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第43届中国控制会议

作者： Huaibo Ma Jun Ma Xiang Li Faculty of Information Engineering and Automation Kunming University of Science and Technology Yunnan Key Laboratory of Intelligent Control and Application Kunming University of Science and Technology

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

Aiming at the problem that the ice-copper grade prediction process is difficult to effectively capture the long-term dependency relationship between data,which leads to low prediction accuracy,it is proposed to construct a model using the powerful long-term memory capability and bidirectional information prediction ability of bidirectional long and short-term memory network(BiLSTM) model,and further optimize the model by using the genetic algorithm(GA) to achieve accurate prediction of ice-copper ***,the genetic algorithm was used to find the optimal hyperparameter combination of the ***,the predicted values of the BiLSTM model optimized by the genetic algorithm are compared with the predicted values of the existing methods and the unoptimized Bi LSTM model using different evaluation ***,the SHAP method is used to give the overall and local interpretation of the prediction results of the BiLSTM *** experimental results show that the RMSE of the BiLSTM model optimized by the genetic algorithm is reduced by at least 3.05%,the MAE is reduced by at least 2.75%,the MAPE is reduced by at least 3.29%,and the R2 is increased by at least 1.51%,which verifies the effectiveness of the proposed method in solving the problem of ice-copper grade prediction,and the SHAP method is able to explain the output of the Bi LSTM model efficiently and increase the transparency of the *** SHAP method can effectively explain the output of the BiLSTM model and increase the transparency of the model.

关键词： Matte grade prediction Genetic algorithm BiLSTM model SHAP model interpretation

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Anomaly Detection of Copper Melting Process Data Based on Anomaly Transformer

Anomaly Detection of Copper Melting Process Data Based on An...

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第43届中国控制会议

作者： Junjia Zhang Jun Ma Xiang Li Faculty of Information Engineering And Automation Kunming University of Science and Technology Yunnan Key Laboratory of Intelligent Control and Application Kunming University of Science and Technology

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

In this paper,aiming at the copper melting process,the relevant process variable parameters are coupled with each other,complicated and change with the production cycle,which leads to the anomaly detection of copper melting *** accuracy of copper melting data,we propose an Anomaly Transformer model based on the Transformer model,which replaces the original Self-Attention mechanism with Anomaly-Attention mechanism,to realize accurate and reliable copper melting process data anomaly *** order to realize accurate and reliable anomaly detection of copper melting process ***,the degree of anomaly of copper melting process data at each time point is measured by the correlation dispersion,and the KL dispersion distance value is utilized to quantify the degree of *** value of KL dispersion to quantify the change of the value of each neighboring time point,and secondly,the above quantized distance value is transform the its attention mechanism into the anomaly attention mechanism form.,in order to present the anomaly deviation and weight of each time point,and distinguish normal points from anomaly points,and finally,the trained anomaly Transformer model is analyzed on the test set for anomaly ***,the trained anomaly Transformer model is analyzed on the test set for anomaly detection,and the results are analyzed and interpreted using F1 evaluation *** experimental results show that in the production process dataset of copper *** application of correlation-based discretization brings a certain 3.7%improvement in the F1 *** addition of the anomalous attention module achieved 43.4% performance improvement,and the final combination of the combination of the combined KL dispersion and the anomaly attention module yielded an F1 score of 71.31,achieving a better anomaly detection result.

关键词： Anomaly Detection of Copper Melting Process Data KL dispersion distance Anomaly-Attention Transformer

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A Bayes CNN-LSTM approach for aero-engine remaining life predictions

A Bayes CNN-LSTM approach for aero-engine remaining life pre...

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第43届中国控制会议

作者： Jiangyan Zhu Jun Ma Jiande Wu Faculty of Information Engineering and Automation Kunming University of Science and Technology Yunnan Key Laboratory of Intelligent Control and Application Kunming University of Science and Technology

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

Remaining life prediction(RUL) plays an important role in prognostic health *** recent years,deep learning-based methods have been widely used for RUL ***,deep learning-based methods all focus on point prediction of RUL,ignoring the uncertainty associated with inaccuracies in the data and *** the prominence of Bayesian methods in uncertainty modelling,this paper uses a Monte Carlo dropout(MC-Dropout)-based Bayesian approximation to capture the epistemic and contingent uncertainty in the prediction process.A Bayes CNN-LSTM-based spatial-temporal feature extraction model is proposed to implement RUL prediction and quantify *** proposed method is also validated on the CMAPSS dataset and compared with CNN,LSTM and CNN-LSTM to verify the effectiveness of Bayesian neural networks.

关键词： Remaining life prediction Bayesian neural networks Epistemic uncertainty Spatial-temporal feature

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Practical Sliding Mode control with Time Delay Estimation for a 4-DOF Parallel Manipulator with Variant Payload 26

Practical Sliding Mode Control with Time Delay Estimation fo...

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26th International Conference on Mechatronics Technology, ICMT 2023

作者： Tran, Duc Thien Nguyen, Thanh Nha Nguyen, Xuan Tra Nguyen, Duc Manh Truong, Quoc Thanh Trinh, Hoai An Nguyen, Manh Hung Ahn, Kyoung Kwan Ho Chi Minh City University of Technology and Education Automation Control Department Ho Chi Minh City70000 Viet Nam Hcmc University of Technology Faculty of Mechanical Engineering Ho Chi Minh City70000 Viet Nam School of Mechanical and Automotive Engineering University of Ulsan Ulsan44610 Korea Republic of

ISBN: (纸本)9798350381429

This paper proposes a sliding mode control (SMC) with a time delay estimation (TDE) for a 4-DOF parallel manipulator with modeling error and a variant payload in practice. The proposed control is constructed from a sliding mode control and a time delay estimator. The sliding mode control is designed to guarantee the tracking objective of the parallel robot. Additionally, the TDE is utilized to compensate for the lumped uncertainty. By incorporating these techniques in the proposed control, the proposed method not only guarantees stability but also enhances the accuracy of the tracking performance in the parallel robot against the lumped uncertainty. The stability and robustness of the closed-loop control system are evaluated by the Lyapunov approach in theory. Finally, some experiments are conducted on the 4-DOF parallel robot testbench. The experimental results of the proposed control are compared to other methods to verify its superiorities. © 2023 IEEE.

关键词： Sliding mode control

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Simulation-Based Metrological Temperature Ensuring and control of the Temperature Field in an Induction Furnace Based on Various Parameters

Simulation-Based Metrological Temperature Ensuring and Contr...

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International Conference on Computer and automation engineering, ICCAE

作者： Jan Rybář Samuel Emebu Sayed Yousuf Sayed Sohaibullah Zarghoon Lukáš Bartalský Peter Onderčo Andrej Smetánka Radek Matušů Faculty of Mechanical Engineering Institute of Automation Informatization and Measurement Slovak University of Technology Bratislava Slovakia Department of Separation Science LUT School of Engineering Science Lappeenranta-Lahti University of Technology Lappeenranta Finland Department of Auto mechanical Engineering Faculty of Electro-Mechanic Kabul Polytechnic University Kabul Afghanistan Department of Automation and Control Engineering Faculty of Applied Informatics Tomas Bata University in Zlín Zlín Czech Republic

ISBN: (数字)9798331533816

ISBN: (纸本)9798331533823

Induction heating is widely used in industrial furnaces because of its rapid response time and high energy efficiency. To design and optimize these furnaces, computer-aided simulations are essential. This study aims to develop an accurate temperature field model for a square cross-section steel billet in an induction furnace by leveraging various parameters in COMSOL Multiphysics software. The simulation analysis incorporated temperature dynamics, considering skin depth, temperaturedependent, and constant parameters of the steel billet. The datadriven model was converted into a state-space representation utilizing MATLAB's System Identification Toolbox. This conversion facilitated the design of a Linear Quadratic Regulator (LQR) with integral gain and pole placement. Further, these controllers' performance was analyzed, and controllers were successfully implemented to regulate the temperature field of the billet from initial temperature to reference temperature, utilizing the distributed parameter system control circuit.

关键词： Billets Analytical models Temperature Accuracy Computational modeling Furnaces Mathematical models Temperature control Steel Induction heating

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Event-Triggered Neural Asynchronous control of Nonhomogeneous Markov Jump Power Systems with Hybrid Cyberattacks and Unknown States

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IEEE Transactions on Power Systems 2025年

作者： Luo, Wende Chen, Haiyang Zong, Guangdeng Zhao, Xudong Qufu Normal University School of Engineering Rizhao276826 China Tiangong University School of Control Science and Engineering Tianjin300387 China Nanjing Institute of Technology School of Automation Nanjing211167 China Dalian University of Technology Faculty of Electronic Information and Electrical Engineering Dalian116024 China

This paper studies the observer-based eventtriggered neural asynchronous control problem of nonhomogeneous Markov jump power systems (MJPSs) under hybrid cyberattacks. Both periodic denial-of-service attacks and deception attacks (DAs) are involved because of the openness of networks. An event-triggered mechanism is established to ease the network load. Besides, neural network (NN) approaches are adopted to suppress the adverse effects of DAs on nonhomogeneous MJPSs, and the hidden Markov model (HMM) is employed to capture the asynchronous phenomenon between the system mode and the controller mode. With NN approaches and HMM, an observer-based NN asynchronous controller is designed. By constructing the mode- and parameter-dependent Lyapunov function, sufficient criteria ensuring boundedness in probability for nonhomogeneous MJPSs are obtained. Then, a design algorithm is shown to simultaneously obtain the controller gains, observer gains, and event-triggering weight matrices based on the established conditions. Finally, the single-machine infinitebus power system and 3-machine 6-bus power system are applied to justify the validity of the proposed algorithm. © 1969-2012 IEEE.

关键词： Lyapunov functions

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Bifurcation analysis of coupled Andronov-Hopf oscillators: A geometric approach

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IFAC-PapersOnLine 2022年第30期55卷 504-509页

作者： Hermann Folke Johann Rolf Thomas Meurer Automation and Control Group Faculty of Engineering Kiel University Kaiserstr. 2 D-24143 Kiel

The bifurcation behaviors of coupled Andronov-Hopf oscillators is analyzed. For this, an analytic solution of the bifurcation point of two linear, static coupled Andronov-Hopf oscillators is provided. This solution is rearranged so that the bifurcation can be interpreted geometrically by maximizing the area of an triangle defined by the system parameters. This geometric interpretation serves as the basis to address a network of linear, static coupled Andronov-Hopf oscillators, where a rather simple solution for the bifurcation point can be determined depending on a simple tree topology. With this, implications about the synchronization of this class of networks can be deduced.

关键词： Andronov-Hopf oscillators bifurcation analysis Andronov-Hopf bifurcation oscillator network synchronization

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Optimal PID control of Spatial Inverted Pendulum With Big Bang–Big Crunch Optimization

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IEEE/CAA Journal of Automatica Sinica 2020年第3期7卷 822-832页

作者： Jia-Jun Wang Tufan Kumbasar School of Automation Hangzhou Dianzi UniversityHangzhou 310018China IEEE Control and Automation Engineering Department Faculty of Electrical and Electronics EngineeringIstanbul Technical UniversityIstanbul TR-34469Turkey

As the extension of the linear inverted pendulum(LIP) and planar inverted pendulum(PIP), this paper proposes a novel spatial inverted pendulum(SIP). The SIP is the most general inverted pendulum(IP) than any existing IP. The model of the SIP is presented for the first time. The SIP inherits all the characteristics of the LIP and the PIP, which is a nonlinear,unstable and underactuated system. The SIP has five degrees of motion freedom and three control forces. Thus, it is a multipleinput and multiple-output(MIMO) system with nonlinear dynamics. To realize the spatial trajectory tracking of the SIP,the control structure with five PID controllers will be *** parameter tuning of the multiple PIDs is a challenging work for the proposed SIP model. To alleviate the difficulties of the parameter tuning for the multiple PID controllers, optimal PIDs can be achieved with the help of Big Bang – Big Crunch(BBBC) optimization. The BBBC algorithm can successfully optimize the parameters of the multiple PID controllers with high convergence speed. The optimization performance index of the BBBC algorithm is compared with that of the particle swarm optimization(PSO). Simulation results certify the rightness and effectiveness of the proposed control and optimization methods.

关键词： Big Bang–Big Crunch(BBBC) optimal PID control spatial inverted pendulum(SIP) spatial trajectory tracking

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Power Loss Analysis of Energy Management System with Model Predictive control in Mae Hong Son Microgrid

Power Loss Analysis of Energy Management System with Model P...

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IEEE International Conference on Power Electronics, Intelligent control and Energy Systems (ICPEICES)

作者： Nattakit Prapanwattana Donlapat Dechawatanapaisal David Banjerdpongchai Abhishek Rajan Dept. of Electrical Engineering Faculty of Engineering Center of Excellence in Intelligent Control Automation for Process Systems Chulalongkorn University Bangkok Thailand Dept. of Electrical Engineering National Institute of Technology Sikkim South Sikkim India

ISBN: (数字)9798350387193

ISBN: (纸本)9798350387209

Energy management system (EMS) is an important tool for energy efficiency and reliability of the power system. The optimal power dispatch of energy resources can be obtained using the nonlinear model predictive control (NMPC). It is formulated as an optimization problem subject to linear and nonlinear constraints. Although the existing system works well under the current conditions, power loss has not been considered. Power loss in transmission lines occurs due to their resistance and a high amount of power flow to loads connecting to the system. The power loss leads to decreased efficiency in the electrical system and reduces the lifespan of equipment because of the high temperature from loss. This paper aims to analyze the power loss in the Mae Hong Son (MHS) microgrid. To achieve the research objectives, we employ the EMS of MHS with NMPC and calculate power loss in transmission lines for a period of 7 days. EMS considers three objective functions, namely, total operating cost, total carbon dioxide emission, and combined economic and emission dispatch and take into account of three seasons consisting of rainy, winter, and summer.

关键词： Resistance Power transmission lines Microgrids Propagation losses Power system reliability Reliability Energy management systems Power generation Load flow Predictive control

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A K-Means Clustering-Based Optimization of IT2FL for Improved Regenerative Braking Performance 1

A K-Means Clustering-Based Optimization of IT2FL for Improve...

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1st International Conference on Smart Mechatronics, ICSMech 2024

作者： Wahid, Muhammad Rizalul Joelianto, Endra Budiman, Bentang Arief Tongroon, Manida Pratama, Mulia Gianti, Mahmudah Salwa Hernadi, Muhammad Fauzan Mechatronics and Artificial Intelligence Universitas Pendidikan Indonesia Bandung Indonesia Instrumentation Control and Automation Research Group Institut Teknologi Bandung Bandung Indonesia Institut Teknologi Bandung Faculty of Mechanical and Aerospace Engineering Bandung Indonesia Kasetsart University Atae Research Unit Department of Mechanical Engineering Sriracha Thailand Pusat Riset Mekatronika Cerdas Organisasi Riset Elektronika dan Informatika-BRIN Bandung Indonesia

ISBN: (纸本)9798350368918

Optimizing regenerative braking systems in electric vehicles presents a complex challenge requiring precise and adaptable control. This research proposes employing K-Means Clustering to the Interval Type-2 Fuzzy Logic (IT2FL) membership functions, thereby improving overall regenerative braking efficiency and enhancing driving range. This research demonstrates that implementing a K-Means in the IT2FL control system in electric vehicles effectively recovers 35.84% of energy. By incorporating a K-means-based approach, the IT2FL controller further enhances vehicle range by 43 kilometers, achieving a total range of 108 kilometers. In comparison, an IT2FL system without K-means recovered only 26.67% of energy and achieved a total range of 93 kilometers. Notably, the IT2FL controller with K-means enabled the electric vehicle to attain an energy efficiency of 22 kilometers per kilowatt-hour. These findings underscore the significant improvement in maximum range offered by the IT2FL controller with K-means compared to alternative methods. © 2024 IEEE.

关键词： Regenerative braking

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