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6th Conference on Advances in Control and Optimization of Dynamical Systems (ACODS)

作者： Mohamed, Majeed Joy, Nidhin CSIR Natl Aerosp Labs Flight Mech & Control Div Bangalore 560017 Karnataka India Coll Engn Trivandrum Trivandrum Kerala India

The estimation of accurate values of aircraft flow angles namely angle of attack (AOA) and angle of sideslip (AOSS) is a crucial step in the safe flight operation and aircraft modeling. The airdata measurement is solely dependent on the data from sensors installed on aircraft, and such sensor data is prone to errors due to flow distortion at aircraft body and sensor misalignment. Further, the online estimation of airdata measurement is more cost-effective and is of more relevance in autonomous flight applications. This work focuses on the online estimate of aircraft flow angles in the presence of atmospheric turbulence using an adaptive sequential estimation algorithm. The proposed estimator has the potential to accurately estimate the AOA and AOSS even in the adverse effect of external disturbance like atmospheric turbulence. (C) 2020, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Extended Kalman filter adaptive algorithm noise covariance matrix state estimation atmospheric turbulence

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Pilot Assisted Channel Assessment for MIMO-OFDM over Dispersive Fading Channels

Pilot Assisted Channel Assessment for MIMO-OFDM over Dispers...

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2020 International Conference on Futuristic Technologies in Control Systems and Renewable Energy, ICFCR 2020

作者： Jose, Jobi Kuriakose, Anu K Ilahia College of Engineering and Technology Ernakulam Electronics and Communication Engineering Kerala India Federal Institute of Science and Technology Ernakulam Electronics and Communication Engineering Kerala India

ISBN: (纸本)9781728188935

The mobile network is the most establishing communication technology nowadays, In order to support its high speed data rate in real time process it often use adaptive algorithms. But in fact, the performance of frequency selective fading channels are not effective while enduring adaptive algorithms. In this suggested method, a better channel assessment is implemented for frequency selective fading channels with an adaptive synchronization algorithm. A correlation factor is introduced to minimize the ISI (intersymbol interference) with the calculation of coarse channel length. In this suggested paper, a mixed form of blind and data aided method are used for channel assessment. The simulation results shows that the implemented channel assessment method is highly accurate with grater tracking speed and lower calculation complexity compared to the existing adaptive algorithms. Where, the previous studies never focused on a specific channel model than its parameters of interest. The theory and results are mentioned and discussed in the paper. © 2020 IEEE.

关键词： adaptive algorithm Channel Estimation Multiple Input Multiple Output (MIMO) OFDM Rayleigh fading

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Decision Tree-Based adaptive Reconfigurable Cache Scheme

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algorithmS 2021年第6期14卷 176页

作者： Zhu, Wei Zeng, Xiaoyang Fudan Univ State Key Lab ASIC & Syst Shanghai 201203 Peoples R China

Applications have different preferences for caches, sometimes even within the different running phases. Caches with fixed parameters may compromise the performance of a system. To solve this problem, we propose a real-time adaptive reconfigurable cache based on the decision tree algorithm, which can optimize the average memory access time of cache without modifying the cache coherent protocol. By monitoring the application running state, the cache associativity is periodically tuned to the optimal cache associativity, which is determined by the decision tree model. This paper implements the proposed decision tree-based adaptive reconfigurable cache in the GEM5 simulator and designs the key modules using Verilog HDL. The simulation results show that the proposed decision tree-based adaptive reconfigurable cache reduces the average memory access time compared with other adaptive algorithms.

关键词： decision tree adaptive algorithm reconfigurable cache multicore processor

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Recursive Maximum Correntropy Learning algorithm With adaptive Kernel Size

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS 2018年第7期65卷 958-962页

作者： Hamid, Radmanesh Hajiabadi, Mojtaba Shahid Sattari Aeronaut Univ Sci & Technol Dept Elect Engn Tehran *** Iran Ferdowsi Univ Mashhad Dept Elect Engn Mashhad *** Iran

In this brief, a robust correntropy-based adaptive learning algorithm, called the adaptive kernel recursive maximum correntropy criterion, is proposed by considering an adaptive kernel size based on the Kullback-Leibler divergence minimization. Simulation results confirm that the proposed algorithm can perform better than other adaptive algorithms especially when the environment is disturbed by non-Gaussian noises. The proposed algorithm is beneficial for using in helicopters, since the pilot speech signal is contaminated by the acoustic impulsive noises that are originated from rotor blades.

关键词： adaptive algorithm correntropy criterion non-Gaussian noise adaptive kernel size

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Mechanical engineering design optimisation using novel adaptive differential evolution algorithm

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INTERNATIONAL JOURNAL OF VEHICLE DESIGN 2019年第2-4期80卷 285-329页

作者： Abderazek, Hammoudi Yildiz, Ali Riza Sait, Sadiq M. Setif 1 Univ Appl Precis Mech Lab Inst Opt & Precis Mech Setif 19000 Algeria Bursa Uludag Univ Dept Automot Engn TR-16059 Bursa Turkey King Fahd Univ Petr & Minerals Comp Engn Dept Dhahran 31261 Saudi Arabia

This paper introduces a new adaptive mixed differential evolution (NAMDE) algorithm for mechanical design optimisation problems. The algorithm uses a self-adaptive mechanism to update the values of mutation and crossover factors. Moreover, elitism is used where the best-found individual in each generation is retained. The performance of NAMDE is evaluated by solving 11 well-known constrained mechanical design problems and two industrial applications. Further, comparison results between NAMDE and other recently published methods, for the first problems, clearly illustrate that the proposed approach is an important alternative to solve current real-world optimisation problems. Besides this, new optimal solutions for some engineering problems are obtained and reported in this paper. For the coupling with a bolted rim problem, the objective function improved by 10%. Whereas for the spur minimisation problem, the final design provides a reduction in gearing mass by 7.5% compared to those published in previous works.

关键词： differential evolution algorithm adaptive parameter control engineering design optimisation constrained optimisation problems DE metaheuristics adaptive algorithm

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Development of an adaptive multi-method algorithm for automatic picking of first arrival times: application to near surface seismic data

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NEAR SURFACE GEOPHYSICS 2018年第5期16卷 507-526页

作者： Khalaf, Amin Camerlynck, Christian Florsch, Nicolas Schneider, Ana Sorbonne Univ EPHE Milieux Environm Transferts & Interact Hydrosyst F-75005 Paris France Tishreen Univ Dept Geol Fac Sci Latakia Syria Sorbonne Univ IDR UMI UMMISCO 209 F-75005 Paris France

Accurate picking of first-arrival times is important in many seismic studies, particularly in seismic tomography and reservoirs or aquifers monitoring. Many techniques have been developed, mainly for seismological purposes, in order to pick first arrivals automatically or semi-automatically. However, these techniques do not reach the accuracy required in shallow seismics due to the complexity of near-surface structures and low signal-to-noise ratio. We propose here a new adaptive algorithm to automatically pick first arrival in near-surface seismic data by combining three picking methods: multi-nested windows, higher order statistics, and Akaike information criterion. They benefit from combining different properties of the signal in order to highlight first arrivals and finally to provide an efficient and robust automatic picking. This strategy mimics the human first-break picking, where a global trend is first defined at the beginning of the picking procedure. The exact first breaks are then sought in the vicinity of each point suggested by this trend. Three successive phases are combined in a multistage algorithm, each of them characterizing a specific signal property. Within each phase, the potential picks and their error range are automatically assessed and sequentially used as prior constraints in the following phase picking. Since having realistic estimates of the error in picked traveltimes is crucial for seismic tomography, our adaptive algorithm automatically provides picked arrival times with their associated uncertainties. We demonstrate the accuracy and robustness of the implemented algorithm using synthetic, pseudo-synthetic and real datasets that pose challenges to classical automatic pickers. A comparison of both manual and adaptive picking procedures demonstrates that our new scheme provides more reliable results even under different noisy conditions. All parameters of our multi-method algorithm are self-adaptive, thanks to the sequential integration

关键词： Automatic picking adaptive algorithm Multi-nested window Kurtosis Akaike Information Criterion Seismic tomography Look-like Monte Carlo

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Fault Diagnosis algorithm Based on Adjustable Nonlinear PI State Observer and Its Application in UAV Fault Diagnosis

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algorithmS 2021年第4期14卷 119页

作者： Miao, Qing Wei, Juhui Wang, Jiongqi Chen, Yuyun Foshan Univ Sch Math & Big Data Foshan 528225 Peoples R China Natl Univ Def Technol Coll Liberal Arts & Sci Changsha 410073 Peoples R China Hunan Inst Traff Engn Hitech Res Inst Hengyang 421099 Peoples R China

Aiming at the problem of fault diagnosis in continuous time systems, a kind of fault diagnosis algorithm based on adaptive nonlinear proportional integral (PI) observer, which can realize the effective fault identification, is studied in this paper. Firstly, the stability and stability conditions of fault diagnosis method based on the PI observer are analyzed, and the upper bound of the fault estimation error is given. Secondly, the fault diagnosis algorithm based on adjustable nonlinear PI observer is designed and constructed, it is analyzed and we proved that the upper bound of fault estimation under this algorithm is better than that of the traditional method. Finally, the L-1011 unmanned aerial vehicle (UAV) is taken as the experimental object for numerical simulation, and the fault diagnosis method based on adaptive observer factor achieves faster response speed and more accurate fault identification results.

关键词： fault diagnosis nonlinear observer adaptive algorithm UAV parameter estimation

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Design of Thermostatic Mixing VALVE based on STM32

Design of Thermostatic Mixing VALVE based on STM32

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2020 Asia Energy and Electrical Engineering Symposium

作者： Sun, Yongchao Cao, Guanzhong Meng, Pu Yuan, Han Mei, Ning Gao, Zhiqiang Xie, Tangjian Ocean Univ China Dept Power Engn Qingdao Peoples R China Qingdao Econ & Technol Dev Zone Haier Water Heate Qingdao Peoples R China

ISBN: (纸本)9781728167824

The STM32 series single-chip microcomputer is used as the controller to control the stepping motor through the L9110S motor drive module, thereby affecting the gap of the cone valve. At the same time, the Wheatstone bridge and the amplifier are used to form a differential amplifier circuit to collect the platinum resistance temperature signal. Use adaptive algorithm to ensure the temperature of the water is stable while taking into account the temperature regulation. The cold water inlet is reasonably restricted to make the temperature of the thermostatic valve constant under variable flow conditions.

关键词： single-chipmicrocomputer thermostatic valve stepping motor adaptive algorithm

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Novel adaptive IMEX two-step Runge-Kutta temporal discretization methods for unsteady flows

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Chinese Journal of Aeronautics 2025年

作者： Xueyu QIN Jian YU Xin ZHANG Zhenhua JIANG Chao YAN National Key Laboratory of Computational Fluid Dynamics Beihang University Beijing 100191 China School of Aeronautic Science and Engineering Beihang University Beijing 100191 China

Efficient and accurate simulation of unsteady flow presents a significant challenge that needs to be overcome in computational fluid dynamics (CFD). Temporal discretization method plays a crucial role in the simulation of unsteady flows. To enhance computational efficiency, we propose the implicit-explicit two-step Runge-Kutta (IMEX-TSRK) time-stepping discretization methods for unsteady flows, and develop a novel adaptive algorithm that correctly partitions spatial regions to apply implicit or explicit methods. The novel adaptive IMEX-TSRK schemes effectively handle the numerical stiffness of the small grid size and improve computational efficiency. Compared to implicit and explicit Runge-Kutta (RK) schemes, the IMEX-TSRK methods achieve the same order of accuracy with fewer first derivative calculations. Numerical case tests demonstrate that the IMEX-TSRK methods maintain numerical stability while enhancing computational efficiency. Specifically, in high Reynolds number flows, the computational efficiency of the IMEX-TSRK methods surpasses that of explicit RK schemes by more than one order of magnitude, and that of implicit RK schemes several times over.

关键词： Implicit-explicit temporal methods Two-step Runge-Kutta methods adaptive algorithm Unsteady flows Navier-Stokes equations

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A New Flame Image Edge Detection algorithm for Reconstruction of the Internal Temperature Field in the Furnace

A New Flame Image Edge Detection Algorithm for Reconstructio...

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第40届中国控制会议

作者： Wang Tao Chen Peng Wang Wei Yusen Gang Deliang Zeng School of Mechanical and Electrical Engineering and Automation Shanghai University School of Control and Computer Engineering North China Electric Power University

For a coal-fired boiler, it is always a difficult problem to reconstruct the internal temperature field. Due to the complex environment inside the furnace, the traditional reconstruction methods are not suitable for the furnace, so the current mainstream methods are based on the characteristics of the furnace internal flame image to reconstruct the temperature field. But the flame image inside the furnace is easily affected by external factors, especially the background. Therefore, it is very important to detect the edge of the flame image and extract the separate flame image for the subsequent temperature field reconstruction. For this purpose, a new edge detection method is proposed in this paper. First, a new rule is designed for color image to gray *** rule can improve the gray difference between flame target and background area. Then the threshold segmentation algorithm is used to preprocess the flame gray image, and a new weighted edge image calculation method is designed to capture more details of the flame edge. Finally, an adaptive double threshold algorithm is used to remove the false edge in the flame edge. The simulation results show that the method is effective and can detect the continuous flame edge very well. It is of great practical value for the temperature field reconstruction in the furnace.

关键词： Flame Image Image Processing Edge Detection adaptive algorithm

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