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40th Chinese Control Conference (CCC)

作者： Xu Lubing Ye Yangfei Yi Yang Zheng Weixing Jiangsu Aviat Tech Coll Zhenjiang 212134 Jiangsu Peoples R China Yangzhou Univ Coll Informat Engn Yangzhou 225127 Jiangsu Peoples R China Univ Western Sydney Sch Comp Engn & Math Sydney NSW 2751 Australia

ISBN: (纸本)9789881563804

In this paper, a disturbance observer based (DOB) anti-disturbance dynamical tracking control is discussed for unmanned aerial vehicles (UAVs) with unknown disturbances. The designed DOBC algorithm is combined with the T-S fuzzy disturbance models so as to achieve the track of the velocity and the pitching angle of UAVs. On one hand, the T-S fuzzy models are employed to describe the unmodeled nonlinear disturbances, in which a DOB on T-S disturbance model is designed to estimate unknown disturbances. On the other hand, a DOB PI-type feedback controller is proposed to ensure the UAV models stability and convergence of the tracking error to zero. Finally, the simulation results further verify the designed DOB algorithm can obtain the satisfactory anti-disturbance and dynamical tracking performance.

关键词： anti-disturbance control UAV models disturbance observer T-S disturbance fuzzy convex optimization algorithm

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Efficient and Fast optimization algorithms for Quantum State Filtering and Estimation 10

Efficient and Fast Optimization Algorithms for Quantum State...

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10th International Conference on Intelligent Control and Information Processing (ICICIP)

作者： Zhang, Kun Cong, Shuang Ding, Jiao Zhang, Jiaojiao Li, Kezhi Univ Sci & Technol China Dept Automat Hefei Peoples R China Chinese Univ Hong Kong Dept Syst Engn & Engn Management Shatin Hong Kong Peoples R China Imperial Coll London Dept Elect & Elect Engn London SW7 2AZ England

ISBN: (纸本)9781728100159

In this paper, based on Alternating Direction Multiplier Method (ADMM) and Compressed Sensing (CS), we develop three types of novel convex optimization algorithms for the quantum state estimation and filtering. Considering sparse state disturbance and measurement noise simultaneously, we propose a quantum state filtering algorithm. At the same time, the quantum state estimation algorithms for either sparse state disturbance or measurement noise are proposed, respectively. Contrast with other algorithms in literature, simulation experiments verify that all three algorithms have low computational complexity, fast convergence speed and high estimation accuracy at lower measurement rates.

关键词： quantum state estimation and filtering Alternating Direction Multiplier Method convex optimization algorithm

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Image reconstruction algorithm based on variable atomic number matching pursuit

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JOURNAL OF algorithmS & COMPUTATIONAL TECHNOLOGY 2017年第2期11卷 103-109页

作者： Zhao, Hongtu Chen, Chong Shi, Chenxu Henan Polytech Univ Coll Phys & Elect Informat Jiaozuo 454000 Peoples R China

As the most critical part of compressive sensing theory, reconstruction algorithm has an impact on the quality and speed of image reconstruction. After studying some existing convex optimization algorithms and greedy algorithms, we find that convex optimization algorithms should possess higher complexity to achieve higher reconstruction quality. Also, fixed atomic numbers used in most greedy algorithms increase the complexity of reconstruction. In this context, we propose a novel algorithm, called variable atomic number matching pursuit, which can improve the accuracy and speed of reconstruction. Simulation results show that variable atomic number matching pursuit is a fast and stable reconstruction algorithm and better than the other reconstruction algorithms under the same conditions.

关键词： Image reconstruction compressive sensing convex optimization algorithm greedy algorithm variable atomic number matching pursuit

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Design method of energy management strategy for range-extended electric buses based on convex optimization 11

Design method of energy management strategy for range-extend...

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11th International Forum on Strategic Technology (IFOST)

作者： Gao, Mingming Du, Jiuyu Harbin Univ Sci & Technol Coll Elect & Elect Engn Beijing Peoples R China Tsinghua Univ State Key Lab Automot Safety & Energy Beijing Peoples R China

ISBN: (纸本)9781509008551

This paper presents an energy management strategy based on convex optimization algorithm for range-extended electric buses (REEB). The convex models of powertrain components are mainly constructed. Moreover, the energy consumption and components energy efficiencies are analyzed based on the energy flow method. The results show that, the fuel consumption of powertrain is 25.99 L/100km, the electrical energy consumption is 26.44 kWh/100km. The energy efficiency of the range extender, electrical power, and powertrain system are 35.04%, 70.13% and 28.30%, respectively. This strategy can be better applied to REEB energy management systems to meet the requirement of powertrain.

关键词： REEB energy management strategy convex optimization algorithm energy efficiency

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Anti-disturbance tracking control for systems with nonlinear disturbances using T-S fuzzy modeling

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NEUROCOMPUTING 2016年 171卷 1027-1037页

作者： Yi, Yang Fan, Xiang Xiang Zhang, Tian Ping Yangzhou Univ Coll Informat Engn Yangzhou 225009 Jiangsu Peoples R China

This paper addresses a novel anti-disturbance dynamical tracking problem for a class of MIMO systems subject to unknown disturbances and nonlinear dynamics. Different from some traditional anti-disturbance results, T-S fuzzy models are firstly employed to describe the nonlinear disturbances, in which a disturbance observer based on T-S exogenous models is designed under different conditions to estimate the unknown nonlinear disturbances for the plants with known and unknown nonlinearities, respectively. By integrating the estimates of disturbance with PI-type control input, a composite controller based on convex optimization theory is proposed to ensure the system stability and convergence of the tracking error to zero. Meanwhile, the favorable disturbance estimation and attenuation performance can also be achieved by the designed convex optimization algorithm. Finally, the effectiveness of the proposed control schemes is verified by simulations for flight control systems with three different types of nonlinear disturbances. (C) 2015 Elsevier B.V. All rights reserved.

关键词： Anti-disturbance control T-S fuzzy models T-S disturbance modeling Disturbance observer (DO) convex optimization algorithm

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On the convergence rate improvement of a primal-dual splitting algorithm for solving monotone inclusion problems

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MATHEMATICAL PROGRAMMING 2015年第2期150卷 251-279页

作者： Bot, Radu Ioan Csetnek, Erno Robert Heinrich, Andre Hendrich, Christopher Univ Vienna Fac Math A-1090 Vienna Austria Tech Univ Chemnitz Dept Math D-09107 Chemnitz Germany

We present two modified versions of the primal-dual splitting algorithm relying on forward-backward splitting proposed in V (Adv Comput Math 38(3):667-681, 2013) for solving monotone inclusion problems. Under strong monotonicity assumptions for some of the operators involved we obtain for the sequences of iterates that approach the solution orders of convergence of and , for , respectively. The investigated primal-dual algorithms are fully decomposable, in the sense that the operators are processed individually at each iteration. We also discuss the modified algorithms in the context of convex optimization problems and present numerical experiments in image processing and pattern recognition in cluster analysis.

关键词： Maximally monotone operator Strongly monotone operator Resolvent Operator splitting Subdifferential Strongly convex function convex optimization algorithm Duality

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A Fast Fixed Point Continuation algorithm with Application to Compressed Sensing

A Fast Fixed Point Continuation Algorithm with Application t...

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2016 6th International Conference on Information Technology for Manufacturing Systems(ITMS 2016)

作者： Qingqing Guo Lei Li School of Science Nanjing University of Posts and Telecommunications

Fixed point continuation(FPC) algorithm is a developed version of convex optimization algorithm,which is an important research method for reconstruction of Compressed Sensing(CS).In this paper,a fast FPC(FFPC) algorithm is proposed to accelerate the convergence speed of FPC *** is introduced into an efficient shifting step,and its current iteration is updated by using special linear combination of two previous *** the accuracy of each iteration is improved,and the convergence speed is *** the numerical experiments,the convergence of FFPC algorithm is proven,the convergence speed of FFPC algorithm is obviously improved compared with the standard FPC algorithm,and the reconstruction quality is better than other algorithms.

关键词： convex optimization algorithm Compressed sensing Fixed point continuation algorithm

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convex optimization of Battery Energy Storage Station in a Micro-grid

Convex Optimization of Battery Energy Storage Station in a M...

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IEEE International Conference on Information and Automation (ICIA)

作者： Zhang, Ruru Li, Yanjie Lou, Yunjiang Harbin Inst Technol Shenzhen Grad Sch Shenzhen Peoples R China

ISBN: (纸本)9781479913343

As the battery energy storage station has the function of improving the fluctuations of power output and regulating system's economic benefit caused by time-of-use pricing, the optimization model of battery energy storage station is proposed to stabilize the power output and to maximize profit of the micro-grid with the known output model of each distributed generator. In order to avoid the disadvantages of dynamic programming algorithm and genetic algorithm, we transform the optimization model to a convex optimization problem and obtain the optimal scheduling policy. Take a specified data in the north area as example, a comparison diagram on power output with and without the use of battery energy storage station shows effectiveness of the model and suitability of using convex optimization algorithm to solve the problem.

关键词： battery energy storage station stable output economic operation convex optimization algorithm

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Tight Semidefinite Relaxation for Combinatorial optimization in UWB Multiuser Detection Systems

Tight Semidefinite Relaxation for Combinatorial Optimization...

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IEEE Vehicular Technology Conference

作者： Chanfei Wang Tiejun Lv Hui Gao Anzhong Hu Key Laboratory of Trustworthy Distributed Computing and Service Ministry of Education School of Information and Communication Engineering Beijing University of Posts and Telecommunications

ISBN: (纸本)9781479944811

In this paper, two near-optimal detectors based on the convex optimization algorithm are proposed for multiuser detection (MUD) in the ultra-wide bandwidth (UWB) systems. The first detector performs semidefinite relaxation (SDR) to approximate the optimum multiuser detection (OMD) which is a nondeterministic polynomial time hard (NP-hard) problem. When the cutting planes generation algorithm is employed to strengthen the relaxation of the SDR, a tight MUD detector for combinatorial optimization is obtained by adding triangle inequalities to the well-known SDR in strict feasible region. Simulations demonstrate that the semidefinite programming (SDP) approaches can provide bit error rate (BER) performance close to the OMD efficiently using the interior point method, and the tight detector provides a better BER performance than the previous detector with a slightly higher complexity.

关键词： combinatorial mathematics computational complexity error statistics mathematical programming multiuser detection relaxation ultra wideband communication BER MUD detector NP-hard problem OMD SDP SDR UWB multiuser detection systems bit error rate combinatorial optimization convex optimization algorithm generation algorithm near-optimal detectors nondeterministic polynomial time hard problem optimum multiuser detection semidefinite programming semidefinite relaxation ultra-wide bandwidth systems Bit error rate Complexity theory Detectors Multiuser detection optimization Programming Vectors Bit error rate Multiuser detection SDPR gene OMD gene combinatorial mathematics Nondeterministic polynomial-time hard Ultra wideband communication Service Discovery Protocol optimization algorithms Complexity theory Programming complexity classes detector relaxation Relaxation

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convex optimization of Battery Energy Storage Station in a Micro-grid

Convex Optimization of Battery Energy Storage Station in a M...

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IEEE International Conference on Information and Automation

作者： Ruru Zhang Yanjie Li Yunjiang Lou Harbin Institute of Technology Shenzhen Graduate School Shenzhen China

ISBN: (纸本)9781479913329

关键词： battery energy storage station stable output economic operation convex optimization algorithm

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