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Design optimization for relative bandwidth of left-handed metamaterials with split-ring resonators

JOURNAL OF OPTICS 2011年第1期13卷 015102-015102页

作者： Liu, Shutian Dong, Yanzhang Xu, Weikai Dalian Univ Technol State Key Lab Struct Anal Ind Equipment Dept Engn Mech Dalian 116024 Peoples R China

Due to their special properties, left-handed metamaterials have important potential applications in engineering. When an incident wave propagates through a periodic material with the dimension of its microstructure much smaller than the wavelength, the metamaterial can be regarded as a homogeneous medium, and its effective electromagnetic parameters (permittivity and permeability) in the frequency domain can be obtained with the S-parameters retrieval method. From this perspective, the design of a material with the desired left-handed characteristics becomes possible. By establishing automatic parametric modeling technology, we can study the transmission and reflection properties of left-handed metamaterials with arrays of split-ring resonators. Next, a whole flow chart of design optimization for improving left-handed metamaterial performance is proposed. Finally, the design method is illustrated through a numerical example including the shape and the size design of split-ring resonators to max relative bandwidth, based on parametric analysis of the left-handed relative bandwidths. sequential quadratic programming and enumeration optimization are applied to solve the optimization problem.

关键词： left-handed metamaterials material design relative bandwidth S-parameters retrieval methods sequential quadratic programming split-ring resonators

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Robust Optimization of Nanometer SRAM Designs

Robust Optimization of Nanometer SRAM Designs

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作者： Dayal, Akshit Texas A&M University

Technology scaling has been the most obvious choice of designers and chip manufacturing companies to improve the performance of analog and digital circuits. With the ever shrinking technological node, process variations can no longer be ignored and play a significant role in determining the performance of nanoscaled devices. By choosing a worst case design methodology, circuit designers have been very munificent with the design parameters chosen, often manifesting in pessimistic designs with significant area overheads. Significant work has been done in estimating the impact of intra-die process variations on circuit performance, pertinently, noise margin and standby leakage power, for fixed transistor channel dimensions. However, for an optimal, high yield, SRAM cell design, it is absolutely imperative to analyze the impact of process variations at every design point, especially, since the distribution of process variations is a statistically varying parameter and has an inverse correlation with the area of the MOS transistor. Furthermore, the first order analytical models used for optimization of SRAM memories are not as accurate and the impact of voltage and its inclusion as an input, along with other design parameters, is often ignored. In this thesis, the performance parameters of a nano-scaled 6-T SRAM cell are modeled as an accurate, yield aware, empirical polynomial predictor, in the presence of intra-die process variations. The estimated empirical models are used in a constrained non-linear, robust optimization framework to design an SRAM cell, for a 45 nm CMOS technology, having optimal performance, according to bounds specified for the circuit performance parameters, with the objective of minimizing on-chip area. This statistically aware technique provides a more realistic design methodology to study the trade off between performance parameters of the SRAM. Furthermore, a dual optimization approach is followed by considering SRAM power supply and wordline

关键词： SRAM Static Noise Margin Leakage Power Response Surface Modeling Dynamic noise Margin Non Linear programming Access Time sequential quadratic programming Book Thesis

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Solving the hydro unit commitment problem via dual decomposition and sequential quadratic programming

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IEEE TRANSACTIONS ON POWER SYSTEMS 2006年第2期21卷 835-844页

作者： Finardi, EC da Silva, EL Univ Fed Santa Catarina BR-88040900 Florianopolis SC Brazil

This paper presents an algorithm that achieves the hydro unit commitment in hydrothermal systems. This problem is difficult to solve since several constraints with continuous and discrete variables exist, including hydraulic coupling, storage and released flow limits of the reservoirs, and unit forbidden operation zones. The forbidden zones cause a noncontinuous operation of the generating units, making the solution of the problem more difficult, due to the associated combinatorial nature. Moreover, there exists the presence of nonlinear functions that represent the tailrace level, the hydraulic losses, and the unit efficiency. To solve a problem that contains all of these characteristics is a challenging task. Within this scenario, an algorithm is presented that makes use of Lagrangian relaxation, in which some variables are artificially duplicated in order to separate the problem into simpler subproblems. The idea is to relax the spatial and temporal coupling present in the constraints associated with the forbidden zones. In order to solve the subproblems of nonlinear continuous nature that result from the relaxation, this paper presents a sequential quadratic programming algorithm. To update the Lagrange multipliers, an algorithm based on the Bundle Method is used. We assess our approach on a real-life hydroelectric configuration, proving the conceptual and practical feasibility of the proposed algorithm.

关键词： hydrothermal systems hydro unit commitment Lagrangian relaxation sequential quadratic programming

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An active set sequential quadratic programming algorithm for nonlinear optimisation

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BULLETIN OF THE AUSTRALIAN MATHEMATICAL SOCIETY 2006年第1期74卷 69-83页

作者： Hu, Qing-Jie Xiao, Yun-Hai Chen, Y. Hunan Univ Inst Appl Math Changsha 410082 Peoples R China Hunan Business Coll Dept Informat Changsha 410205 Peoples R China

In this paper, we have proposed an active set feasible sequential quadratic programming algorithm for nonlinear inequality constraints optimization problems. At each iteration of the proposed algorithm, a feasible direction of descent is obtained by solving a reduced quadratic programming subproblem. To overcome the Maratos effect, a higher-order correction direction is obtained by solving a reduced least square problem. The algorithm is proved to be globally convergent and superlinearly convergent under some mild conditions without strict complementarity.

关键词： sequential quadratic programming Least squares method higher-order algorithms quadratic programming Complementarity descent iterative methods inequality constraint

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A Gait Generation Method for the Compass-type Biped Robot on Slopes via Discrete Mechanics

A Gait Generation Method for the Compass-type Biped Robot on...

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IEEE Conference on Decision and Control

作者： Tatsuya Kai Takeshi Shintani Faculty of Information Science and Electrical Engineering Kyushu University JAPAN Kyocera Corporation JAPAN

ISBN: (纸本)9781612848006

In this paper, we develop a discrete mechanics approach to gait generation on slopes for the compass-type biped robot. We formulate a optimal gait generation problem for the discrete compass-type robot and show a solving method of it by the sequential quadratic programming to calculate a discrete control input. Then, we propose a transformation method from a discrete control input into a continuous zero-order hold input based on discrete Lagrange-d'Alembert principle. As a result of numerical simulations, it is confirmed that stable gaits on both downward and upward slopes can be generated for the continuous compass-type robot by the proposed method.

关键词： biped robot control input Gait Locomotion discrete element sequential quadratic programming Robot mechanic Mechanics

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Identification of linear systems using output measurements with only two possible values

Identification of linear systems using output measurements w...

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IEEE Conference on Decision and Control

作者： Bruno Depraetere Gregory Pinte Jan Swevers PMA Faculty of Mechanical Engineering Katholieke Universiteit Leuven Celestijnenlaan 300 B B-3001 Leuven Belgium Flanders Mechatronics Technology Centre (FMTC) Celestijnenlaan 300 D B-3001 Leuven Belgium

ISBN: (纸本)9781612848006

Classical identification cannot be applied when no output measurements are available. In many situations however, discrete information on the unmeasured outputs can still be obtained and used to identify the underlying dynamics. An example is a moving object where an optical sensor can detect whether or not is in the sensors line of sight but whose position is not measured. Using these discrete data sources to estimate a model for the underlying dynamics is equivalent to the estimation of the linear parameters of a Wiener system, which has a known but non-invertible static non-linearity with two output levels. Techniques are derived to perform this estimation, using sequential quadratic programming to minimize a least squares goal function. Simulations are used to validate the proposed approach, yielding good convergence of the linear model parameters to their targets and a high prediction accuracy for the unmeasured variable of the Wiener system.

关键词： identification wiener model gauss-newton least squares sequential quadratic programming discrete sensor data linear model estimation

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A Modified Penalty-free-type Nonmonotone SQP Method

A Modified Penalty-free-type Nonmonotone SQP Method

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The Fourth International Joint Conference on Computational Science and Optimization(第四届计算科学与优化国际大会 CSO 2011)

作者： KeSu College of Mathematics and Computer Science Hebei University Baoding 071002 P.R.China

A modified penalty-free-type nonmonotone SQP method for inequality constrained optimization is proposed in this paper. This algorithm has no need on the penalty function and allows nonmonotonic decrease for the constrained violation function. Comparing with the filter-based approaches, our method leads to more flexibility. Under some reasonable conditions, the global convergence properties of our algorithm is presented. Moreover, some numerical results are given.

关键词： sequential quadratic programming Nonmono-tone Global convergence

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Target Neighbor Consistent Feature Weighting for Nearest Neighbor Classification 11

Target Neighbor Consistent Feature Weighting for Nearest Nei...

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Annual Conference on Neural Information Processing Systems

作者： Ichiro Takeuchi Masashi Sugiyama Department of Engineering Nagoya Institute of Technology Department of Computer Science Tokyo Institute of Technology

ISBN: (纸本)9781618395993

We consider feature selection and weighting for nearest neighbor classifiers. A technical challenge in this scenario is how to cope with discrete update of nearest neighbors when the feature space metric is changed during the learning process. This issue, called the target neighbor change, was not properly addressed in the existing feature weighting and metric learning literature. In this paper, we propose a novel feature weighting algorithm that can exactly and efficiently keep track of the correct target neighbors via sequential quadratic programming. To the best of our knowledge, this is the first algorithm that guarantees the consistency between target neighbors and the feature space metric. We further show that the proposed algorithm can be naturally combined with regularization path tracking, allowing computationally efficient selection of the regularization parameter. We demonstrate the effectiveness of the proposed algorithm through experiments.

关键词： Nearest neighbor Eigenvector Neighbor sequential quadratic programming algorithms Feature extraction

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Design of optimal sampling times for pharmacokinetic trials via spline approximation

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TURKISH JOURNAL OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCES 2010年第6期18卷 1019-1030页

作者： Asyali, Musa Hakan Zirve Univ Dept Elect & Elect Engn TR-27260 Kizilhisar Gaziantep Turkey

Understanding and comparison of different drug delivery formulations are based on pharmacokinetic parameters (PKP) such as area under curve, maximum concentration, and time to reach maximum concentration. Accurate estimation of PKP is of critical importance in capturing drug absorption and elimination characteristics and in reaching bioequivalence decisions. Since PKP are estimated from a limited number of samples, the timing of the samples directly influences the accuracy of estimation. Optimization of the sampling times may not only increase the accuracy of PKP estimation, but also reduce the number of samples to be drawn, which in turn lessens the inconvenience to the subjects and the cost of the study. In this study, as an alternative to conventional piece-wise linear approximation, we proposed cubic spline approximation to the time-concentration curve and also introduced a global optimality criterion that focuses on the closeness of all the pharmacokinetic parameter estimators to their true values simultaneously. By minimizing the criterion function over sampling times and watching the regulatory practice/guidance for sample collection, we designed optimal sampling times that can be used in pharmacokinetic studies. We demonstrated that using our approach it is possible to obtain more accurate estimates of PKP with fewer samples.

关键词： Pharmacokinetic parameters optimal sampling time design spline approximation sequential quadratic programming

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Optimization of System Parameters for Liquid Rocket Engines with Gas-Generator Cycles

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JOURNAL OF PROPULSION AND POWER 2010年第1期26卷 113-119页

作者： Cai, Guobiao Fang, Jie Zheng, Yuntao Tong, Xiaoyan Chen, Jun Wang, Jue Beijing Univ Aeronaut & Astronaut Sch Astronaut Beijing 100191 Peoples R China Beijing Aerosp Prop Inst Beijing 100076 Peoples R China

System design of liquid rocket engines must consider engine performance, weight, cost, and reliability requirements. A general design optimization framework has been developed in this paper to select the best system parameters for liquid rocket engines with gas-generator cycles. The object is to maximize the specific impulse and vacuum thrust-to-weight ratio of the engine with given system requirements and design assumptions by changing thrust-chamber pressure and mixture ratio. The system analysis, along with the engine weight estimation, is based on a modular scheme. Multidisciplinary design optimization formulations including multidisciplinary feasible and collaborative optimization are used, evaluated, and compared during the optimization process. Several techniques of multi-objective processing are also used to identify the Pareto frontier and the optimal compromise solutions. A proposed cryogenic-propellant engine using liquid oxygen and hydrogen with a gas-generator cycle is studied as a specific example. Moreover, uncertainties in the engine operation, such as thrust-chamber pressure and mixture ratio, are taken into account as random variables in the reliability-based optimization. Results are presented to illustrate the tradeoff between the engine performance and reliability requirements.

关键词： Combustion Products Liquid Rocket Engine Chamber Pressure Thrust to Weight Ratio Pareto Frontier MDO Cryogenic Propellants Rocket Engine sequential quadratic programming Mass Flow Rate

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