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International Conference on Computer and Electrical engineering, ICCEE

作者： Masoud Sadeghian Alireza Fatehi Department of Mechatronics Engineering International Campus Sharif University of Technology Kish Island Iran Advanced Process Automation and Control (APAC) Research group Faculty of Electrical Engineering K.N. Toosi University of Technology Tehran Iran

One of the most important parts of a cement factory is the cement rotary kiln which plays a key role in quality and quantity of produced cement. In this part, the physical exertion and bilateral movement of air and materials, together with chemical reactions take place. Thus, this system has immensely complex and nonlinear dynamic equations. These equations have not worked out yet. Only in exceptional case; however, a large number of the involved parameters were crossed out and an approximation model was presented instead. This issue caused many problems for designing a cement rotary kiln controller. In this paper, we presented nonlinear predictor and simulator models for a real cement rotary kiln by using nonlinear identification technique on the Locally Linear Neuro-Fuzzy (LLNF) model. For the first time, a simulator model as well as a predictor one with a precise fifteen minute prediction horizon for a cement rotary kiln is presented. These models are trained by LOLIMOT algorithm which is an incremental tree-structure algorithm. At the end, the characteristics of these models are expressed. Furthermore, we presented the pros and cons of these models. The data collected from White Saveh Cement Company is used for modeling.

关键词： Predictive models Kilns Computational modeling Power system modeling Production facilities Nonlinear control systems Chemical technology Nonlinear equations Automatic control Process control

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Data-Driven Stochastic-Robust Planning for Resilient Hydrogen-Electricity System with Progressive Hedging Decoupling

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IEEE Transactions on Sustainable Energy 2024年

作者： Wen, Ziyi Zhang, Xian Wang, Guibin Li, Yiqun Qiu, Jing Wen, Fushuan Harbin Institute of Technology Shenzhen School of Mechanical Engineering and Automation 518055 China Shenzhen University College of Mechatronics and Control Engineering Shenzhen518060 China Southeast University School of Transportation Nanjing211189 China The University of Sydney School of Electrical and Information Engineering SydneyNSW2006 Australia Zhejiang University College of Electrical Engineering Hangzhou310027 China

Given the severe damage that typhoons can inflict on power systems, it is of utmost urgency to develop proactive pre-disaster planning to enhance power system resilience and mitigate economic losses. To this end, considering the high efficiency and long-term storage capabilities of hydrogen energy, a resilience-oriented planning model of the hydrogen-electricity integrated energy system (H-EIES) is constructed in this work. In this resilience-oriented planning model, hardening power lines and constructing hydrogen-to-power stations (H2Ps) are jointly planned to reduce load shedding during typhoons. A tri-layer stochastic-robust optimization (SRO) approach is proposed to find the optimal construction strategy under uncertainties, where the first layer determines the planning strategy, the second layer identifies the worst outage contingency, and the third layer ensures the optimal operation. However, the uncertainty of typhoons presents significant challenges to the feasibility of the proposed SRO approach. Therefore, this work leverages the Wasserstein generative adversarial network with gradient penalty (WGAN-GP) and spectral clustering method to quantify the typhoon uncertainty, capturing the spatial correlations of 2-dimensional (2D) gridded wind speeds and exploring typical typhoon scenarios. Additionally, a novel nested column-and-constraint generation with progressive hedging algorithm (C&CG-PHA) is elaborately designed to solve the complex tri-layer and multi-scenario coupled optimization problem. In this developed C&CG-PHA, C&CG is employed to decouple the tri-layer planning model into a master problem and a subproblem for iterative solving, and PHA is employed to decouple the multi-scenario embedded master problem into serval scenario-independent problems to improve the solving efficiency. Validating by the real-life typhoon data, numerical experiments are carried out and indicate the economic efficiency and robustness of the proposed SRO approach, where th

关键词： Stochastic systems

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Reinforcement Learning-Based Predictive control for Autonomous Electrified Vehicles

Reinforcement Learning-Based Predictive Control for Autonomo...

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2018 IEEE Intelligent Vehicles Symposium, IV 2018

作者： Liu, Teng Yang, Chao Hu, Chuanzheng Wang, Hong Li, Li Cao, Dongpu Wang, Fei-Yue State Key Laboratory of Automotive Simulation and Control Jilin University China Vehicle Intelligence Pioneers Inc. Qingdao Shandong266109 China Jiangsu XCMG Construction Machinery Research Institute Ltd. Xuzhou Jiangsu221004 China Mechanical and Mechatronics Engineering Department Waterloo University N2L 3G1 Canada Faculty of Department of Automation Tsinghua University China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China

ISBN: (纸本)9781538644522

This paper proposes a learning-based predictive control technique for self-driving hybrid electric vehicle (HEV). This approach is a hierarchical framework. The higher-level is a human-like driver model, which is applied to predict accelerations in the car following situation to replicate a human driver's demonstrations. The lower-level is a reinforcement learning (RL)-based controller, which enforces the battery and fuel consumption constraints to improve energy efficiency of HEV. In addition, we present induced matrix norm (IMN) to handle cases that the training data cannot provide sufficient information on how to operate in current driving situation. Simulation results illustrate that the proposed method can reproduce human driver's driving style and promote fuel economy. © 2018 IEEE.

关键词： Reinforcement learning

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Intelligent On-Line System for Monitoring Technical Condition of High-Voltage Cable Couplings

Intelligent On-Line System for Monitoring Technical Conditio...

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International Russian Smart Industry Conference (SmartIndustryCon)

作者： Vadim R. Gasiyarov Stanislav V. Voronin Andrey A. Radionov Ivan V. Lyubimov Sergey A. Evdokimov Vadim R. Khramshin Department of Automation and Control Moscow Polytechnic University Moscow Russia Department of Mechatronics and Automation South Ural State University Chelyabinsk Russia Power Engineering and Automated Systems Institute Nosov Magnitogorsk State Technical University Magnitogorsk Russia

The article provides the characteristics of the end cable couplings of the closed switchgear 110 kV at the electric steelmaking workshop of the metallurgical plant. The functions of the continuous technical condition monitoring system are substantiated, including continuous temperature monitoring and on-line registration of partial discharges in the insulation. The first function provides monitoring of the operational load, and the second has the maximum sensitivity for diagnosing defect propagation. A functional diagram of the developed intelligent on-line system for monitoring technical condition with digital signal transmission is provided. The choice of sensors and processor unit is justified. The authors consider the temperature control system of high-voltage equipment “WDM-T”, including a wireless sensor and an information receiver. The results of monitoring the thermal regime are provided, the advantages of partial discharge analysis are pointed out. The temperature trends of the end couplings included in the cable line phases are considered. The system is implemented on the closed switchgear 110 kV end couplings, its long-term operation has confirmed the effectiveness of technical condition monitoring. The developed system may be a component of an on-line cyberphysical system for monitoring the condition of high-voltage equipment in the electric steelmaking workshop.

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SOME FUNDAMENTAL PROPERTIES ON THE SAMPLING FREE NABLA LAPLACE TRANSFORM

arXiv

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arXiv 2019年

作者： Chen, YangQuan Wei, Yiheng Chen, Yuquan Wang, Yong Lab of Mechatronics Embedded Systems and Automation School of Engineering University of California Merced 5200 North Lake Road MercedCA95343 United States Lab of Vibration Control and Vehicle Control Department of Automation University of Science and Technology of China Anhui Hefei230026 China

Discrete fractional order systems have attracted more and more attention in recent years. Nabla Laplace transform is an important tool to deal with the problem of nabla discrete fractional order systems, but there is still much room for its development. In this paper, 14 lemmas are listed to conclude the existing properties and 14 theorems are developed to describe the innovative features. On one hand, these properties make the N-transform more effective and efficient. On the other hand, they enrich the discrete fractional order system theory. Copyright © 2019, The Authors. All rights reserved.

关键词： Laplace transforms

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Fuzzy controller Design for Atomic Force Microscope System

Fuzzy Controller Design for Atomic Force Microscope System

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International Symposium on Knowledge Acquisition and Modeling, KAM

作者： Her-Terng Yau Cheng-Chi Wang Chao-Lin Kuo Ming-Jyi Jang Yuan-Hung Su Department of Electrical Engineering Far East University Tainan Taiwan Department of Mechanical Engineering Far East University Tainan Taiwan Department of Automation and Control Engineering Far East University Tainan Taiwan Graduate Institute of Opto-Mechatronics Far East University Tainan Taiwan

This paper presents the design of a nonlinear rule based fuzzy logic controller for the nonlinear dynamic behavior of the probe tip of an atomic force microscope system (AFMs). At first, we use the bifurcation diagram to analysis the complex dynamic behavior of the atomic force microscope system. Next, the positive maximum Lyapunov exponent is obtained to identify that the chaotic motion do exist in AFMs. In order to suppress the undesired chaotic motion in AFMs, we address the design schemes of fuzzy logic controller to stabilize the slave chaotic AFMs to the master periodic AFMs. In the controller design process, it directly constructs the fuzzy rules subject to a common Lyapunov function such that the error dynamics of master and slave AFMs satisfy stability in the Lyapunov sense. It overcomes the trial-and-error tuning for the membership functions and rule base in traditional fuzzy logic control. Finally, a numerical simulation is used to illustrate the effectiveness of the proposed controller.

关键词： Atomic force microscopy Fuzzy control Fuzzy systems Force control control systems Fuzzy logic Chaos Nonlinear dynamical systems Master-slave Nonlinear control systems

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Development of the vibration analysis and suppression technology for laser galvanometers based on inertial sensing technology

Development of the vibration analysis and suppression techno...

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SICE International Symposium on control Systems (ISCS)

作者： Wen-Chuan Chen Yu-Liang Hsu Po-Huan Chou Hsin-Hung Lee Hsing-Cheng Chang Shih-Chin Yang Chin-Sheng Chen Department of Automatic Control Engineering Feng Chia University Taichung Taiwan Institute of Automation Technology National Taipei University of Technology Taipei Taiwan Mechatronics Control Department Industrial Technology Research Institute Hsinchu Taiwan Department of Mechanical Engineering National Taiwan University Taipei Taiwan

ISBN: (纸本)9781509056149

This paper presents an inertial-sensing-based vibration analysis and suppression system for laser galvanometers. The functions of this system are to measure the vibrations during rotation motions of galvanometers and to design a comb filter for restraining the vibrations of the galvanometers effectively. The proposed system is composed of an intelligent motion control platform, a servo driver circuit, a galvanometer driver module, a galvanometer, and a MEMS piezoelectric accelerometer. The proposed system can measure the vibration signals generated by the galvanometer using the piezoelectric accelerometer and utilize the fast Fourier transformation (FFT) to analyze the vibration frequencies. Subsequently, a digital comb filter is designed to restrain the vibrations of the galvanometer based on the obtained vibration frequencies. Finally, the experimental results have successfully validated that the proposed inertial-sensing-based vibration analysis and suppression system, and the designed comb filter can measure, analyze, and restrain the vibrations of the galvanometer effectively and further improve the accuracy and stability of the laser galvanometer scanning system.

关键词： Vibrations Frequency measurement Resonant frequency Vibration measurement Mirrors Accelerometers Torque

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Batch constrained multi-objective Bayesian optimization using the example of ultrasonic wire bonding

Batch constrained multi-objective Bayesian optimization usin...

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IEEE/ASME (AIM) International Conference on Advanced Intelligent mechatronics

作者： Fabian Reiling Christian Henke Matthias Hunstig Stefan Gröger Ansgar Trächtler department Scientific Automation Fraunhofer Institute for Mechatronic Systems Design Paderborn Germany Deputy Head of Research at Hesse GmbH Paderborn Germany Head of Chair of Control Engineering and Mechatronics Paderborn Germany

ISBN: (数字)9798350355369

ISBN: (纸本)9798350355376

Setting optimum process parameters for complex manufacturing processes such as ultrasonic wire bonding is already challenging for one target variable. Due to numerous influencing physical factors, such processes often lack the necessary detailed physical models. Due to the lack of these models, such processes cannot be adjusted to an optimum using classic optimization methods. In manufacturing processes in particular, the process must be optimized with regard to several objectives such as process time or quality. A popular method for optimizing such processes without models is multi-objective Bayesian optimization. For this purpose, surrogate models in the form of Gaussian processes are used in combination with a multi-objective acquisition function. In real processes, parallel function evaluation offers advantages in terms of trial efficiency and scalability. In this paper, we present a new algorithm for batch-constrained Bayesian multi-objective optimization. With this algorithm, an arbitrary number of function evaluations per iteration can be specified, whereby a more efficient determination of the Pareto front approximation can be achieved in real applications. For this purpose, the Expected Hypervolume Improvement is extended by a term to consider a quality criterion. Using the ultrasonic wire bonding process as an example, we experimentally prove that the proposed framework is able to approximate the Pareto front of the system with only a few function evaluations. For this purpose, the process capability index should be maximized and the process time minimized.

关键词： Manufacturing processes mechatronics Scalability Optimization methods Predictive models Approximation algorithms Acoustics

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A novel type of trigonometric neural network trained by Extended Kalman Filter

A novel type of trigonometric neural network trained by Exte...

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International Workshop on Advanced Computational Intelligence (IWACI)

作者： M. Norouzi M. Mansouri M. Teshnehlab M. Aliyari Shoorehdeli Faculty of Engineering Department of Computer Engineering Science and Research Branch Islamic Azad University Iran Intelligent System Laboratory (ISLAB) Faculty of Electrical Engineering Control Department K.N. Toosi University of Technology Tehran Iran Faculty of Electrical Engineering Department of Mechatronics Engineering Advanced Process Automation &Control Laboratory (APAC) K.N. Toosi University of Technology Tehran Iran

In this study, a new type of trigonometric neural network is presented by adding frequency and phase to trigonometric activation functions. The proposed trigonometric neural network has more flexibility in comparison with conventional trigonometric neural networks and even other types of neural networks. Due to the low convergence rate and high posibility of trapping in a local minimum of backpropagation algorithm, Extended Kalman Filter algorithm is used to train the neural network's parameters which they appear in a nonlinear form. The Simulation of the suggested neural network based on the prediction of Mackey-Glass time series and identification of a nonlinear dynamic ystem reveals the efficiency of the proposed network. To show the efficiency of this method, the results are compared with the results of the others.

关键词： Biological neural networks Kalman filters Equations Neurons Vectors Covariance matrix Mathematical model

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A frequency limited model reduction technique for linear discrete systems

A frequency limited model reduction technique for linear dis...

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Australian control Conference (AUCC)

作者： Xin Du Ahmad Jazlan Victor Sreeram Roberto Togneri Abdul Ghafoor Shafishuhaza Sahlan School of Mechatronics Engineering and Automation Shanghai University Shanghai P. R. China Electronic and Computer Engineering University of Western Australia Western Australia WA Australia Department of Electrical Engineering National University of Sciences and Technology Rawalpindi Pakistan Control & Mechatronics Eng. Dept. (CMED) Universiti Teknologi Malaysia Skudai Johor Malaysia

This paper describes the model reduction framework for single-input single-output (SISO) discrete-time systems based on the preservation parameters such as Markov properties of the original system by applying a Frequency-Limited Impulse Response Gramian based Balanced Truncation method. This proposed method extends the Frequency-Limited Impulse Response Gramians model reduction method for continuous systems described in the recent paper in [20] to be applicable for discrete time systems. A numerical example is provided to compare the performances between various frequency limited model reduction methods at an arbitrarily selected frequency range within the passband of a digital filter. The stability of the reduced order models are also checked for each scenario.

关键词： Reduced order systems Observability controllability Matrix decomposition Time-frequency analysis Equations Mathematical model

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