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IEEE CSAA Guidance, Navigation and Control Conference (CGNCC)

作者： Sun Zhengxiang Chao Tao Wang Songyan Yang Ming Harbin Inst Technol Harbin 150000 Peoples R China

ISBN: (数字)9781538611715

ISBN: (纸本)9781538611715

To solve the non-convex ascent trajectory optimization problem with non-convex dynamic equations and constraints, a convex optimization method is proposed in this paper. The ascent trajectory optimization problem is formulated by giving the ascent dynamic equations and analyzing constraint conditions, which is discretized into a nonlinear programming problem by trapezoidal integration. Then convex methods are researched on discrete constraints and dynamic equations, and an iterative algorithm is proposed based on narrowing trust region constraint. Simulation result proves that the method is faster and more accurate than the pseudo spectral method, and its low requirement of initial value and suitability for the change of terminal state in large range highly improve the efficiency of the ascent optimization.

关键词： ascent optimization convex method trust region iteration algorithm

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Hybrid Sparsity Model for Fast Terahertz Imaging

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MICROMACHINES 2021年第10期12卷 1181-1181页

作者： Ren, Xiaozhen Bai, Yanwen Jiang, Yuying Henan Univ Technol Sch Artificial Intelligence & Big Data Zhengzhou 450001 Peoples R China Henan Univ Technol Coll Informat Sci & Engn Zhengzhou 450001 Peoples R China Henan Univ Technol Key Lab Grain Informat Proc & Control Minist Educ Zhengzhou 450001 Peoples R China

In order to shorten the long-term image acquisition time of the terahertz time domain spectroscopy imaging system while ensuring the imaging quality, a hybrid sparsity model (HSM) is proposed for fast terahertz imaging in this paper, which incorporates both intrinsic sparsity prior and nonlocal self-similarity constraints in a unified statistical model. In HSM, a weighted exponentiation shift-invariant wavelet transform is introduced to enhance the sparsity of the terahertz image. Simultaneously, the nonlocal self-similarity by means of the three-dimensional sparsity in the transform domain is exploited to ensure high-quality terahertz image reconstruction. Finally, a new split Bregman-based iteration algorithm is developed to solve the terahertz imaging model more efficiently. Experiments are presented to verify the effectiveness of the proposed approach.

关键词： terahertz imaging sparsity prior nonlocal self-similarity hybrid sparsity model iteration algorithm

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Discrete approximate optimal vibration control for nonlinear vehicle active suspension

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JOURNAL OF VIBROENGINEERING 2017年第2期19卷 1287-1300页

作者： Han, Shi-Yuan Zhong, Xiao-Fang Chen, Yue-Hui Tang, Gong-You Univ Jinan Sch Informat Sci & Engn Jinan 250022 Peoples R China Shandong Womens Univ Sch Informat Technol Jinan 250300 Peoples R China Ocean Univ China Sch Informat Sci & Engn Qingdao Peoples R China

This paper presents the approximate optimal vibration control methodology for discrete nonlinear vehicle active suspension subject to persistent road disturbances. Based on a dynamic model of nonlinear vehicle active suspension and a linear exogenous system model of the persistent road disturbances, a nonlinear two-point boundary value (TPBV) problem is introduced. By introducing a sensitive parameter, the original TPBV problem is reformed as a series of TPBV problems without nonlinear items. A discrete approximate optimal vibration controller (DAOVC) can be obtained by solving a Riccati equation, Stein equation, and nonlinear compensation item, respectively. An iteration algorithm is designed to realize the computational realizability of DAOVC based on the control performance. It is demonstrated that the control performance of ride comfort, road holding ability, and suspension deflection under the DAOVC are much smaller than the ones under the classical feedforward and feedback optimal vibration controller (FFOVC) and open-loop vehicle suspension system.

关键词： vehicle active suspension vibration control nonlinear compensation nonlinear control iteration algorithm

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A solution technique for capacitated two-level hierarchical time minimization transportation problem

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COMPUTERS & OPERATIONS RESEARCH 2023年 151卷

作者： Ding, Hui Xie, Fanrong Sichuan Univ Sci & Engn Sch Math & Stat Zigong 643000 Peoples R China Chinese Acad Sci Inst Computat Math & Sci Engn Comp Beijing 100080 Peoples R China Nanchang Univ Dept Math Nanchang 330031 Peoples R China

As a generalization of two-level hierarchical time minimization transportation problem (2HTMTP), capacitated two -level hierarchical time minimization transportation problem (C2HTMTP) is a vital issue due to the route shipping capacity finiteness in reality, and no research report on C2HTMTP is available owing to the intractability. Only 4 approaches with defects are available in the literature to resolve 2HTMTP, and they cannot be applied directly to C2HTMTP although their generalized versions can. In this paper, by creating mathematical model along with auxiliary models and constructing network with lower and upper arc capacities, C2HTMTP is transformed into a collection of searching feasible flow in the constructed network, and consequently 4 iteration algorithms, with two respectively derived from other two by applying binary search, are developed as C2HTMTP's solution method basing feasible flow algorithm. It is proved that the 4 iteration algorithms find C2HTMTP's optimum solution in a polynomial computation time. Because of sufficiently exploiting C2HTMTP's intrinsic network flow structure, the 4 iteration algorithms hold the merits such as no memory overflow, easier implementation on computer, higher computation efficiency, and easier extension to the capacitated multilevel hierarchical time minimization transportation problem with level exceeding two, and successfully overcome the deficiencies of extant solving approaches to 2HTMTP. Computational experiments validate that as compared to extant best solving method for 2HTMTP, the 4 iteration algorithms are robust and efficient C2HTMTP's solution method able to serve as a powerful tool to solve other related complex optimization problems, where in terms of computation time, when applied to solve 2HTMTP, three algorithms vastly outperform (even the worst performing one rivals) extant best solving approach to 2HTMTP, especially when applied to solve C2HTMTP, two fast descent algo-rithms are rivals ranking first

关键词： Transportation Time minimization iteration algorithm Binary search Network with lower and upper arc capacities

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Large margin projection-based multi-metric learning for classification

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KNOWLEDGE-BASED SYSTEMS 2022年 243卷 108481-108481页

作者： Yuan, Chao Yang, Liming China Agr Univ Coll Informat & Elect Engn Beijing 100083 Peoples R China China Agr Univ Coll Sci Beijing 100083 Peoples R China

Metric learning has been a promising technology to improve classification performance, which aims to learn a data-dependent distance metric such that the similarity between samples can be more effectively evaluated. Metric plays a significant role in the description of similarity between samples, however, learning a single distance metric is usually inadequate, especially when dealing with the heterogeneously distributed data. Traditional metric learning only considers a global metric, while the local metric, which is critical for heterogeneous data, is ignored. In this paper, we formulate a novel large margin projection-based multi-metric learning (LMML) for the binary classification of heterogeneous data, which constructs a unified framework based on global metric and local metrics, where two local distance metrics are learned, one for each class, so that the covariance of samples is as small as possible, and the sample of another class is as far away as possible from the mean of the sample. Moreover, a global distance metric is introduced to capture the common structure between the two classes, which requires that the distance metric in each class should be as close as possible to the global one. An efficient iterative algorithm is designed to optimize the LMML. We also conduct some insightful analyses on the computational complexity and the convergence of the proposed algorithm. Experiments are conducted on artificial datasets, UCI benchmark datasets and handwritten digit datasets to evaluate the proposed method. Compared with the state-of-the-art approaches, the experiment results demonstrate the feasibility and effectiveness of the proposed method. (C) 2022 Elsevier B.V. All rights reserved.

关键词： Classification Heterogeneously distributed data Multi-metric learning iteration algorithm

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A Novel Adaptive Differential Privacy algorithm for Empirical Risk Minimization

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ASIA-PACIFIC JOURNAL OF OPERATIONAL RESEARCH 2021年第5期38卷 2140011-2140011页

作者： Zhang, Kaili Zhang, Haibin Zhao, Pengfei Chen, Haibin Beijing Univ Technol Dept Operat Res & Informat Engn Beijing 100124 Peoples R China Beijing Univ Civil Engn & Architecture Sch Civil & Transportat Engn Beijing 102616 Peoples R China Qufu Normal Univ Sch Management Sci Rizhao 276800 Shandong Peoples R China

Privacy-preserving empirical risk minimization model is crucial for the increasingly frequent setting of analyzing personal data, such as medical records, financial records, etc. Due to its advantage of a rigorous mathematical definition, differential privacy has been widely used in privacy protection and has received much attention in recent years of privacy protection. With the advantages of iterative algorithms in solving a variety of problems, like empirical risk minimization, there have been various works in the literature that target differentially private iteration algorithms, especially the adaptive iterative algorithm. However, the solution of the final model parameters is imprecise because of the vast privacy budget spending on the step size search. In this paper, we first proposed a novel adaptive differential privacy algorithm that does not require the privacy budget for step size determination. Then, through the theoretical analyses, we prove that our proposed algorithm satisfies differential privacy, and their solutions achieve sufficient accuracy by infinite steps. Furthermore, numerical analysis is performed based on real-world databases. The results indicate that our proposed algorithm outperforms existing algorithms for model fitting in terms of accuracy.

关键词： Differential privacy empirical risk minimization iteration algorithm

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Estimation of Road Adhesion Coefficient Based on Tire Aligning Torque Distribution

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JOURNAL OF DYNAMIC SYSTEMS MEASUREMENT AND CONTROL-TRANSACTIONS OF THE ASME 2018年第5期140卷 051010-051010页

作者： Ma, Biao Lv, Chen Liu, Yahui Zheng, Minghui Yang, Yiyong Ji, Xuewu China Univ Geosci Sch Engn & Technol Beijing 100083 Peoples R China Tsinghua Univ State Key Lab Automot Safety & Energy Beijing 100084 Peoples R China Univ Calif Berkeley Dept Mech Engn Berkeley CA 94720 USA

Road adhesion coefficient is an important parameter in vehicle active safety control system. Many researchers estimate road adhesion coefficient by total tire self-aligning torque (SAT, also called front-axle aligning torque), which obtains the average road adhesion coefficient of front wheels, thus leading large estimation error. In this paper, a novel estimation of road adhesion coefficient based on single tire SAT, which is obtained by tire aligning torque distribution, is brought forward. Due to the use of SAT, the proposed estimation method is available in steering only condition. The main idea of the proposed method is that road adhesion coefficient is estimated by single tire SAT instead of total tire SAT. The single tire SAT is closer to real tire torque state, and it can be obtained by aligning torque distribution, which makes use of the ratio for the aligning torque of front-left wheel and front-right wheel. Tire sideslip angle used in torque distribution is estimated by unscented Kalman filter (UKF). Two coefficients, including front-left and front-right tire-road friction coefficients, are estimated by iteration algorithm form single tire SAT. The final road adhesion coefficient is determined by a coefficient identification rule, which is designed to determine which tire-road friction coefficient as the final road adhesion coefficient. Both simulations and tests that use gyroscope/lateral accelerometer/global position system (GPS)/strain gauge are conducted, to validate the proposed methodology that can provide accurate road adhesion coefficient to vehicle active safety control.

关键词： road adhesion coefficient estimation self-aligning torque tire aligning torque distribution UKF iteration algorithm

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Multistage decomposition algorithm for blind source separation

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自然科学进展(英文版) 2002年第5期12卷 378-282页

作者： Feng Dazheng BAO Zheng ZHANG Xianda Key Laboratory for Radar Signal Processing Xidian University Xi'an 710071 China

A new algorithm for blind source separation is proposed, which only extracts the single independent component at each stage. The single independent component is acquired by an iterative algorithm for searching for the optimal solution of the defined cost function. Moreover, all the independent components are obtained by systematic multistage decomposition and multistage reconstruction. When there is spatially colored noise, the performance of this algorithm is advantageous over jointly approximated diagonalization of eigen-matrices (JADE). Simulated results show that if the number of source signals is more than 25, its computational complexity is lower than that of JADE.

关键词： blind source separation multistage decomposition multistage reconstruction criterion iteration algorithm

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An Indoor UWB 3D Positioning Method for Coplanar Base Stations

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SENSORS 2022年第24期22卷 9634-9634页

作者： Zhou, Ning Si, Minghao Li, Dehai Seow, Chee Kiat Mi, Jinzhong Chinese Acad Surveying & Mapping Beijing 100036 Peoples R China China Univ Min & Technol Sch Environm Sci & Spatial Informat Xuzhou 221116 Peoples R China Univ Glasgow Sch Comp Sci Sir Alwyn Williams Bldg Glasgow G128RZ Scotland

As an indispensable type of information, location data are used in various industries. Ultrawideband (UWB) technology has been used for indoor location estimation due to its excellent ranging performance. However, the accuracy of the location estimation results is heavily affected by the deployment of base stations;in particular, the base station deployment space is limited in certain scenarios. In underground mines, base stations must be placed on the roof to ensure signal coverage, which is almost coplanar in nature. Existing indoor positioning solutions suffer from both difficulties in the correct convergence of results and poor positioning accuracy under coplanar base-station conditions. To correctly estimate position in coplanar base-station scenarios, this paper proposes a novel iterative method. Based on the Newton iteration method, a selection range for the initial value and iterative convergence control conditions were derived to improve the convergence performance of the algorithm. In this paper, we mathematically analyze the impact of the localization solution for coplanar base stations and derive the expression for the localization accuracy performance. The proposed method demonstrated a positioning accuracy of 5 cm in the experimental campaign for the comparative analysis, with the multi-epoch observation results being stable within 10 cm. Furthermore, it was found that, when base stations are coplanar, the test point accuracy can be improved by an average of 63.54% compared to the conventional positioning algorithm. In the base-station coplanar deployment scenario, the upper bound of the CDF convergence in the proposed method outperformed the conventional positioning algorithm by about 30%.

关键词： UWB indoor location iteration algorithm coplanar base station

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A CCBM-based generalized GKB iterative regularization algorithm for inverse Cauchy problems

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JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS 2023年第1期432卷

作者： Gong, Rongfang Wang, Min Huang, Qin Zhang, Ye Nanjing Univ Aeronaut & Astronaut Sch Math Nanjing 211106 Peoples R China MIIT Key Lab Math Modelling & High Performance Comp Air Nanjing 211106 Peoples R China Beijing Inst Technol Sch Math & Stat Beijing 100081 Peoples R China Shenzhen MSU BIT Univ Shenzhen 518172 Peoples R China

This paper examines inverse Cauchy problems that are governed by a kind of elliptic partial differential equation. The inverse problems involve recovering the missing data on an inaccessible boundary from the measured data on an accessible boundary, which is severely ill-posed. By using the coupled complex boundary method (CCBM), which integrates both Dirichlet and Neumann data into a single Robin boundary condition, we reformulate the underlying problem into an operator equation. Based on this new formulation, we study the solution existence issue of the reduced problem with noisy data. A Golub-Kahan bidiagonalization (GKB) process together with Givens rotation is employed for iteratively solving the proposed operator equation. The regularizing property of the developed method, called CCBM-GKB, and its convergence rate results are proved under a posteriori stopping rule. Finally, a linear finite element method is used for the numerical realization of CCBM-GKB. Various numerical experiments demonstrate that CCBM-GKB is a kind of accelerated iterative regularization method, as it is much faster than the classic Landweber method.(c) 2023 Elsevier B.V. All rights reserved.

关键词： Cauchy problem Inverse problems Regularization iteration algorithm Golub-Kahan bidiagonalization Givens rotation

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