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Measurement of surface stress-strain distribution inside a grain of carbon steel via optical microscope

Measurement 2025年 255卷

作者： I Dewa Made Oka Dharmawan Jinyi Lee Department of Control Instrumentation and Robot Engineering Graduate School of Chosun University Gwangju 61452 Republic of Korea Interdisciplinary Program in IT-BIO Convergence System Chosun University Gwangju 61452 Republic of Korea Department of Electronic Engineering Chosun University Gwangju 61452 Republic of Korea

The advancement of alloys and steel in engineering highlights the critical need for robust methods to ensure structural integrity. While traditional Non-Destructive Testing and Evaluation (NDT/E) techniques provide valuable insights, they often fail to detect pre-existing stress conditions that contribute to fatigue cracks. Recent approaches have addressed this limitation by analyzing stress and strain at the grain level using advanced measurement systems—often based on diffraction techniques—integrated with Finite Element Method (FEM) and Digital Image Correlation (DIC) platforms. However, the application of these techniques for in-service inspections remains limited by challenges in accessibility, cost, and scalability. To overcome these issues, an integrated 2D surface system combining optical microscopy with DIC and grain-level analysis within the FEM framework is proposed. This method enables efficient visualization of grain-level deformation and stress distribution, thereby providing deeper insights into the microstructural behavior of polycrystalline materials under external loads. The proposed methodology is theoretically outlined and validated through simulations and experimental analyses, demonstrating its potential as a practical solution for in-service inspections. Ultimately, this approach is expected to advance inspection techniques by offering an accessible and scalable tool for monitoring microstructural behavior and identifying potential failure mechanisms through surface analysis.

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Finite-time stability of delayed systems

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IMA Journal of Mathematical control and Information 2000年第2期17卷 101-109页

作者： Lazarević, M.P. Debeljković, D.Lj. Nenadić, Z.Lj. Milinković, S.A. Faculty of Mechanical Engineering Department of Control Engineering 27. marta 80 11000 Belgrade Yugoslavia Faculty of Technology and Metallurgy System Control Group Karnegijeva 4 11000 Belgrade Yugoslavia

The problem of sufficient conditions that enable system trajectories to stay within the a priori given sets for a particular class of autonomous delayed system. The main features of finite-time stability have been extended to particular class of linear autonomous delayed systems. The results give sufficient conditions for the stability of the system under consideration, and are derived using a technique which differs significantly from approaches used in all references cited.

关键词： Delay control systems

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Teaching and Practicing Model Predictive control

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IFAC-PapersOnLine 2016年第6期49卷 34-39页

作者： Honc, Daniel Sharma K., Rahul Abraham, Anuj Duek, Frantiek Pappa, Natarajan Department of Process Control Faculty of Electrical Engineering and Informatics University of Pardubice Czech Republic Department of Instrumentation Engineering Madras Institute of Technology Campus Anna University Chennai India

How to explain Model Predictive control (MPC) to students? How to practise it? The paper deals with chain of actions involving teaching, practicing and laboratory application of MPC at University of Pardubice in Czech Republic and at Anna University in India. Individual steps are presented and discussed with examples from educational experience - e.g. modelling and identification, derivation of MPC controller, simulations and laboratory applications. Every phase has a key and weak point as well. Desired results is that students understand better the theoretical concepts and they are able to apply predictive controllers at least for laboratory processes. Derivations and MATLAB scripts are available online. © 2016

关键词： Model predictive control controllers Experiments Identification (control systems) MATLAB Models Optimization Predictive control systems Teaching Czech Republic Educational experiences Laboratory process Matlab scripts Modelling and identifications Predictive controller Weak points

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Self-balancing Robot control Using Fractional-Order PID controller

Self-balancing Robot Control Using Fractional-Order PID Cont...

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2019 International MultiConference of Engineers and Computer Scientists, IMECS 2019

作者： Kankhunthodl, K. Kongratana, V. Numsomran, A. Tipsuwanporn, V. Instrumentation Engineering Faculty of Engineering King Mongkut’s Institute of Technology Ladkrabang Bangkok Thailand Department of Instrumentation and Control Engineering Faculty of Engineering King Mongkut’s Institute of Technology Ladkrabang Bangkok Thailand department of Instrumentation and Control Engineering Faculty of Engineering King Mongkut’s Institute of Technology Ladkrabang Bangkok Thailand Department of Instrumentation and Control Engineering Faculty of Engineering King Mongkut’s Institute of Technology Ladkrabang Bangkok Thailand

This paper presents a two-wheeled robot control that can balance upright on its own by controlling the angular speed of the motor to keep the robot upright using measured data from the gyroscope sensor. The aim of this study is to demonstrate the design of fractional-order PID controller (FOPID) that has more controllability and the ability to adjust outperform traditional PID controller. The design of optimal FOPID controller based on integer-order PID parameters are explained and validated its performance compared with the traditional PID controller using Matlab simulation. As well as the real system experiment is implemented on Raspberry Pi using IIR filters cascaded second-order section form II. The study revealed the appropriate concept of implementation of FOPID on the real system. © 2019 Turkiye Klinikleri Journal of Medical Sciences. All rights reserved.

关键词： controllers

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Neural network and principal component regression in non-destructive soluble solids content assessment:a comparison

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Journal of Zhejiang University-Science B(Biomedicine & Biotechnology) 2012年第2期13卷 145-151页

作者： Kim-seng CHIA Herlina ABDUL RAHIM Ruzairi ABDUL RAHIM Department of Control and Instrumentation Faculty of Electrical EngineeringUniversiti Teknologi Malaysia

Visible and near infrared spectroscopy is a non-destructive,green,and rapid technology that can be utilized to estimate the components of interest without conditioning it,as compared with classical analytical *** objective of this paper is to compare the performance of artificial neural network(ANN)(a nonlinear model)and principal component regression(PCR)(a linear model)based on visible and shortwave near infrared(VIS-SWNIR)(400-1000 nm)spectra in the non-destructive soluble solids content measurement of an ***,we used multiplicative scattering correction to pre-process the spectral ***,PCR was applied to estimate the optimal number of input ***,the input variables with an optimal amount were used as the inputs of both multiple linear regression and ANN *** initial weights and the number of hidden neurons were adjusted to optimize the performance of *** suggest that the predictive performance of ANN with two hidden neurons outperforms that of PCR.

关键词： Artificial neural network （ANN） Principal component regression （PCR） Visible and shortwave nearinfrared （VIS-SWNIR） Spectroscopy Apple Soluble solids content （SSC）

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Implementing Industry 4.0 in Discrete Manufacturing: Options and Drawbacks

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IFAC-PapersOnLine 2018年第6期51卷 473-478页

作者： Arm, J. Zezulka, F. Bradac, Z. Marcon, P. Kaczmarczyk, V. Benesl, T. Schroeder, T. Department of Control and Instrumentation Faculty of Electrical Engineering and Communication Brno University of Technology Brno Czech Republic Institute for Automation Engineering Faculty of Electrical Engineering and Information Technology Otto von Guericke University Magdeburg Germany

The Industry 4.0 concept embodies a topic widely discussed during specialized meetings and tutorials. Originally, this approach was interpreted as an attempt to shift industrial processes towards establishing the fully digitized smart factory; at present, however, it already exerts an influence on many other fields and disciplines. In this article, the concept is described from the perspective of discrete manufacturing. The implementation possibilities are outlined, with options such as the Asset Administrative Shell or Consumer-Provider model introduced in greater detail. We also mention some drawbacks to implementing job shop scheduling as provided by the latter option; these disadvantages include, for instance, the deadlock situation. Some methods to solve the problem are demonstrated to facilitate well-balanced presentation. A job shop scheduling algorithm using the AAS is also addressed, and a new evaluation function is proposed. © 2018

关键词： Job shop scheduling Industry 4.0 Optimization Scheduling algorithms deadlock decentralized Discrete manufacturing Distributed control Evaluation function Industrial processs Manufacturing plant Well balanced

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Discrete-Time PID×(n-2) Stage PD Cascade controllers with First Order Hold and Delayed First Order Hold Discretizations

Discrete-Time PID×(n-2) Stage PD Cascade Controllers with F...

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2017 International MultiConference of Engineers and Computer Scientists, IMECS 2017

作者： Chiengtee, Channarong Pannil, Pittaya Ukakimaparn, Prapart Trisuwannawat, Thanit Department of Instrumentation and Control Engineering Faculty of Engineering King Mongkut’s Institute of Technology Ladkrabang Bangkok10520 Thailand Department of Instrumentation and Control Engineering Faculty of Engineering King Mongkut’s Institute of Technology Ladkrabang Bangkok10520 Thailand Department of Instrumentation and Control Engineering Faculty of Engineering King Mongkut’s Institute of Technology Ladkrabang Bangkok10520 Thailand Department of Instrumentation and Control Engineering Faculty of Engineering King Mongkut’s Institute of Technology Ladkrabang Bangkok10520 Thailand

ISBN: (纸本)9789881404732

This paper proposes a technique to design the (n-2) stage PD (Proportional-Derivative) controller cascaded with the PID (Proportional-Integral-Derivative) controller in accordance with nth order plants. The Continuous-Time (CT) design is firstly reviewed to show the advantages of the Kitti’s method. The proposed technique is based on the Kitti’s method in combination with the use of First Order Hold (FOH) to discretize the CT plant and Delayed First Order Hold (DFOH) to discretize the CT controller for obtaining the proper Discrete-Time (DT) controller structure. The simulation results confirm that the proposed design technique can be applied to the DT framework with better specifications than it was expected.

关键词： Two term control systems

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Posicast PID × (n-2) Stage PD Cascade controllers for Magnetically-Levitation system

Posicast PID × (n-2) Stage PD Cascade Controllers for Magne...

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2017 International MultiConference of Engineers and Computer Scientists, IMECS 2017

作者： Surintramon, Panupong Pannil, Pittaya Ukakimaparn, Prapart Trisuwannawat, Thanit Department of Instrumentation and Control Engineering Faculty of Engineering King Mongkut's Institute of Technology Ladkrabang Bangkok10520 Thailand Department of Instrumentation and Control Engineering Faculty of Engineering King Mongkut’s Institute of Technology Ladkrabang Bangkok10520 Thailand Department of Instrumentation and Control Engineering Faculty of Engineering King Mongkut’s Institute of Technology Ladkrabang Bangkok10520 Thailand Department of Instrumentation and Control Engineering Faculty of Engineering King Mongkut’s Institute of Technology Ladkrabang Bangkok10520 Thailand

ISBN: (纸本)9789881404732

When a plant to be controlled is third or higher nth order, the PID×(n-2) stage PD cascade controllers are very suitable to be applied for control. To verify the advantages of these controllers, the Magnetically-Levitation plant is then selected as an example of unstable plant to be stabilized and controlled. The design technique is based on placing the controller zeros. The overall controlled system can be approximated as a standard second-order system prompt for designing the Posicast controller to obtain the output response with no overshoot in the last step.

关键词： controllers

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Unified resilience model using deep learning for assessing power system performance

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Heliyon 2025年第4期11卷 e42802页

作者： Artemchuk, Volodymyr Garbuz, Iurii Jamil Alsayaydeh, Jamil Abedalrahim Shkarupylo, Vadym Oliinyk, Andrii Bin Yusof, Mohd Faizal Herawan, Safarudin Gazali Department of Mathematical and Econometric Modelling G.E. Pukhov Institute for Modelling in Energy Engineering of the NAS of Ukraine Kyiv Ukraine Department of Environmental Protection Technologies and Radiation Safety Center for Information-analytical and Technical Support of Nuclear Power Facilities Monitoring of the NAS of Ukraine Kyiv Ukraine Department of Іnformation Systems in Economics Kyiv National Economic University Named After Vadym Hetman Kyiv Ukraine Department of Computerized Control System National Aviation University Kyiv Ukraine Department of Engineering Technology Fakulti Teknologi Dan Kejuruteraan Elektronik Dan Komputer (FTKEK) Universiti Teknikal Malaysia Melaka (UTeM) Melaka 76100 Malaysia Department of Computer Systems Networks and Cybersecurity of the National University of Life and Environmental Sciences of Ukraine Kyiv Ukraine Department of Software Tools Faculty of Computer Science and Technology Zaporizhzhia Polytechnic National University Zaporizhzhia Ukraine Research Section Faculty of Resilience Rabdan Academy Abu Dhabi United Arab Emirates Industrial Engineering Department Faculty of Engineering Bina Nusantara University Jakarta 11480 Indonesia

Energy resilience in renewable energy sources dissemination components such as batteries and inverters is crucial for achieving high operational fidelity. Resilience factors play a vital role in determining the performance of power systems, regardless of their operating environment and interruptions. This article introduces a Unified Resilience Model (URM) using Deep Learning (DL) to enhance power system performance. The proposed model analyzes environmental factors impacting the resilience of batteries and energy storage devices. This deep learning approach trains performance-impacting factors using previously known low resilience drain data. The learning output is utilized to augment various strengthening factors, thereby improving resilience. Drain mitigation and performance improvements are combined for direct impact verification. This process validates the model's fidelity in enhancing power system performance, with a specific focus on the impact of weather factors. © 2025 The Authors

关键词： Deep learning Energy resilience Fidelity Weather impact

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Optimal Design of Reactive Power PI Regulator for Hydro Power Plants

Optimal Design of Reactive Power PI Regulator for Hydro Powe...

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IEEE International Conference on control Applications

作者： Robert, Gerard Hurtado, Dominique Control System EDF Hydro Engineering Centre France Instrumentation and Control Department EDF National Nuclear Equipments Centre France

ISBN: (纸本)9781424422227

This paper presents an optimal PI controller for Automatic reactive power Regulators (AQR) which equip some French hydro power plants. The developed AQR algorithm participates to secondary voltage control following some control performance criteria required by the Transmission system Operator. controller parameters are calculated by solving a constrained nonlinear optimization that maximizes the robustness of the feedback control while incorporating the control performance specifications. That involves a 'worst case' design approach which takes into account modeling uncertainties and gain variations in the operating domain. Moreover a mere anti-windup strategy has been achieved in the AQR algorithm. Referring to Matlab simulations and measurements carried out on a 110 MVA pilot hydro unit, results are complying with demands.

关键词： Reactive power

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