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Adaptive unit-vector law with time-varying gain for finite-time parameter estimation in LTI systems

APPLIED NUMERICAL MATHEMATICS 2020年 155卷 16-28页

作者： Kapetina, M. N. Pisano, A. Rapaic, M. R. Usai, E. Univ Novi Sad Fac Tech Sci Dept Comp & Control Engn Trg Dositeja Obradovica 6 Novi Sad 21000 Serbia Univ Cagliari Dept Elect & Elect Engn Via Marengo I-09123 Cagliari Italy

A continuation of previous authors' work on adaptive parameter estimation for linear dynamical systems having irrational transfer function is presented in this work. An original modification of the gradient algorithm, inspired by the variable structure control techniques and additionally featuring a time-varying adaptation gain, is presented and analyzed using Lyapunov techniques. The exposition is illustrated by several numerical examples which illustrate the effectiveness of the proposed algorithm. (C) 2019 Published by Elsevier B.V. on behalf of IMACS.

关键词： Adaptive parameter estimation Fractional order systems Distributed parameter systems Delayed systems gradient algorithm Lyapunov stability

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Extreme Learning Machine Under Minimum Information Divergence Criterion

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IEEE ACCESS 2020年 8卷 122026-122035页

作者： Song, Chengtian Pan, Lizhi Liu, Qiang Jiang, Zhihong Jia, Jianguang Beijing Inst Technol Sch Mechatron Engn Beijing 100081 Peoples R China Ordnance Sci Inst China Beijing 100089 Peoples R China PLA AMS Inst Syst Engn Beijing 100091 Peoples R China

In recent years, extreme learning machine (ELM) and its improved algorithms have been successfully applied to various classification and regression tasks. In these algorithms, MSE criterion is commonly used to control training error. However, MSE criterion is not suitable to deal with outliers, which can exist in general regression or classification tasks. In this paper, a novel extreme learning machine under minimum information divergence criterion (ELM-MinID) is proposed to deal with the training set with noises. In minimum information divergence criterion, the Gaussian kernel function and Euclidean information divergence are utilized to substitute the mean square error (MSE) criterion to enhance the anti-noise ability of ELM. Experimental results on two synthetic datasets and eleven benchmark datasets show that this method is superior to traditional ELMs.

关键词： Extreme learning machine minimum information divergence criterion kernel method gradient algorithm

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Optimization of ACE mode transition control schedule considering geometric adjustment speed

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INTERNATIONAL JOURNAL OF TURBO & JET-ENGINES 2022年第0期

作者： Song, Keran Jia, Linyuan Chen, Yuchun Tan, Tian Fan, Peiyang Northwestern Polytech Univ Sch Power & Energy Xian 710072 Peoples R China

Aiming to optimize the mode transition control schedule of the adaptive cycle engine (ACE), an optimization method based on a gradient algorithm was proposed. During the mode transition, the compressor surge margin, the total turbine inlet temperature and the combustion chamber fuel-air ratio are not exceeded. The integration of thrust by time was selected as the optimization objective. The geometric parameters were updated via the optimization target derivative. The speed limit of the geometric adjustment mechanism was also considered in the optimization process. The control schedules of two mode transition processes, from triple to double bypass mode and from double to triple-bypass mode were optimized. The optimization method presented in this paper can be applied to various mode transitions and the geometric adjustment speed meets all the constraints.

关键词： ACE geometric adjustment schedule gradient algorithm mode transition

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Robotic Ad-hoc Networks Connectivity Maintenance based on RF Signal Strength Mapping

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INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS 2022年第2期13卷 9-23页

作者： Ayad, Mustafa Voyles, Richard Ayad, Mohamed SUNY Coll Oswego Elect & Comp Engn Oswego NY 13126 USA Purdue Univ Elect & Comp Engn Technol W Lafayette IN 47907 USA

Network connectivity preservation is one of the substantial factors in achieving efficient mobile robot teams' maneuverability. We present a connectivity maintenance method for a robot team's communication. The proposed approach augments the Radio Frequency Mapping Recognition (RFMR) method and the signal strength gradient decent approach for an overall goal to create a Proactive Motion Control algorithm (PMCA). The PMCA algorithm controls and helps strengthen mobile communicating robots' connectivity in the existent Radio Frequency (RF) obstacles. The RFMR method takes advantage of Hidden Markov Models (HMMs) results, which assist in learning electromagnetic environments depending on measurements of RF signal strength. The classification results of HMM lead the robots to resolve whether to continue the current trajectory for avoiding the obstacle shadow or move back to desirable robust Signal Strength (SS) positions. In both cases, the robot will run the gradient approach to determine the signal change trend and drive the robot toward the strong SS direction for maintaining link connectivity. The PMCA, depending on the results of RFMR and gradient approaches, promises to preserve robots' motion control and link connectivity maintenance.

关键词： RF mapping recognition link connectivity gradient algorithm

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Regression Model-Based Flux Observer for IPMSM Sensorless Control with Wide Speed Range

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ENERGIES 2021年第19期14卷 6249页

作者： Choi, Jongwon Hannam Univ Dept Elect & Elect Engn Daejeon 34430 South Korea

A new linear regression form is derived for a flux observer and a position observer is designed. In general, the observability of the permanent-magnet synchronous motor is lost at zero speed. In this work, the proposed regressor vector contains current derivative terms in both directions (dq-axis), and it gives the chance for the model-based flux observer to operate at zero speed. When an excitation signal is injected into d and q axes with the proposed flux observer, it helps to satisfy the persistent excitation condition in the low-speed range. Therefore, the sensorless performance of the model-based is improved greatly, even at zero speed. However, it appears with a disturbance term, which depends on the derivative of the d-axis current. Thus, the disturbance does not vanish when an excitation signal is injected. In this work, the disturbance term is also taken care of in constructing an observer. It results in an observer which allows signal injection. Thus, high frequency signal can be injected in the low speed region and turned off when it is unnecessary as the speed increases. This model-based approach utilizes the signal injection directly without recurring to a separate high frequency model. In other words, it provides a seamless transition without switching to the other algorithm. The validity is demonstrated by simulation and experimental results under various load conditions near zero speed.

关键词： linear regression form sensorless algorithm IPMSM active flux nonlinear observer gradient algorithm persistence of excitation signal injection

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Collaborative Tracking Systems Using Decentralized Iterative Learning Control 39

Collaborative Tracking Systems Using Decentralized Iterative...

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39th Chinese Control Conference (CCC)

作者： Shen, Dong Liu, Yanze Song, Qijiang Renmin Univ China Sch Math Beijing 100872 Peoples R China Beijing Univ Chem Technol Coll Informat Sci & Technol Beijing 100029 Peoples R China

ISBN: (纸本)9789881563903

This study addresses the collaborative tracking problem for a set of linear systems with noisy measurements using decentralized iterative learning control. The collaborative tracking problem indicates that the desired reference trajectory over a finite time interval is required to be precisely tracked by a combination of the outputs of several independent subsystems. A description of the achievable tracking reference and its corresponding input is elaborated. Two decentralized learning schemes are then provided to solve the collaborative tracking problem iteratively. Numerical simulations are given to verify the derived results.

关键词： Collaborative Tracking Iterative Learning Control gradient algorithm Stochastic Control

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Iterative Optimization-Based ISAR Imaging With Sparse Aperture and Its Application in Interferometric ISAR Imaging

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IEEE SENSORS JOURNAL 2019年第19期19卷 8681-8693页

作者： Rong, Jiajia Wang, Yong Han, Tao Harbin Inst Technol Res Inst Elect Engn Technol Harbin 150001 Heilongjiang Peoples R China

Recently, high-resolution inverse synthetic aperture radar (ISAR) imaging with sparse aperture (SA) data has attracted increasing attention. The theory of compressive sensing (CS) suggests that an unknown sparse signal can be accurately recovered by taking advantage of very limited samples. For ISAR images, the number of the resolution cells occupied by the strong scattering points of the target is usually much smaller than that of the resolution cells of the image plane, revealing the strong sparsity trait of the ISAR signal. This trait of ISAR signal creates the conditions for incorporating CS into high-resolution ISAR imaging. In this paper, a novel iterative optimization-based SA-ISAR imaging approach is proposed. First, the SA-ISAR signal model is established and the envelope alignment is executed on the one-dimensional range profiles of the SA data. Next, the gradient-based algorithm is exploited to recover the complete signals. Then, by iteratively performing the procedures of the envelope alignment and the signal recovery, the accuracy of signal recovery can be significantly improved and a high-quality ISAR image can be obtained. Ultimately, the extension of the iterative optimization-based SA-ISAR imaging to the three-dimensional (3-D) interferometric ISAR (InISAR) imaging is successfully implemented via the traditional ISAR imagery pair interferometric method. The experiments based on the measured and simulated data are carried out to validate the superiority of the novel algorithm.

关键词： ISAR sparse aperture (SA) gradient algorithm interferometric ISAR (InISAR) envelope alignment

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Sensorless Control of IPMSM Based on Regression Model

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IEEE TRANSACTIONS ON POWER ELECTRONICS 2019年第9期34卷 9191-9201页

作者： Choi, Jongwon Nam, Kwanghee Bobtsov, Alexey A. Ortega, Romeo Pohang Univ Sci & Technol Dept Elect Engn Pohang 790784 South Korea ITMO Univ Dept Control Syst & Informat St Petersburg 197101 Russia CNRS SUPELEC Lab Signaux & Syst F-91192 Gif Sur Yvette France

A position-sensorless algorithm is developed for an interior permanent-magnet synchronous motor, while reflecting the saliency in an extended electromotive force term. Active flux is converted into a new linear regression form, and a high-pass filter was applied. Then, the gradient algorithm is applied to derive an estimate of the active flux in the stationary frame. The proposed observer is an inherently sensorless type because it does not require the rotor speed or position information. It is practically attractive since it does not require the use of pure integrator that is marginally stable. In addition, the observer can be constructed without the phase modulation flux linkage constant. It is basically a model-based method. However, it is easily extended to a signal injection method that is robust in the low-speed region. Ultimate boundedness is established using the persistency of excitation condition. Validity of the algorithm is demonstrated experimentally via torque and speed control with a full load in the low-speed range.

关键词： gradient algorithm interior permanent-magnet synchronous motor (IPMSM) linear regression form nonlinear observer persistency of excitation saliency sensorless control signal injection

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Asymptotic Equivalence of Evolution Equations Governed by Cocoercive Operators and Their Forward Discretizations

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JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS 2019年第1期182卷 30-48页

作者： Contreras, Andres Peypouquet, Juan Univ Chile Dept Ingn Matemat FCFM Beauchef 851 Santiago Chile Univ Chile FCFM Dept Ingn Matemat Beauchef 851 Santiago Chile Univ Chile FCFM Ctr Modelamiento Matemat CNRSUMI2807 Beauchef 851 Santiago Chile

The purpose of this work is to study discrete approximations of evolution equations governed by cocoercive operators by means of Euler iterations, both in a finite and in an infinite time horizon. On the one hand, we give precise estimations for the distance between iterates of independently generated Euler sequences and use them to obtain bounds for the distance between the state, given by the continuous-time trajectory, and the discrete approximation obtained by the Euler iterations. On the other hand, we establish the asymptotic equivalence between the continuous- and discrete-time systems, under a sharp hypothesis on the step sizes, which can be removed for operators deriving from a potential. As a consequence, we are able to construct a family of smooth functions for which the trajectories/sequences generated by basic first-order methods converge weakly but not strongly, extending the counterexample of Baillon. Finally, we include a few guidelines to address the problem in smooth Banach spaces.

关键词： Asymptotic equivalence Cocoercive operators Euler iterations gradient algorithm

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Demand-Side Energy Management Considering Price Oscillations for Residential Building Heating and Ventilation Systems

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IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS 2019年第8期15卷 4742-4752页

作者： Ma, Kai Yu, Yangqing Yang, Bin Yang, Jie Yanshan Univ Sch Elect Engn Qinhuangdao 066004 Hebei Peoples R China Xian Univ Architecture & Technol Sch Bldg Serv Sci & Engn Xian 710055 Shaanxi Peoples R China

This paper presents an energy management method to optimally control the energy supply and the temperature settings of distributed heating and ventilation systems for residential buildings. The control model attempts to schedule the supply and demand simultaneously with the purpose of minimizing the total costs. Moreover, the Predicted Percentage of Dissatisfied (PPD) model is introduced into the consumers' cost functions and the quadratic fitting method is applied to simplify the PPD model. An energy management algorithm is developed to seek the optimal temperature settings, the energy supply, and the price. Furthermore, due to the ubiquity of price oscillations in electricity markets, we analyze and examine the effects of price oscillations on the performance of the proposed algorithm. Finally, the theoretical analysis and simulation results both demonstrate that the proposed energy management algorithm with price oscillations can converge to a region around the optimal solution.

关键词： Demand response (DR) energy management gradient algorithm heating and ventilation price oscillations

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