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Robust mismatched filtering algorithm for passive bistatic radar using worst-case performance optimization Research Articles

Gang Chen, Jun Wang,chengang_xidian@163.com,wangjun@xidian.edu.cn

Frontiers of Information Technology & Electronic Engineering 2020, Volume 21, Issue 7,   Pages 963-1118 doi: 10.1631/FITEE.1900150

Abstract: detects targets by exploiting available local broadcasters and communication transmissions as illuminators, which are not designed for radar. The signal usually contains a time-varying structure, which may result in high-level range ambiguity sidelobes. Because the mismatched filter is effective in suppressing sidelobes, it can be used in a . However, due to the in the reference signal, the sidelobe suppression performance seriously degrades in a system. To solve this problem, a novel algorithm is developed using . In this algorithm, the influence of the low energy level in the reference signal is taken into consideration, and a new cost function is built based on . With this optimization, the mismatched filter weights can be obtained by minimizing the total energy of the ambiguity . Quantitative evaluations and simulation results demonstrate that the proposed algorithm can realize sidelobe suppression when there is a low-energy reference signal. Its effectiveness is proved using real data.

Keywords： 外辐射源雷达；距离副峰；低信噪比；失配滤波；最差性能最优    

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Real-Time Assessment and Diagnosis of Process Operating Performance

Shabnam Sedghi,Biao Huang

Engineering 2017, Volume 3, Issue 2,   Pages 214-219 doi: 10.1016/J.ENG.2017.02.004

Abstract:

Over time, the performance of processes may deviate from the initial design due to process variations and uncertainties, making it necessary to develop systematic methods for online optimality assessment based on routine operating process data. Some processes have multiple operating modes caused by the set point change of the critical process variables to achieve different product specifications. On the other hand, the operating region in each operating mode can alter, due to uncertainties. In this paper, we will establish an optimality assessment framework for processes that typically have multi-mode, multi-region operations, as well as transitions between different modes. The kernel density approach for mode detection is adopted and improved for operating mode detection. For online mode detection, the model-based clustering discriminant analysis (MclustDA) approach is incorporated with some a priori knowledge of the system. In addition, multi-modal behavior of steady-state modes is tackled utilizing the mixture probabilistic principal component regression (MPPCR) method, and dynamic principal component regression (DPCR) is used to investigate transitions between different modes. Moreover, a probabilistic causality detection method based on the sequential forward floating search (SFFS) method is introduced for diagnosing poor or non-optimum behavior. Finally, the proposed method is tested on the Tennessee Eastman (TE) benchmark simulation process in order to evaluate its performance.

Keywords： Optimality assessment     Probabilistic principal component regression     Multi-mode    

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A Precision-Positioning Method for a High-Acceleration Low-Load Mechanism Based on Optimal Spatial and Temporal Distribution of Inertial Energy Article

Xin Chen,Youdun Bai,Zhijun Yang,Jian Gao,Gongfa Chen

Engineering 2015, Volume 1, Issue 3,   Pages 391-398 doi: 10.15302/J-ENG-2015063

Abstract:

High-speed and precision positioning are fundamental requirements for high-acceleration low-load mechanisms in integrated circuit (IC) packaging equipment. In this paper, we derive the transient nonlinear dynamicresponse equations of high-acceleration mechanisms, which reveal that stiffness, frequency, damping, and driving frequency are the primary factors. Therefore, we propose a new structural optimization and velocity-planning method for the precision positioning of a high-acceleration mechanism based on optimal spatial and temporal distribution of inertial energy. For structural optimization, we first reviewed the commonly flexible multibody dynamic optimization using equivalent static loads method (ESLM), and then we selected the modified ESLM for optimal spatial distribution of inertial energy; hence, not only the stiffness but also the inertia and frequency of the real modal shapes are considered. For velocity planning, we developed a new velocity-planning method based on nonlinear dynamic-response optimization with varying motion conditions. Our method was verified on a high-acceleration die bonder. The amplitude of residual vibration could be decreased by more than 20% via structural optimization and the positioning time could be reduced by more than 40% via asymmetric variable velocity planning. This method provides an effective theoretical support for the precision positioning of high-acceleration low-load mechanisms.

Keywords： high-acceleration low-load mechanism     precision positioning     spatial and temporal distribution     inertial energy     equivalent static loads method (ESLM)     velocity planning    

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Adaptive Optimization of Correlation-Interval for DopplerSpread Estimation and Its Iterative Implement

Zhang Peng,Bi Guangguo,Cao Xiuying,Yuan Xiaohui

Strategic Study of CAE 2007, Volume 9, Issue 6,   Pages 71-76

Abstract:

In this paper,  at first research of relation between correlation-interval and estimation accuracy is carried out,  and the optimal correlation-interval is proved to be existent that is adaptive to signal-to-noise ratio and velocity varieties. Then some special characteristics of the optimal correlation-interval are explored. Based on them an iterative correlation-interval optimized (CIO) algorithm is proposed.  It optimizes the correlation- interval and calculates the Doppler spread by increasing the resolution on time-domain iteratively.  Simulation results show that contrasted to conventional schemes the proposed approach is less sensitive to signal-to-noise ratio and velocity varieties,  and can improves the performance dramatically in low signal-to-noise ratio environment in which the conventional schemes has a poor performance. It achieves the high accurate estimation of Doppler spread directly.

Keywords： Doppler spread     autocorrelation     optimization     iteration    

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The Optimal Control Model of Reservoir Operations andSolving With Maximum Principle

Fang Qiang,Wang Xianjia, Fang Debin

Strategic Study of CAE 2007, Volume 9, Issue 4,   Pages 55-59

Abstract:

This paper tries to describe the continuous transformation characteristic of reservoir operations with optimal control theory. After constructing the optimal control model of reservoir o perations, the paper presents the necessary condition of optimal control of reservoir operations using maximum principle and analyzes the characteristic and concrete expression of optimal control strategy of reservoir operations in different conditions and environment. At last, an analysis of a numerical example is presented and the results indicate the approach is valid.

Keywords： water conservancy management     optimal control model     maximum principle     reservoiroperations    

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A Multi-Objective Optimal Experimental Design Framework for Enhancing the Efficiency of Online Model Identification Platforms Article

Arun Pankajakshan, Conor Waldron, Marco Quaglio, Asterios Gavriilidis, Federico Galvanin

Engineering 2019, Volume 5, Issue 6,   Pages 1049-1059 doi: 10.1016/j.eng.2019.10.003

Abstract:

Recent advances in automation and digitization enable the close integration of physical devices with their virtual counterparts, facilitating the real-time modeling and optimization of a multitude of processes in an automatic way. The rich and continuously updated data environment provided by such systems makes it possible for decisions to be made over time to drive the process toward optimal targets. In many manufacturing processes, in order to achieve an overall optimal process, the simultaneous assessment of multiple objective functions related to process performance and cost is necessary. In this work, a multiobjective optimal experimental design framework is proposed to enhance the efficiency of online model-identification platforms. The proposed framework permits flexibility in the choice of trade-off experimental design solutions, which are calculated online—that is, during the execution of experiments. The application of this framework to improve the online identification of kinetic models in flow reactors is illustrated using a case study in which a kinetic model is identified for the esterification of benzoic acid and ethanol in a microreactor.

Keywords： Multi-objective optimization     Optimal design of experiments     Online    

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Optimal pricing of perishable goods under strategic consumers

Chen Xiaohong,Yi Guodong and Cheng Lulu

Strategic Study of CAE 2015, Volume 17, Issue 1,   Pages 120-128

Abstract:

With access to information is becoming more and more convenient and quick， the strategic behavior of customers is becoming more common in everyday life. In this paper， we study the optimal pricing of perishable goods in the presence of strategic customers. Monopolist sells a finite quantify of products in a certain period of time. Customers select the optimal time to buy based on the principle of utility maximization. This paper is divided into two scenarios including not replenish inventory and replenish inventory. Studies have shown that the game equilibrium exists between sellers and consumers. After a seller announces the pricing strategy， the structure of customers is divided by an optimal threshold function. The strategic behavior of customers has a significant impact on the profits of a seller. A seller can accord to the market demand and the time sensitivity of customers through proper inventory and price setting to reduce losses from the strategic behavior of customers. The situation with replenishing inventory is better than the situation without replenishing inventory only when market demand is larger.

Keywords： perishable goods； strategic consumers； optimal pricing； Stackelberg game    

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200 km Per Hour一The Best Choice for Beijing - Shanghai Express Railway

Li Yushan

Strategic Study of CAE 2004, Volume 6, Issue 12,   Pages 7-12

Abstract:

This paper, proceeding from China's actual conditions, holds that in the construction of Beijing — Shanghai express railway China should choose “the optimal” instead of “the fastest”. For the long and medium distance the passenger train which “starts at sunset and arrives at daybreak” has the optimal cost performance. The paper maintains that the electrified fast-speed wheel/rail system with a speed of 200 km per hour should be the best choice for China*s railway development. It accords with not only the demands of the development of real socio-economic base of China, which is vast in territory, but also the demands of the future development of China and the world as well. In the time with increasing energy crisis, the maglev train with speed of 400 km per hour and the high-speed rail system with speed of 300 km per hour will lead to the unbearable wastes of socio-economic resources and huge loss in operation.

Keywords： Beijing - Shanghai express railway     optimal choice     maglev     high-speed rail system     fast-speed rail system    

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Optimal Robust Control of AC Position Servo System for Multiple Rockets

Chai Huawei,Ma Dawei,Li Zhigang,Le Guigao,Wang Feng

Strategic Study of CAE 2007, Volume 9, Issue 10,   Pages 83-87

Abstract:

In order to realize high speed and high precision position control in an AC servo system,  in view of such kinds of uncertainties as moment of inertia and load moment changing widely,  and strong impact moment,  an optimal robust control tactics is put forward.  Experimental results show that this control tactics has strong robustness,  and has fairly good dynamic performances and steady-state precision.

Keywords： rocket mortar     AC position servo system     robust control     optimal control    

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Optimization of formation for multi-agent systems based on LQR

Chang-bin Yu, Yin-qiu Wang, Jin-liang Shao,brad.yu@anu.edu.au,wh6508@gmail.com,jinliangshao@126.com

Frontiers of Information Technology & Electronic Engineering 2016, Volume 17, Issue 2,   Pages 96-109 doi: 10.1631/FITEE.1500490

Abstract: In this paper, three optimal linear algorithms are proposed for first-order linear from a perspective with cost functions consisting of both interaction energy cost and individual energy cost, because both the collective object (such as formation or consensus) and the individual goal of each agent are very important for the overall system. First, we propose the optimal formation algorithm for first-order without initial physical couplings. The parameter matrix of the algorithm is the solution to an . It is shown that the matrix is the sum of a Laplacian matrix and a positive definite diagonal matrix. Next, for physically interconnected , the optimal formation algorithm is presented, and the corresponding parameter matrix is given from the solution to a group of quadratic equations with one unknown. Finally, if the communication topology between agents is fixed, the local feedback gain is obtained from the solution to a quadratic equation with one unknown. The equation is derived from the derivative of the cost function with respect to the local feedback gain. Numerical examples are provided to validate the effectiveness of the proposed approaches and to illustrate the geometrical performances of .

Keywords： Linear quadratic regulator (LQR)     Formation control     Algebraic Riccati equation (ARE)     Optimal control     Multi-agent systems    

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Galerkin approximationwith Legendre polynomials for a continuous-time nonlinear optimal control problem Article

Xue-song CHEN

Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 10,   Pages 1479-1487 doi: 10.1631/FITEE.1601101

Abstract: We investigate the use of an approximation method for obtaining near-optimal solutions to a kind of nonlinear continuous-time (CT) system. The approach derived from the Galerkin approximation is used to solve the generalized Hamilton-Jacobi-Bellman (GHJB) equations. The Galerkin approximation with Legendre polynomials (GALP) for GHJB equations has not been applied to nonlinear CT systems. The proposed GALP method solves the GHJB equations in CT systems on some well-defined region of attraction. The integrals that need to be computed are much fewer due to the orthogonal properties of Legendre polynomials, which is a significant advantage of this approach. The stabilization and convergence properties with regard to the iterative variable have been proved. Numerical examples show that the update control laws converge to the optimal control for nonlinear CT systems.

Keywords： Generalized Hamilton-Jacobi-Bellman equation     Nonlinear optimal control     Galerkin approximation     Legendre polynomials    

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Optimal two-impulse space interception with multiple constraints Research Articles

Li Xie, Yi-qun Zhang, Jun-yan Xu,lixie@ncepu.edu.cn,yiqunzhang@hotmail.com,junyan_Xu@sina.cn

Frontiers of Information Technology & Electronic Engineering 2020, Volume 21, Issue 7,   Pages 963-1118 doi: 10.1631/FITEE.1800763

Abstract: We consider optimal two-impulse with . The are imposed on the terminal position of a space interceptor, impulse and impact instants, and the component-wise magnitudes of velocity impulses. These optimization problems are formulated as and solved by the calculus of variations. Slackness variable methods are used to convert all inequality constraints into equality constraints so that the Lagrange multiplier method can be used. A new is presented. As a result, an indirect optimization method is developed. Subsequently, our method is used to solve the two-impulse of free-flight ballistic missiles. A number of conclusions for have been drawn based on highly accurate numerical solutions. Specifically, by numerical examples, we show that when time and velocity impulse constraints are imposed, optimal two-impulse solutions may occur; if two-impulse instants are free, then a two-impulse space interception problem with velocity impulse constraints may degenerate to a one-impulse case.

Keywords： 空间拦截问题；变分法；多约束；两速度脉冲；多点边值问题；局部最优解；动态松弛变量法    

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Robust and accurate optimal transportation map by self-adaptive sampling Research Articles

Yingshi Wang, Xiaopeng Zheng, Wei Chen, Xin Qi, Yuxue Ren, Na Lei, Xianfeng Gu,nalei@dlut.edu.cn,gu@cs.stonybrook.edu

Frontiers of Information Technology & Electronic Engineering 2021, Volume 22, Issue 9,   Pages 1207-1220 doi: 10.1631/FITEE.2000250

Abstract: plays a fundamental role in many fields in engineering and medicine, including surface parameterization in graphics, registration in computer vision, and generative models in deep learning. For quadratic distance cost, map is the gradient of the Brenier potential, which can be obtained by solving the . Furthermore, it is induced to a geometric convex optimization problem. The is highly non-linear, and during the solving process, the intermediate solutions have to be strictly convex. Specifically, the accuracy of the discrete solution heavily depends on the sampling pattern of the target measure. In this work, we propose a algorithm which greatly reduces the sampling bias and improves the accuracy and robustness of the discrete solutions. Experimental results demonstrate the efficiency and efficacy of our method.

Keywords： 最优传输；Monge-Ampère方程；自适应采样    

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Indirect adaptive fuzzy-regulated optimal control for unknown continuous-time nonlinear systems

Haiyun Zhang, Deyuan Meng, Jin Wang, Guodong Lu,gray_sun@zju.edu.cn,tinydreams@126.com,dwjcom@zju.edu.cn,lugd@zju.edu.cn

Frontiers of Information Technology & Electronic Engineering 2021, Volume 22, Issue 2,   Pages 141-286 doi: 10.1631/FITEE.1900610

Abstract: We present a novel indirect adaptive fuzzy-regulated optimal control scheme for continuous-time nonlinear systems with unknown dynamics, mismatches, and disturbances. Initially, the Hamilton-Jacobi-Bellman (HJB) equation associated with its performance function is derived for the original nonlinear systems. Unlike existing adaptive dynamic programming (ADP) approaches, this scheme uses a special non-quadratic variable performance function as the reinforcement medium in the actor-critic architecture. An adaptive structure is correspondingly constructed to configure the weighting matrix of the performance function for the purpose of approximating and balancing the HJB equation. A concurrent self-organizing learning technique is designed to adaptively update the critic weights. Based on this particular critic, an adaptive optimal feedback controller is developed as the actor with a new form of augmented Riccati equation to optimize the fuzzy-regulated variable performance function in real time. The result is an online mechanism implemented as an , which involves continuous-time adaptation of both the optimal cost and the optimal control policy. The convergence and closed-loop stability of the proposed system are proved and guaranteed. Simulation examples and comparisons show the effectiveness and advantages of the proposed method.

Keywords： Indirect adaptive optimal control     Hamilton-Jacobi-Bellman equation     Fuzzy-regulated critic     Adaptive optimal control actor     Actor-critic structure     Unknown nonlinear systems    

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Predicting SARS for Guangdong, Beijing and Mainland China 2003 Cases

Wang Jianfeng

Strategic Study of CAE 2003, Volume 5, Issue 8,   Pages 23-29

Abstract:

The study is aimed at choosing a better predictive model for the accurate description of SARS in Guangdong, Beijing and Mainland China in 2003. Observation and general experience have shown a sigmoid type of curve consisted of four phases comparable to the phases of the SARS growth in 2003 ： an initial lagging period, a period of accelerating change, a period of decelerating change, and a stationary period. In order to model the SARS system, a generalized Logistic growth function has been adopted in the paper. With the officially published data, the main features of evolution of the SARS population size have been obtained using the generalized Logistic growth model by optimizing technique. Then, for getting evolutionary process prediction, several classical S-models such as the Pearl, the Gompertz, Von Bertalanffy, and Richards are tested. The practice of calculations has found that the Gompertz model gives the most accurate results where fitting criteria are estimated as residual sum of squares (RSS).

Keywords： SARS     generalized Logistic growth model     Gompertz function     prediction     optimization    

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Title Author Date Type Operation

Robust mismatched filtering algorithm for passive bistatic radar using worst-case performance optimization

Gang Chen, Jun Wang,chengang_xidian@163.com,wangjun@xidian.edu.cn

Journal Article

Real-Time Assessment and Diagnosis of Process Operating Performance

Shabnam Sedghi,Biao Huang

Journal Article

A Precision-Positioning Method for a High-Acceleration Low-Load Mechanism Based on Optimal Spatial and Temporal Distribution of Inertial Energy

Xin Chen,Youdun Bai,Zhijun Yang,Jian Gao,Gongfa Chen

Journal Article

Adaptive Optimization of Correlation-Interval for DopplerSpread Estimation and Its Iterative Implement

Zhang Peng,Bi Guangguo,Cao Xiuying,Yuan Xiaohui

Journal Article

The Optimal Control Model of Reservoir Operations andSolving With Maximum Principle

Fang Qiang,Wang Xianjia, Fang Debin

Journal Article

A Multi-Objective Optimal Experimental Design Framework for Enhancing the Efficiency of Online Model Identification Platforms

Arun Pankajakshan, Conor Waldron, Marco Quaglio, Asterios Gavriilidis, Federico Galvanin

Journal Article

Optimal pricing of perishable goods under strategic consumers

Chen Xiaohong,Yi Guodong and Cheng Lulu

Journal Article

200 km Per Hour一The Best Choice for Beijing - Shanghai Express Railway

Li Yushan

Journal Article

Optimal Robust Control of AC Position Servo System for Multiple Rockets

Chai Huawei,Ma Dawei,Li Zhigang,Le Guigao,Wang Feng

Journal Article

Optimization of formation for multi-agent systems based on LQR

Chang-bin Yu, Yin-qiu Wang, Jin-liang Shao,brad.yu@anu.edu.au,wh6508@gmail.com,jinliangshao@126.com

Journal Article

Galerkin approximationwith Legendre polynomials for a continuous-time nonlinear optimal control problem

Xue-song CHEN

Journal Article

Optimal two-impulse space interception with multiple constraints

Li Xie, Yi-qun Zhang, Jun-yan Xu,lixie@ncepu.edu.cn,yiqunzhang@hotmail.com,junyan_Xu@sina.cn

Journal Article

Robust and accurate optimal transportation map by self-adaptive sampling

Yingshi Wang, Xiaopeng Zheng, Wei Chen, Xin Qi, Yuxue Ren, Na Lei, Xianfeng Gu,nalei@dlut.edu.cn,gu@cs.stonybrook.edu

Journal Article

Indirect adaptive fuzzy-regulated optimal control for unknown continuous-time nonlinear systems

Haiyun Zhang, Deyuan Meng, Jin Wang, Guodong Lu,gray_sun@zju.edu.cn,tinydreams@126.com,dwjcom@zju.edu.cn,lugd@zju.edu.cn

Journal Article

Predicting SARS for Guangdong, Beijing and Mainland China 2003 Cases

Wang Jianfeng

Journal Article