joint, the position-posture control is transformed into the trajectory tracking control. Unlike the general trajectory planning, the trajectories of the active joints are planned to include several parameters. Meanwhile, the parameters are solved using a chaos particle swarm optimization algorithm to guarantee that all joint angles can reach to their desired angles. Then, to obtain the high trajectory tracking accuracy at every moment under the external disturbance, the nonlinear disturbance observer is constructed and a nonlinear fast terminal sliding mode tracking controller is designed. Finally, the feasibility and superiority of this strategy are verified via two simulations.

ACS Style

Pan Zhang; Xuzhi Lai; Yawu Wang; Min Wu. Chaos-PSO-based Motion Planning and Accurate Tracking for Position-posture Control of a Planar Underactuated Manipulator with Disturbance. International Journal of Control, Automation and Systems 2021, 1 -11.

AMA Style

Pan Zhang, Xuzhi Lai, Yawu Wang, Min Wu. Chaos-PSO-based Motion Planning and Accurate Tracking for Position-posture Control of a Planar Underactuated Manipulator with Disturbance. International Journal of Control, Automation and Systems. 2021; ():1-11.

Chicago/Turabian Style

Pan Zhang; Xuzhi Lai; Yawu Wang; Min Wu. 2021. "Chaos-PSO-based Motion Planning and Accurate Tracking for Position-posture Control of a Planar Underactuated Manipulator with Disturbance." International Journal of Control, Automation and Systems , no. : 1-11.

Journal article
Published: 19 July 2021 in IEEE Transactions on Neural Networks and Learning Systems
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This article is concerned with passivity analysis of neural networks with a time-varying delay. Several techniques in the domain are improved to establish the new passivity criterion with less conservatism. First, a Lyapunov-Krasovskii functional (LKF) is constructed with two general delay-product-type terms which contain any chosen degree of polynomials in time-varying delay. Second, a general convexity lemma without conservatism is developed to address the positive-definiteness of the LKF and the negative-definiteness of its time-derivative. Then, with these improved results, a hierarchical passivity criterion of less conservatism is obtained for neural networks with a time-varying delay, whose size and conservatism vary with the maximal degree of the time-varying delay polynomial in the LKF. It is shown that the conservatism of the passivity criterion does not always reduce as the degree of the time-varying delay polynomial increases. Finally, a numerical example is given to illustrate the proposed criterion and benchmark against the existing results.

ACS Style

Fei Long; Chuan-Ke Zhang; Yong He; Qing-Guo Wang; Zhen-Man Gao; Min Wu. Hierarchical Passivity Criterion for Delayed Neural Networks via A General Delay-Product-Type Lyapunov-Krasovskii Functional. IEEE Transactions on Neural Networks and Learning Systems 2021, PP, 1 -12.

AMA Style

Fei Long, Chuan-Ke Zhang, Yong He, Qing-Guo Wang, Zhen-Man Gao, Min Wu. Hierarchical Passivity Criterion for Delayed Neural Networks via A General Delay-Product-Type Lyapunov-Krasovskii Functional. IEEE Transactions on Neural Networks and Learning Systems. 2021; PP (99):1-12.

Chicago/Turabian Style

Fei Long; Chuan-Ke Zhang; Yong He; Qing-Guo Wang; Zhen-Man Gao; Min Wu. 2021. "Hierarchical Passivity Criterion for Delayed Neural Networks via A General Delay-Product-Type Lyapunov-Krasovskii Functional." IEEE Transactions on Neural Networks and Learning Systems PP, no. 99: 1-12.

Journal article
Published: 02 July 2021 in Journal of the Franklin Institute
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In this paper, a robust mixed-sensitivity H∞ controller is designed to control surface weight on bit using surface measurement feedback. First, we construct a drill-string longitudinal model with uncertain penetration resistance coefficient based on finite element method, and a reduced-order model is derived for controller synthesis. In order to solve the fixed point tracking problem of weight on bit control with parameter uncertainty, the mixed-sensitivity H∞ control strategy is developed to design on the model with uncertain parameter. The boundary of the uncertain parameter is obtained using field data. A quadratic stability condition of the closed-loop system is derived by using a single Lyapunov function, based on which a suitable dynamic output feedback H∞ controller is obtained. The uncertain penetration resistance coefficient and system’s high-order mode are considered in modeling and control of weight on bit for the first time. Comparison with field data is provided to validate our modeling method. Numerical results are given on a set of models with different penetration resistance coefficient. The integral of time multiplied by the squared error criterion of the closed-loop system with parameters obtained through equidistant sampling are provided. The simulation results demonstrate that the proposed controller can improve the robustness of the system’s tracking performance to parameter uncertainty and suppress the tracking oscillation results from the high-order mode.

ACS Style

Sike Ma; Min Wu; Luefeng Chen; Chengda Lu; Weihua Cao. Robust mixed-sensitivity H∞ control of weight on bit in geological drilling process with parameter uncertainty. Journal of the Franklin Institute 2021, 358, 6433 -6461.

AMA Style

Sike Ma, Min Wu, Luefeng Chen, Chengda Lu, Weihua Cao. Robust mixed-sensitivity H∞ control of weight on bit in geological drilling process with parameter uncertainty. Journal of the Franklin Institute. 2021; 358 (13):6433-6461.

Chicago/Turabian Style

Sike Ma; Min Wu; Luefeng Chen; Chengda Lu; Weihua Cao. 2021. "Robust mixed-sensitivity H∞ control of weight on bit in geological drilling process with parameter uncertainty." Journal of the Franklin Institute 358, no. 13: 6433-6461.

Journal article
Published: 22 June 2021 in Computers & Industrial Engineering
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Rate of penetration (ROP) is one of the crucial drilling condition monitoring parameters due to its vital role in real-time assessing drilling operating performance. Operators often adjust operating parameters to meet higher performance requirements. Therefore, drilling operating performance assessment is critical for controlling and optimizing of the drilling process. An operating performance assessment strategy with multiple modes based on least square support vector machines for drilling process is presented in this paper. First, the process capability index is to be taken as the indicator of the ROP and defines the drilling operating performance. Next, the K-means clustering algorithm is used to identify the operating modes. Then, for each mode, an individual drilling operating performance assessment model is established by the method of least squares support vector machines. Finally, drilling operating performance grade is obtained, and actual data of drill well are used for experiments. Further comparative analyses were performed with other state-of-the-art methods, including the Decision tree, Support vector machines (SVM), Least squares support vector machines (LS-SVM), Principal component analysis (PCA), and Partial least squares (PLS). Simulations revealed that the proposed method results in the accurate assessment of operating performance in the drilling process with the accuracy of 87%, the precision of 85.3%, the recall of 88.2%, and the F-Score of 87.6%. In particular, the assessment accuracy was improved by 18.6%, 11.3%, 5.2%, 9.68%, 8.32% in comparison to Decision Tree, SVM, LS-SVM, PCA, and PLS. Performance comparisons reflect the superiority of our model that can ensure high accuracy about operating performance in a drilling process.

ACS Style

Haipeng Fan; Min Wu; Weihua Cao; Xuzhi Lai; Luefeng Chen; Chengda Lu; Sheng Du; Jinhua She. An operating performance assessment strategy with multiple modes based on least square support vector machines for drilling process. Computers & Industrial Engineering 2021, 159, 107492 .

AMA Style

Haipeng Fan, Min Wu, Weihua Cao, Xuzhi Lai, Luefeng Chen, Chengda Lu, Sheng Du, Jinhua She. An operating performance assessment strategy with multiple modes based on least square support vector machines for drilling process. Computers & Industrial Engineering. 2021; 159 ():107492.

Chicago/Turabian Style

Haipeng Fan; Min Wu; Weihua Cao; Xuzhi Lai; Luefeng Chen; Chengda Lu; Sheng Du; Jinhua She. 2021. "An operating performance assessment strategy with multiple modes based on least square support vector machines for drilling process." Computers & Industrial Engineering 159, no. : 107492.

Research article
Published: 21 June 2021 in International Journal of Systems Science
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The design of a trajectory is significant to the efficiency and safety of a drilling process. In this paper, wellbore stability, indicated by the safe mud weight, is introduced as constraints to formulate a drilling trajectory optimisation problem. The upper and lower bounds of the safe mud weight are analysed according to the real data of a well. To solve the optimisation problem with strict constraints, we devise a new multi-objective optimisation algorithm. The devised algorithm takes advantage of inverted generational distance and knee points, and improves the convergence and diversity of the obtained solutions by modifying the selection process. Simulation results show that the devised algorithm is effective on the drilling trajectory optimisation problem constrained to wellbore stability.

ACS Style

Wendi Huang; Min Wu; Jie Hu; Luefeng Chen; Chengda Lu; Xin Chen; Weihua Cao. A multi-objective optimisation algorithm for a drilling trajectory constrained to wellbore stability. International Journal of Systems Science 2021, 1 -14.

AMA Style

Wendi Huang, Min Wu, Jie Hu, Luefeng Chen, Chengda Lu, Xin Chen, Weihua Cao. A multi-objective optimisation algorithm for a drilling trajectory constrained to wellbore stability. International Journal of Systems Science. 2021; ():1-14.

Chicago/Turabian Style

Wendi Huang; Min Wu; Jie Hu; Luefeng Chen; Chengda Lu; Xin Chen; Weihua Cao. 2021. "A multi-objective optimisation algorithm for a drilling trajectory constrained to wellbore stability." International Journal of Systems Science , no. : 1-14.

Journal article
Published: 28 April 2021 in IEEE Transactions on Cybernetics
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Sintering is the preproduction process of ironmaking, whose products are the basis of ironmaking. How to improve the operating performance of the iron ore sintering process has always been a problem that operators are committed to solve. An operating performance improvement method based on prediction and grade assessment is presented in this article. First, considering the data distribution characteristics of the process, a performance index prediction model based on the Gaussian process regression is built, in which the mutual information analysis method is used to select the inputs of the performance index prediction model. Then, the operating performance grade is assessed by a threshold division method. Next, the operating performance grade guides the control of the burn-through point to improve the operating performance. Finally, experimental verification is performed based on the actual running data. The results show that the proposed method has high prediction accuracy, and it is also significant in improving the operating performance. Therefore, this approach provides an effective solution to predict and improve operating performance.

ACS Style

Sheng Du; Min Wu; Luefeng Chen; Li Jin; Weihua Cao; Witold Pedrycz. Operating Performance Improvement Based on Prediction and Grade Assessment for Sintering Process. IEEE Transactions on Cybernetics 2021, PP, 1 -13.

AMA Style

Sheng Du, Min Wu, Luefeng Chen, Li Jin, Weihua Cao, Witold Pedrycz. Operating Performance Improvement Based on Prediction and Grade Assessment for Sintering Process. IEEE Transactions on Cybernetics. 2021; PP (99):1-13.

Chicago/Turabian Style

Sheng Du; Min Wu; Luefeng Chen; Li Jin; Weihua Cao; Witold Pedrycz. 2021. "Operating Performance Improvement Based on Prediction and Grade Assessment for Sintering Process." IEEE Transactions on Cybernetics PP, no. 99: 1-13.

Journal article
Published: 28 April 2021 in IEEE/ASME Transactions on Mechatronics
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This paper proposes a customized kernel-based Fuzzy C-Means (CKFCM) clustering, which provides an original framework for data interpretation and data analysis and delivers an effective solution for an accurate division of actual run data under multiple operating conditions in an iron ore sintering process (IOSP). The improvement of CKFCM clustering is achieved by including an adjustment factor introduced into the kernel-based Fuzzy C-Means clustering. The adjustment factor only needs to consider a small amount of labeled data that are determined based on expert experience. Subsequently, the CKFCM clustering is applied to the modeling of the IOSP, and Spearman's rank correlation coefficient method is utilized to determine input variables of the model under different operating conditions. Furthermore, the broad learning model is employed to build the prediction model for each operating condition. Finally, we conducted an in-depth analysis of the presented clustering method. Its performance has been experimentally demonstrated by many publicly available datasets. Meanwhile, simulation results involving actual run data of the IOSP demonstrate the superiority and effectiveness of the developed model in carbon efficiency prediction. We show that the developed model outperforms the state-of-the-art prediction models in achieving a good balance between simplicity and accuracy.

ACS Style

Jie Hu; Min Wu; Luefeng Chen; Witold Pedrycz. A Novel Modeling Framework Based on Customized Kernel-based Fuzzy C-Means Clustering in Iron Ore Sintering Process. IEEE/ASME Transactions on Mechatronics 2021, PP, 1 -1.

AMA Style

Jie Hu, Min Wu, Luefeng Chen, Witold Pedrycz. A Novel Modeling Framework Based on Customized Kernel-based Fuzzy C-Means Clustering in Iron Ore Sintering Process. IEEE/ASME Transactions on Mechatronics. 2021; PP (99):1-1.

Chicago/Turabian Style

Jie Hu; Min Wu; Luefeng Chen; Witold Pedrycz. 2021. "A Novel Modeling Framework Based on Customized Kernel-based Fuzzy C-Means Clustering in Iron Ore Sintering Process." IEEE/ASME Transactions on Mechatronics PP, no. 99: 1-1.

Journal article
Published: 23 April 2021 in Engineering Applications of Artificial Intelligence
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Burn-through point (BTP) is an essential parameter in the iron ore sintering process. Operators usually judge whether the current production is stable by monitoring the BTP. It comes with significant application prospects to predict the BTP accurately. A prediction model of the BTP with fuzzy time series is designed in this paper. First, the fuzzy time series prediction method with the Fuzzy C-Means clustering is presented as the core modeling method. A prediction model of the response is constructed to obtain a timely response to the current BTP. The prediction model of the difference is established to estimate the present unmeasurable disturbance on the BTP. Then, a hybrid prediction model is built, which realizes the composition of these two models by an adjustment factor. Finally, a series of experiments is carried out using the raw time series data from an iron and steel plant. The experimental result shows that the designed model has better prediction performance for the BTP than existing models, which is an advantage resulting from the hybrid structure and the fuzzy time series prediction model with the Fuzzy C-Means clustering. This prediction model of the BTP implies the foundation for the stable control of the iron ore sintering process.

ACS Style

Sheng Du; Min Wu; Luefeng Chen; Witold Pedrycz. Prediction model of burn-through point with fuzzy time series for iron ore sintering process. Engineering Applications of Artificial Intelligence 2021, 102, 104259 .

AMA Style

Sheng Du, Min Wu, Luefeng Chen, Witold Pedrycz. Prediction model of burn-through point with fuzzy time series for iron ore sintering process. Engineering Applications of Artificial Intelligence. 2021; 102 ():104259.

Chicago/Turabian Style

Sheng Du; Min Wu; Luefeng Chen; Witold Pedrycz. 2021. "Prediction model of burn-through point with fuzzy time series for iron ore sintering process." Engineering Applications of Artificial Intelligence 102, no. : 104259.

Journal article
Published: 19 April 2021 in IEEE Transactions on Control Systems Technology
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Load frequency control (LFC) of modern power systems tends to employ open communication networks to transmit measurement/control signals. Under a limited network bandwidth, the continuous and high-sampling-rate signal transmission will be prone to degradation of the LFC performance through network congestion. This brief proposes a decentralized control performance standards (CPSs)-oriented event-triggered (ET) LFC scheme for power systems under constrained communication bandwidth. The proposed scheme comprises the ET LFC scheme and the CPSs-oriented regulation scheme. In the CPSs-oriented regulation scheme, regulation rules are designed to adjust the threshold parameter of the ET LFC scheme based on the North American Electrical Reliability Council (NERC)'s CPS1 and CPS2. The rules generate a larger threshold parameter to lower the triggering frequency in order to reduce unnecessary transmission of measurement/control signals, while ensuring the frequency and tie-lie power of the power systems to meet the required CPS1 and CPS2 instead of the asymptotic stability requirement in the existing research. The reduced transmission of these signals lessens the communication burden. In addition, the decentralized control strategy is used to solve the problems of poor large scalability and computational dimension caused by the centralized control strategy. The effectiveness of the proposed scheme is evaluated on an IEEE 39-bus test system with renewable energy sources.

ACS Style

Xing-Chen Shangguan; Yong He; Chuan-Ke Zhang; Li Jin; Wei Yao; Lin Jiang; Min Wu. Control Performance Standards-Oriented Event-Triggered Load Frequency Control for Power Systems Under Limited Communication Bandwidth. IEEE Transactions on Control Systems Technology 2021, PP, 1 -9.

AMA Style

Xing-Chen Shangguan, Yong He, Chuan-Ke Zhang, Li Jin, Wei Yao, Lin Jiang, Min Wu. Control Performance Standards-Oriented Event-Triggered Load Frequency Control for Power Systems Under Limited Communication Bandwidth. IEEE Transactions on Control Systems Technology. 2021; PP (99):1-9.

Chicago/Turabian Style

Xing-Chen Shangguan; Yong He; Chuan-Ke Zhang; Li Jin; Wei Yao; Lin Jiang; Min Wu. 2021. "Control Performance Standards-Oriented Event-Triggered Load Frequency Control for Power Systems Under Limited Communication Bandwidth." IEEE Transactions on Control Systems Technology PP, no. 99: 1-9.

Journal article
Published: 19 April 2021 in Journal of Process Control
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Geological drilling process is operating under complex geological conditions, which may lead to a high risk of downhole incidents and thus compromise the drilling efficiency. To achieve prompt detection of downhole incidents and prevent them from developing to serious drilling accidents, this paper proposes a new data-driven detection method for downhole incidents based on the amplitude change detection and dynamic time warping. Two major phases are involved: the change monitoring phase detects whether there is any significant change in the drilling signals and extracts variational trend features by linear fitting and amplitude change detection; the incident detection phase determines if the cause of a change is a normal switching or a downhole incident by similarity analysis based on the dynamic time warping and the density-based spatial clustering. Industrial case studies show that the proposed method achieves good performance in downhole incidents detection for geological drilling processes.

ACS Style

Yupeng Li; Weihua Cao; Wenkai Hu; Min Wu. Detection of downhole incidents for complex geological drilling processes using amplitude change detection and dynamic time warping. Journal of Process Control 2021, 102, 44 -53.

AMA Style

Yupeng Li, Weihua Cao, Wenkai Hu, Min Wu. Detection of downhole incidents for complex geological drilling processes using amplitude change detection and dynamic time warping. Journal of Process Control. 2021; 102 ():44-53.

Chicago/Turabian Style

Yupeng Li; Weihua Cao; Wenkai Hu; Min Wu. 2021. "Detection of downhole incidents for complex geological drilling processes using amplitude change detection and dynamic time warping." Journal of Process Control 102, no. : 44-53.

Journal article
Published: 19 April 2021 in Applied Soft Computing
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This paper is concerned with the optimization problem of drilling trajectory design, which plays a vital role in ensuring the safety and enhancing the efficiency of an industrial drilling process. Due to complex geological environment and limited capacity of equipment, the problem to be addressed features multi-objective and multi-constraint, and consists of two challenges: (1) how to formulate a proper optimization scheme and efficiently solve it for a group of solutions; and (2) how to pick out a desired result from the obtained Pareto solutions according to certain requirements. In this paper, to meet drilling practice, three objective functions are introduced regarding trajectory length, well-profile energy, and target error, respectively. Constraints are the range of decision parameters, non-negative constraints and bound of the target area. As a result, a comprehensive optimization model for the design of drilling trajectory is established. A novel optimization algorithm is devised to deal with the contradictory objectives and multiple nonlinear constraints, which combines an adaptive penalty function with multi-objective evolutionary algorithm based on decomposition. A fuzzy-entropy-based evaluation approach is further employed to determine a satisfactory solution from the group of obtained ones. A case study illustrates that (1) our optimization solution is indeed beneficial to the optimization of drilling trajectory; and (2) the optimization algorithm and the decision method therein outperform some existing ones, which shows both practical and theoretical significance.

ACS Style

Wendi Huang; Min Wu; Luefeng Chen; Xin Chen; Weihua Cao. Multi-objective drilling trajectory optimization using decomposition method with minimum fuzzy entropy-based comprehensive evaluation. Applied Soft Computing 2021, 107, 107392 .

AMA Style

Wendi Huang, Min Wu, Luefeng Chen, Xin Chen, Weihua Cao. Multi-objective drilling trajectory optimization using decomposition method with minimum fuzzy entropy-based comprehensive evaluation. Applied Soft Computing. 2021; 107 ():107392.

Chicago/Turabian Style

Wendi Huang; Min Wu; Luefeng Chen; Xin Chen; Weihua Cao. 2021. "Multi-objective drilling trajectory optimization using decomposition method with minimum fuzzy entropy-based comprehensive evaluation." Applied Soft Computing 107, no. : 107392.

Journal article
Published: 18 April 2021 in Journal of Process Control
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With the increase of drilling depth, complicated geological environments lead to a high risk of loss and kick. Fault diagnosis plays an essential role in minimizing the financial and environmental losses of the drilling process. On account of the temporal correlation of drilling parameters, a fault diagnosis method based on feature clustering of time series data for loss and kick of the drilling process is presented in this paper. Distance correlation is conducted for parameter combination to retain the whole information of drilling process. Global trend, local trends, and approximate entropy features are extracted to illustrate the characteristic of the time series. Density-based clustering method is performed for each combination to mine the local similarity among drilling parameters. Based on the clustering results of each combination as the inputs, the Bayesian classifier is further utilized to obtain the final fault diagnosis result. Experiments are executed with the actual data collected from a practical drilling process. The results indicate that the proposed method has both low false alarm rate and low miss alarm rate.

ACS Style

Zheng Zhang; Xuzhi Lai; Min Wu; Luefeng Chen; Chengda Lu; Sheng Du. Fault diagnosis based on feature clustering of time series data for loss and kick of drilling process. Journal of Process Control 2021, 102, 24 -33.

AMA Style

Zheng Zhang, Xuzhi Lai, Min Wu, Luefeng Chen, Chengda Lu, Sheng Du. Fault diagnosis based on feature clustering of time series data for loss and kick of drilling process. Journal of Process Control. 2021; 102 ():24-33.

Chicago/Turabian Style

Zheng Zhang; Xuzhi Lai; Min Wu; Luefeng Chen; Chengda Lu; Sheng Du. 2021. "Fault diagnosis based on feature clustering of time series data for loss and kick of drilling process." Journal of Process Control 102, no. : 24-33.

Journal article
Published: 13 April 2021 in IEEE Transactions on Systems, Man, and Cybernetics: Systems
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The control objective of the vertical plane underactuated manipulator (VPUM) is generally to swing up the end point (EP) from the vertical down equilibrium point (VDEP) to the vertical up equilibrium point (VUEP), and finally, to stabilize it at the VUEP. The zone control methods are usually used to achieve this control objective, but the problem of these methods is that they cannot find a unified zone range, and it is easy to appear singularity in the motion process. In this article, for two-link VPUMs, we propose a control strategy based on trajectory planning and optimization, which does not need to divide the zone range, avoids the singularity problem, and can achieve the control objective quickly and smoothly. We design the trajectory by using the time scale method for the active link according to the initial and target states. Then, we obtain the trajectory parameters by employing differential evolution algorithm to ensure that the passive link can also move from the initial states to the target states simultaneously. We design a sliding mode tracking controller to make the active link move along the designed trajectory, so the EP is moved to VUEP. Meantime, we design a sliding mode stabilization controller to ensure that the system is stable at VUEP. Finally, the universality and robustness of the proposed method are proved by simulations.

ACS Style

Lejun Wang; Xuzhi Lai; Pan Zhang; Min Wu. A Control Strategy Based on Trajectory Planning and Optimization for Two-Link Underactuated Manipulators in Vertical Plane. IEEE Transactions on Systems, Man, and Cybernetics: Systems 2021, PP, 1 -10.

AMA Style

Lejun Wang, Xuzhi Lai, Pan Zhang, Min Wu. A Control Strategy Based on Trajectory Planning and Optimization for Two-Link Underactuated Manipulators in Vertical Plane. IEEE Transactions on Systems, Man, and Cybernetics: Systems. 2021; PP (99):1-10.

Chicago/Turabian Style

Lejun Wang; Xuzhi Lai; Pan Zhang; Min Wu. 2021. "A Control Strategy Based on Trajectory Planning and Optimization for Two-Link Underactuated Manipulators in Vertical Plane." IEEE Transactions on Systems, Man, and Cybernetics: Systems PP, no. 99: 1-10.

Chapter
Published: 27 March 2021 in Developments in Advanced Control and Intelligent Automation for Complex Systems
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The sintering process produces sinters as blast furnace materials. The quality of the sinter and the stability of the sintering process are related to the efficiency, energy consumption, and cost of the blast furnace production. The sintering thermal state parameters directly affect the quality of the sinter and the stability of the sintering process. The stability of the sintering process is based on the stable control of sintering thermal parameters. This chapter introduces the sintering process characteristics, presents a carbon efficiency optimization scheme, and describes the intelligent control of burn-through point and sintering ignition temperature.

ACS Style

Min Wu; Sheng Du; Jie Hu; Xin Chen; Weihua Cao; Witold Pedrycz. Intelligent Control of Sintering Process. Developments in Advanced Control and Intelligent Automation for Complex Systems 2021, 101 -141.

AMA Style

Min Wu, Sheng Du, Jie Hu, Xin Chen, Weihua Cao, Witold Pedrycz. Intelligent Control of Sintering Process. Developments in Advanced Control and Intelligent Automation for Complex Systems. 2021; ():101-141.

Chicago/Turabian Style

Min Wu; Sheng Du; Jie Hu; Xin Chen; Weihua Cao; Witold Pedrycz. 2021. "Intelligent Control of Sintering Process." Developments in Advanced Control and Intelligent Automation for Complex Systems , no. : 101-141.

Chapter
Published: 27 March 2021 in Developments in Advanced Control and Intelligent Automation for Complex Systems
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Wind power forecasting improves the wind power trade and the wind power dispatch level. Wind speed is closely related to the accuracy of wind energy forecasting. This chapter introduces the process of wind power generation, describes an amplitude-frequency characteristic extraction method for the wind speed, and presents a hybrid-kernel least-squares support vector machine based wind power forecasting method.

ACS Style

Min Ding; Min Wu; Ryuichi Yokoyama; Yosuke Nakanishi; Yicheng Zhou. A Short-Term Wind Power Forecasting Method Based on Hybrid-Kernel Least-Squares Support Vector Machine. Developments in Advanced Control and Intelligent Automation for Complex Systems 2021, 395 -411.

AMA Style

Min Ding, Min Wu, Ryuichi Yokoyama, Yosuke Nakanishi, Yicheng Zhou. A Short-Term Wind Power Forecasting Method Based on Hybrid-Kernel Least-Squares Support Vector Machine. Developments in Advanced Control and Intelligent Automation for Complex Systems. 2021; ():395-411.

Chicago/Turabian Style

Min Ding; Min Wu; Ryuichi Yokoyama; Yosuke Nakanishi; Yicheng Zhou. 2021. "A Short-Term Wind Power Forecasting Method Based on Hybrid-Kernel Least-Squares Support Vector Machine." Developments in Advanced Control and Intelligent Automation for Complex Systems , no. : 395-411.

Journal article
Published: 23 March 2021 in IEEE Transactions on Industrial Electronics
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The heating furnace is a sizeable energy-consuming device in iron and steel industry. In compact strip production (CSP), the size of the heating furnace is large and the working conditions are complicated. Furthermore, the large fluctuation of furnace temperature leads to large loss of billet combustion and energy consumption. This paper deals with the design of hybrid intelligent control based on condition identification for the combustion process of the CSP heating furnace. By analyzing the process of the heating furnace and existing problems, the structure of a hybrid intelligent control system is proposed, and the working conditions are divided into two categories: stable and fluctuating. A fuzzy controller is designed to improve the control accuracy of furnace temperature under the stable working condition, and an expert controller is used to adjust the temperature rapidly under the fluctuating working condition. Besides, calorific value compensation is introduced to reduce the influence of calorific value of gas fluctuation on temperature. After verifying the effectiveness, the proposed method has been used in a steel plant and achieved a good control result. The intelligent control system improves the control precision of the furnace temperature and reduces energy consumption compared with the traditional control system.

ACS Style

Ying Feng; Min Wu; Luefeng Chen; Xin Chen; Weihua Cao; Sheng Du; Witold Pedrycz. Hybrid Intelligent Control Based on Condition Identification for Combustion Process in Heating Furnace of Compact Strip Production. IEEE Transactions on Industrial Electronics 2021, PP, 1 -1.

AMA Style

Ying Feng, Min Wu, Luefeng Chen, Xin Chen, Weihua Cao, Sheng Du, Witold Pedrycz. Hybrid Intelligent Control Based on Condition Identification for Combustion Process in Heating Furnace of Compact Strip Production. IEEE Transactions on Industrial Electronics. 2021; PP (99):1-1.

Chicago/Turabian Style

Ying Feng; Min Wu; Luefeng Chen; Xin Chen; Weihua Cao; Sheng Du; Witold Pedrycz. 2021. "Hybrid Intelligent Control Based on Condition Identification for Combustion Process in Heating Furnace of Compact Strip Production." IEEE Transactions on Industrial Electronics PP, no. 99: 1-1.

Journal article
Published: 18 March 2021 in Journal of Process Control
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The accurate prediction of rate of penetration (ROP) has a crucial role in improving efficiency and minimizing cost in geological drilling process. Considering the drilling characteristics of strong nonlinearity, complexity, multiple variables and drilling conditions in drilling process, an online hybrid prediction model based on the drilling data is developed to achieve high accuracy prediction of the ROP. First, mutual information analysis is used to determine the appropriate model inputs. Then,k-nearest neighbor algorithm and dynamic time warping (KNN–DTW) are combined to identify drilling condition. After that, ROP prediction model is established by support vector regression (SVR) method. The hyperparameters of SVR method are obtained by hybrid bat algorithm (HBA) and nondominated sorting genetic algorithm II (NSGA-II) based on the identified drilling condition. Finally, a modified sliding window method is developed to update the prediction model to deal with complex and variable drilling process. The simulation results show that our method has higher accuracy than other methods, and our method can identify the drilling condition and provide guidance for the drilling operation.

ACS Style

Yang Zhou; Xin Chen; Haibin Zhao; Min Wu; Weihua Cao; Yongchun Zhang; Haibo Liu. A novel rate of penetration prediction model with identified condition for the complex geological drilling process. Journal of Process Control 2021, 100, 30 -40.

AMA Style

Yang Zhou, Xin Chen, Haibin Zhao, Min Wu, Weihua Cao, Yongchun Zhang, Haibo Liu. A novel rate of penetration prediction model with identified condition for the complex geological drilling process. Journal of Process Control. 2021; 100 ():30-40.

Chicago/Turabian Style

Yang Zhou; Xin Chen; Haibin Zhao; Min Wu; Weihua Cao; Yongchun Zhang; Haibo Liu. 2021. "A novel rate of penetration prediction model with identified condition for the complex geological drilling process." Journal of Process Control 100, no. : 30-40.

Regular paper
Published: 28 February 2021 in Asian Journal of Control
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This paper is concerned with observer‐based trajectory control of directional drilling system with rotary steering devices. Since the trajectory orientation cannot be measured directly, most of the existing results implicitly assume that the trajectory orientation is equal to the measurement of orientation of the bottom hole assembly (BHA) or the drill bit, which would bring in certain control errors in practice. To avoid such control errors, in this paper, a trajectory control approach is established, which includes a state observer to estimate the trajectory orientation based on the measurement of the BHA orientation. Firstly, the relationship between the trajectory orientation and the BHA orientation is analyzed, and a trajectory evolution model is introduced according to the analysis. Secondly, based on this trajectory evolution model, a variable transformation technique is applied such that a trajectory tracking control problem is formulated. Thirdly, a feedback control strategy is devised based on the estimation of the trajectory orientation for trajectory tracking. Fourthly, stability analysis of the closed‐loop system is discussed, and the design of the controller and state observer is done. Finally, a typical case is used to illustrate the correctness and effectiveness of our approach.

ACS Style

Zhen Cai; Xuzhi Lai; Min Wu; Luefeng Chen; Chengda Lu. Observer‐based trajectory control for directional drilling process. Asian Journal of Control 2021, 1 .

AMA Style

Zhen Cai, Xuzhi Lai, Min Wu, Luefeng Chen, Chengda Lu. Observer‐based trajectory control for directional drilling process. Asian Journal of Control. 2021; ():1.

Chicago/Turabian Style

Zhen Cai; Xuzhi Lai; Min Wu; Luefeng Chen; Chengda Lu. 2021. "Observer‐based trajectory control for directional drilling process." Asian Journal of Control , no. : 1.

Journal article
Published: 24 February 2021 in IEEE Transactions on Cybernetics
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This article presents an improved equivalent-input-disturbance (EID) approach to handle unknown disturbances and plant uncertainties. The disturbances and uncertainties are treated as a lumped disturbance in an EID-based control system. The effect of the lumped disturbance is compensated by an EID estimator. A constraint between design parameters and uncertainties is imposed on the design of the estimator. In addition, there are insufficient analyses of the influence of uncertainties on the control performance and the stability of the system. A new filter is devised for an improved EID estimator in this article to remove the constraint. This ensures that the sensitivity of the system to disturbances at low frequencies can be freely decreased. An analysis of the system reveals that uncertainties not only influence disturbance-rejection and reference-tracking performance but also affect system stability. A sufficient stability criterion is derived with consideration of uncertainties. The validity of the presented method is demonstrated by simulation and experimental results.

ACS Style

Youwu Du; Weihua Cao; Jinhua She; Min Wu; Mingxing Fang; Seiichi Kawata. Disturbance Rejection and Robustness of Improved Equivalent-Input-Disturbance-Based System. IEEE Transactions on Cybernetics 2021, PP, 1 -10.

AMA Style

Youwu Du, Weihua Cao, Jinhua She, Min Wu, Mingxing Fang, Seiichi Kawata. Disturbance Rejection and Robustness of Improved Equivalent-Input-Disturbance-Based System. IEEE Transactions on Cybernetics. 2021; PP (99):1-10.

Chicago/Turabian Style

Youwu Du; Weihua Cao; Jinhua She; Min Wu; Mingxing Fang; Seiichi Kawata. 2021. "Disturbance Rejection and Robustness of Improved Equivalent-Input-Disturbance-Based System." IEEE Transactions on Cybernetics PP, no. 99: 1-10.