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Application of grey system theory to phosphorite sinter process: From modeling to control

ASIAN JOURNAL OF CONTROL 2021年第1期23卷 13-22页

作者： Toktassynova, Nigina Fourati, Hassen Suleimenov, Batyrbek Satbayev Univ Dept Automat & Control Alma Ata Kazakhstan Univ Grenoble Alpes GIPSA Lab F-38400 Grenoble France

The sintering process of phosphorite ore occurs with a large amount of return caused by untimely process control. The control task of phosphorite ore sintering is to regulate the parameters of the process to obtain a high quality sinter. The parameter clearly responsible for sinter quality is the temperature in the wind box. Therefore, in order to solve the control task, it is necessary to predict the highest temperature of the charge (also known as the burn through point (BTP)). In this paper, the theory of grey systems is used as a predictive model, which makes it possible to obtain an adequate model that uses a small number of initial samples of real temperature data. Based on the grey model GMC(1,n) a new optimal model is presented, which is constructed by using optimization algorithm. Optimal model predicts the BTP, and to establish an optimal regulation, a control synthesis is carried out through an optimization of the prediction according to the "particle swarm" algorithm.

关键词： burn through point control structure grey system optimization algorithm predictive model sinter process

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Automatic design of a high-image-quality augmented reality head-up display optical system with single optical engine and multi-focal planes based on smoothly stitched polynomial

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OPTICAL ENGINEERING 2025年第4期64卷

作者： Guo, Xiangxin Mu, Da Changchun Univ Sci & Technol Sch Phys & Optoelect Engn Changchun Peoples R China Changchun Univ Sci & Technol Photoelect Measurement & Control Technol Inst Changchun Peoples R China

Conventional augmented reality head-up display (AR-HUD) suffers from various issues, such as the single-source image corresponding to the single focal plane, difficult optimization design of special face shape, and low definition under a wide frame. We propose an AR-HUD imaging system design method based on a single image source, multi-focal plane architecture with dual free-form surfaces, enabling compatibility with arbitrary windshield geometries. First, Malus' law and the law of reflection are applied to solve the point cloud envelope distribution. Following field-of-view expansion under adjacent-domain continuity conditions, the data are fitted and characterized using a smoothly stitched polynomial (SSP) to construct the initial architecture. Finally, an optical path feedback iteration method is employed to optimize edge fields and determine the optimal fitting coefficients. Using this method, two AR-HUD spatial display layouts are designed: horizontal and vertical multi-focal plane configurations. Simulation results indicate that the proposed iterative algorithm achieves high optimization efficiency. Comparative analysis between SSP-characterized surfaces and traditional XY polynomial surfaces demonstrates significant improvements in edge-field modulation transfer function and grid distortion. These results further validate the feasibility and superiority of the proposed design framework.

关键词： geometric optics smoothly stitched polynomial optimization algorithm multi-focal plane display

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Under-expanded jet noise prediction using surrogate models based on artificial neural networks 28

Under-expanded jet noise prediction using surrogate models b...

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28th AIAA/CEAS Aeroacoustics Conference

作者： Centracchio, Francesco Meloni, Stefano Jawahar, Hasan Kamliya Azarpeyvand, Mandi Camussi, Roberto Iemma, Umberto Roma Tre Univ Dept Engn Via Vito Volterra 62 I-00146 Rome Italy Univ Bristol Dept Aerosp Engn Bristol BS8 1TR Avon England Univ Bristol Dept Mech Aerosp Bristol BS8 1TR Avon England

ISBN: (数字)9781624106644

ISBN: (纸本)9781624106644

The use of surrogate models in recent times plays a key role in the design process and, over the past few years, machine learning algorithms are adapting to the use of active metamodelling techniques. In the present study, Artificial Neural Networks formulation is used as a data-driven nonlinear model aimed at describing the dynamics of an experimental test campaign related to the noise emitted by a single-stream jet in under-expanded conditions. The architecture of the neural network is selected employing a deterministic optimization algorithm, coupled with data informed tuning of the input parameters. The data set explored here was acquired in the state-of-the-art aeroacoustic facility at the University of Bristol. Both the near-and far-field acoustic measurements were carried out for a cold under-expanded jet for Mach numbers ranging from 1.1 to 1.4. The predictions by the metamodel are in good agreement with the experimental data, and the results demonstrate the capability of metamodels as a reliable tool to estimate jet noise in under-expanded flow conditions for a wide range of Mach numbers and near-field locations.

关键词： Surrogate Model Aircraft Noise Artificial Neural Network Mach Numbers Flow Conditions optimization algorithm Acoustic Measurement Near and Far Field Machine Learning Sound Pressure Level

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Design optimization of linear arrays and time-modulated antenna arrays using meta-heuristics approach

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INTERNATIONAL JOURNAL OF NUMERICAL MODELLING-ELECTRONIC NETWORKS DEVICES AND FIELDS 2022年第5期35卷

作者： Poddar, Suman Paul, Prajat Chakraborty, Avishek Ram, Gopi Mandal, Durbadal NIT Durgapur Dept ECE Durgapur W Bengal India SR Univ Dept ECE Warangal 506371 Telangana India NIT Warangal Dept ECE Warangal Telangana India

This article presents an approach to design a non-uniformly excited linear array antenna (LAA) and an alternate solution to LAAs in the form of time-modulated linear arrays (TMLA) for optimum far-field radiation pattern synthesis. The performance analysis of both the antenna arrays is studied, and the advantages and limitations of the proposed design approaches are presented with numerical outcomes. The far-field radiation pattern is optimized to reduce the interference by simultaneously lowering the sidelobe levels and increasing the directivities of LAAs and TMLAs. A recently proposed meta-heuristics computation technique called whale optimization algorithm (WOA) is employed to get the optimal results. The current excitation amplitude and the inter-element spacing of the 16-element LAA are optimized with WOA to attain the desired results. However, due to the large dynamic range ratios (DRRs) of excitation weights, array feed network complexities are increased, which restricts the design of typical LAAs. TMLAs can be regarded as an alternative solution where the problem of large DRRs as well as the design complexities of LAAs are eliminated. The concept of 'time' is vital in time-modulation as it plays the role of an added degree of freedom realized by periodically turning ON and OFF the radio-frequency switches with an electronic control circuit to achieve an enhanced array radiation pattern. WOA is utilized to determine the optimal switch-ON time periods for each array element and the optimal inter-element spacing of a 16-element TMLA. A set of numerical results validates the advantages of TMLAs over LAAs, and the limitations of TMLAs with respect to LAAs are also indicated. The performance of both the arrays is then compared with other published literature results to establish the superiority of the proposed approach.

关键词： linear array antenna meta-heuristics optimization algorithm pattern synthesis sidelobe levels time-modulation

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Application of Self-adaptive Vision-Correction algorithm for Water-Distribution Problem

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KSCE JOURNAL OF CIVIL ENGINEERING 2021年第3期25卷 1106-1115页

作者： Lee, Eui Hoon Chungbuk Natl Univ Sch Civil Engn Cheongju 28644 South Korea

Water is one of the essential elements in human life, and the water-distribution system is an important infrastructure that distributes water to the people. The design of the water-distribution system was done manually in the past, but recently, it was conducted by applying optimization algorithms. Various optimization algorithms were developed for the optimal design of the water-distribution system, but there was a disadvantage to perform sensitivity analysis for parameter estimation manually. A vision-correction algorithm (VCA) was developed to emulate the conventional manual vision-correction procedure, and it exhibited a good performance in many mathematical benchmark and civil engineering problems. However, the VCA has limited usefulness because of its large number of parameters, many of which require estimation. In this study, a self-adaptive VCA (SAVCA) was developed to overcome these shortcomings by modifying the parameters of the VCA to be self-adaptive or fixed. The Balerma network - a water-distribution system - was selected as a civil engineering problem. The results of SAVCA were better than those of other methods for the design of Balerma network. The SAVCA exhibited good usability and performance and can be applied to various fields in civil engineering including the water-distribution system.

关键词： Water-distribution system Civil engineering problem Metaheuristic Self-adaptive Vision correction optimization algorithm

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A Unified Electrothermal Behavior Modeling Method for Both SiC MOSFET and GaN HEMT

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IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS 2021年第10期68卷 9366-9375页

作者： Long, Xiao Jun, Zhao Zhang, Botao Chen, Dongdong Liang, Wu Minnan Univ Sci & Technol Sch Elect & Elect Engn Quanzhou 362700 Peoples R China Northeastern Univ State Key Lab Synthet Automat Proc Ind Shenyang 110819 Peoples R China Zhejiang Univ Coll Elect Engn Hangzhou 310027 Peoples R China Wuhan Univ Sci & Technol Sch Comp Sci & Technol Wuhan 430065 Peoples R China

This article has presented a unified electrothermal behavior modeling method for both silicon carbide (SiC) metal oxide semiconductor field effect transistor (mosfet) and gallium nitride (GaN) high electron mobility transistor (HEMT). The electrothemal behavior of these two kind of devices in both the first and the third quadrant is accurately modeled with serval compact equations. A modeling data and optimization algorithm-based parameter extraction method have been proposed to replace the previous time consuming and labor intensive one. The proposed parameter fitting algorithm is a genetic algorithm and Levenberg-Marquardt combined optimization algorithm possessing the advantages of global optimization and fast convergence speed, and modeling data can come from both datasheets and measurement. The correctness and accuracy of the proposed modeling method has been verified by simulation and experiment result. Meanwhile, it has been proved that the proposed modeling method is applicable to several commercially available SiC mosfets and GaN HEMTs.

关键词： Mathematical model Semiconductor device modeling MOSFET Silicon carbide Gallium nitride HEMTs Logic gates Electrothermal model gallium nitride (GaN) high electron mobility transistor (HEMT) optimization algorithm parameter extraction silicon carbide metal oxide semiconductor field effect transistor (MOSFET)

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Tour Design Using Resonant-Orbit Invariant Manifolds in Patched Circular Restricted Three-Body Problems

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JOURNAL OF GUIDANCE CONTROL AND DYNAMICS 2021年第1期44卷 106-119页

作者： Anderson, Rodney L. CALTECH Jet Prop Lab 4800 Oak Grove DrM-S 301-121 Pasadena CA 91109 USA

It is increasingly desirable to incorporate multibody effects in tour design early in the process to both discover new solutions and reduce the number and size of required maneuvers. Flybys have previously been designed using the heteroclinic connections of resonant orbits in the circular restricted three-body problem (CRTBP), but tour design often requires the consideration of additional moons, especially within the Jovian system. In this study, the heteroclinic connections of multiple resonant orbits are chained together within separate CRTBP models to perform multiple flybys that advance through desired resonances. Methods for patching these trajectories together are explored, and sample trajectories are computed.

关键词： Ganymede Orbital Period Computing optimization algorithm Numerical optimization Keplerian Orbit Libration Points Astrodynamics Astronomy Earth

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Data-Driven Modeling Approach for Mistuned Cyclic Structures

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AIAA JOURNAL 2021年第7期59卷 2684-2696页

作者： Kelly, Sean T. Lupini, Andrea Epureanu, Bogdan, I Univ Michigan Dept Mech Engn Ann Arbor MI 48109 USA

A data-driven approach to predict dynamic responses of mistuned cyclic dynamic structures is presented. Nominally cyclic structures such as turbomachinery bladed disks, or blisks, contain deviations from perfect symmetry, called mistuning, which can significantly increase the forced response of the structure subject to periodic excitations. The ability to accurately model the response is crucial for understanding a structure's dynamics during operation, and thus many reduced-order models have been developed. Data-driven approaches, however, are largely unexplored for predicting physical responses of cyclic structures, and are desirable due to their ability to leverage both computational and experimental data. In this paper, two feed-forward neural networks (FFNNs) are trained using physical responses and parameters from an individual sector of the cyclic structure. The desired physical responses of all sectors are predicted via a cyclic coupling procedure. By only using sector-level data, the number of simulations and/or experiments required to generate training data is substantially reduced, and the approach is not restricted to a specific projection basis unlike previous physics-based methods. A lumped mass model (LMM) of a blisk with stiffness mistuning is used to generate computational surrogate data for training and validation. Both FFNNs achieve high prediction accuracy on both training data and unseen test data. For a test case with an unseen mistuning pattern, this approach shows strong agreement with known actual responses. For this test case, prediction errors in the LMM blade tip amplitudes across all sectors are less than 2%, and the amplification factor error is less than 0.2%.

关键词： Convolutional Neural Network Structural Dynamics Turbomachinery Bladed Disks Stiffness Matrices optimization algorithm Frequency Domain Boundary Value Problems Structural Health Monitoring Graphics Processing Unit Monte Carlo Simulation

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Flexible job-shop scheduling and heterogeneous repairman assignment with maintenance time window and employee timetable constraints

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EXPERT SYSTEMS WITH APPLICATIONS 2021年 186卷

作者： An, Youjun Chen, Xiaohui Li, Yinghe Zhang, Ji Jiang, Junwei Chongqing Univ State Key Lab Mech Transmiss Chongqing 400030 Peoples R China

This work focuses on a new flexible scheduling problem in the job-shop that considers both maintenance activity and repairman competence under maintenance time window and employee timetable constraints. To deal with this problem, a hybrid multi-objective biogeography-based optimization (HMOBBO) algorithm is proposed, which has the following features: (1) a flexible decoding mechanism that considers maintenance time window and heterogeneous repairman constraints is designed;(2) three calculation methods of habitat suitability index (HSI) are defined;(3) tabu search (TS) algorithm is incorporated into the presented algorithm;and (4) a new offspring population generation mechanism is constructed. In numerical simulation, the parameter setting is firstly analyzed to ensure its robustness for different datasets via comparing the performance of each critical parameter combination. Secondly, different HSIs and migration models are separately compared through multiply running the literature instances, it is shown that fitness function 2 (the reciprocal of the sum of the normalized objective function values) and migration model 1 (constant immigration and linear emigration model) are the most suitable and steady in our experiments. Thirdly, the superiority of HMOBBO is proved by confronting with other six intelligent algorithms. Finally, through contrast variant models, the significance of considering employee timetable and repairman assignment is verified, and the benefits of the integrated optimization model/method are also demonstrated by comparing with hierarchical optimization model/method.

关键词： Flexible job-shop scheduling Heterogeneous repairman assignment Maintenance time window Employee timetable Hybrid multi-objective biogeography-based optimization algorithm

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Solving Logistics Distribution Center Location with Improved Cuckoo Search algorithm

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INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE SYSTEMS 2021年第1期14卷 676-692页

作者： Li, Juan Yang, Yuan-Hua Lei, Hong Wang, Gai-Ge Hubei Normal Univ Sch Comp & Informat Engn Huangshi 435002 Hubei Peoples R China Wuchang Univ Technol Sch Artificial Intelligence Wuhan 430223 Peoples R China Jilin Univ Key Lab Symbol Computat & Knowledge Engn Minist Educ Changchun 130012 Peoples R China Ocean Univ China Dept Comp Sci & Technol Qingdao 266100 Peoples R China Guangxi Univ Nationalities Guangxi Key Lab Hybrid Computat & IC Design Anal Nanning 530006 Peoples R China

As a novel swarm intelligence optimization algorithm, cuckoo search (CS), has been successfully applied to solve various optimization problems. Despite its simplicity and efficiency, the CS is easy to suffer from the premature convergence and fall into local optimum. Although a lot of research has been done on the shortage of CS, learning mechanism has not been used to achieve the balance between exploitation and exploration. Based on this, a differential CS extension with balanced learning namely Cuckoo search algorithm with balanced-learning (O-BLM-CS) is proposed. Two sets, the better fitness set (FSL) and the better diversity set (DSL), are produced in the iterative process. Two excellent individuals are selected from two sets to participate in search process. The search ability is improved by learning their beneficial behaviors. The FSL and DSL learning factors are adaptively adjusted according to the individual at each generation, which improve the global search ability and search accuracy of the algorithm and effectively balance the contradiction between exploitation and exploration. The performance of O-BLM-CS algorithm is evaluated through eighteen benchmark functions with different characteristics and the logistics distribution center location problem. The results show that O-BLM-CS algorithm can achieve better balance between exploitation and exploration than other improved CS algorithms. It has strong competitiveness in solving both continuous and discrete optimization problems. (C) 2021 The Authors. Published by Atlantis Press B.V.

关键词： Cuckoo search algorithm Balanced-learning The better fitness set The better diversity set optimization algorithm

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