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Optimal fractional order adaptive controllers for AVR applications

ELECTRICAL ENGINEERING 2018年第1期100卷 267-283页

作者： Ortiz-Quisbert, Marco E. Duarte-Mermoud, Manuel A. Milla, Freddy Castro-Linares, Rafael Lefranc, Gaston Univ Chile Dept Elect Engn Ave Tupper 2007 Santiago Chile Univ Chile Adv Min Technol Ctr AMTC Ave Tupper 2007 Santiago Chile IPN CINVESTAV Dept Elect Engn Ave IPN 2508 Mexico City DF Mexico Pontificia Univ Catolica Valparaiso Sch Elect Engn Ave Brasil 2147 Valparaiso Chile

This work presents strategies for fractional order model reference adaptive control (FOMRAC) and fractional order proportional-integral-derivative control (FOPID) applied to an automatic voltage regulator (AVR). The paper focuses on tuning the gains and orders of the FOPID controller and the gains and orders adaptive laws of the FOMRAC controller, with the goal of minimizing non-linear and high dimensionality objective functions, using sequential quadratic programming (SQP), particle swarm optimization (PSO), and genetic algorithms (GA). Two models used for AVR have been studied and reported in the literature and are the bases of the three case studies reported in this paper. To analyze the advantages and disadvantages of the proposed MRAC, comparisons are made with the previous results, i.e. with the results obtained by a PID controller and an MRAC controller optimized by GA. We demonstrate through some performance criteria that fractional order controllers optimized by the PSO algorithm improve the behavior of the controlled system, specifically the robustness with respect to model uncertainties, and improvements with respect to the speed convergence of the signals.

关键词： Fractional order adaptive control Model reference adaptive control Automatic voltage regulator Particle swarm optimization Genetic algorithms sequential quadratic programming

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Computational Design of Microvascular Radiative Cooling Panels for Nanosatellites

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JOURNAL OF THERMOPHYSICS AND HEAT TRANSFER 2018年第3期32卷 605-616页

作者： Tan, Marcus Hwai Yik Bunce, Devin Ghosh, Alexander R. M. Geubelle, Philippe H. Univ Illinois Dept Mech Sci & Engn Urbana IL 61801 USA Univ Illinois Dept Aerosp Engn 306F Talbot Lab104 South Wright St Urbana IL 61801 USA

This novel application of microvascular panels as nanosatellite radiator panels involves the key challenge of satisfying design constraints involving the coolant temperatures and pressure drop across the microchannel network. To address this challenge, the radiator panels are represented by dimensionally reduced hydraulic and nonlinear thermal models. The interface-enriched generalized finite element method and the Newton-Raphson scheme are then combined to solve the resulting nonlinear equations. Next, an interface-enriched generalized finite element method-based sensitivity analysis of the nonlinear equations is developed and combined with an existing sequential quadratic programming algorithm to solve an optimization problem specifically formulated to optimize the thermal performance of the radiator. The resulting thermal performance of the optimized designs is not only superior to that of the reference designs but is also in excellent agreement with an analytical model derived based on the assumption of near-monotonic variation in the coolant temperature along the microchannel network. A feasibility study on a reference design and an optimized design shows that only the latter can satisfy all design constraints with appropriately chosen flow rates. Solutions of the thermal and hydraulic models are also verified with ANSYS FLUENT simulations.

关键词： Coolant Nanosatellite Generalized Finite Element Method Radiator Panel Dirac Delta Function ANSYS FLUENT Thermal Performance sequential quadratic programming Radiative Cooling Thermal Modeling

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On the Global Convergence of a Projective Trust Region Algorithm for Nonlinear Equality Constrained Optimization

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Acta Mathematica Sinica,English Series 2018年第12期34卷 1804-1828页

作者： Yong Gang PEI De Tong ZHU Mathematics and Information Science He 'nan Normal University Xinxiang 453007 P. R. China Mathematics and Science College Shanghai Normal University Shanghai 200234 P. R. China

A trust-region sequential quadratic programming （SQP） method is developed and analyzed for the solution of smooth equality constrained optimization problems. The trust-region SQP algorithm is based on filter line search technique and a composite-step approach, which decomposes the overall step as sum of a vertical step and a horizontal step. The algorithm includes critical modifications of horizontal step computation. One orthogonal projective matrix of the Jacobian of constraint functions is employed in trust-region subproblems. The orthogonal projection gives the null space of the trans- position of the Jacobian of the constraint function. Theoretical analysis shows that the new algorithm retains the global convergence to the first-order critical points under rather general conditions. The preliminary numerical results are reported.

关键词： sequential quadratic programming trust-region filter line search projection global convergence

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Optimal operation of building microgrids - comparison with mixed-integer linear and continuous non-linear programming approaches

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COMPEL-THE INTERNATIONAL JOURNAL FOR COMPUTATION AND MATHEMATICS IN ELECTRICAL AND ELECTRONIC ENGINEERING 2018年第2期37卷 603-616页

作者： Reinbold, Vincent Dinh, Van-Binh Tenfen, Daniel Delinchant, Benoit Saelens, Dirk Katholieke Univ Leuven Leuven Belgium Grenoble Univ Grenoble France Inst Fed Educ Ciencia & Tecnol Santa Catarina Florianopolis SC Brazil Grenoble Univ Grenoble Elect Engn Lab G2Elab Grenoble France

PurposeThis paper aims to present two mathematical models to solve the Energy Management problem of a building microgrid (MG). In particular, it proposes a deterministic mixed integer linear programming (MILP) and non-linear programming (NLP) formulations. This paper focuses on the modelling process and the optimization performances for both approaches regarding optimal operation of near-zero energy buildings connected to an electric MG with a 24-h time horizon. Design/methodology/approachA general architecture of a MG is detailed, involving energy storage systems, distributed generation and a thermal reduced model of the grid-connected building. A continuous non-linear model is detailed along with linearizations for the mixed-integer liner formulation. Multi-physic, non-linear and non-convex phenomena are detailed, such as ventilation and air quality models. FindingsResults show that both approaches are relevant for solving the energy management problem of the building MG. Originality/valueIntroduction and modelling of the thermal loads within the MG. The resulting linear program handles the mutli-objective trade-off between discomfort and the cost of use taking into account air quality criterion. Linearization and modelling of the ventilation system behaviour, which is generally non-linear and non-convex equality constraints, involving air quality model, heat transfer and ventilation power. Comparison of both MILP and NLP methods on a general use case provides a solution that can be interpreted for implementation.

关键词： Microgrid Mixed integer linear programming Optimal operation sequential quadratic programming

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Computational intelligence methodology for the analysis of RC circuit modelled with nonlinear differential order system

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NEURAL COMPUTING & APPLICATIONS 2018年第6期30卷 1905-1924页

作者： Raja, Muhammad Asif Zahoor Mehmood, Ammara Niazi, Shahab Ahmad Shah, Syed Muslim COMSATS Inst Informat Technol Dept Elect Engn Attock Pakistan Islamia Univ Bahawalpur UCE&T Dept Comp Syst Engn Bahawalpur Pakistan Capital Univ Sci & Technol Dept Elect Engn Islamabad Pakistan

In this study, we solve nonlinear initial value problems arising in circuit analysis by applying bio-inspired computational intelligence technique using feed-forward artificial neural networks (ANNs) optimized with genetic algorithms (GAs), sequential quadratic programming (SQP), and their combined scheme. The system of resister-capacitor (RC) circuit having nonlinear capacitance is mathematically modelled with unsupervised ANNs by defining an energy function in mean-square error (MSE) sense. The objectives are to minimize the MSE for which the parameters of the networks are estimated initially with GA-based global search and in steady state with SQP algorithm for efficient local search. We consider a set of scenarios to evaluate the performance of the proposed scheme for different resistance and capacitance values along with current variations in the nonlinear RC circuit system. The results are compared with well-established fully explicit Runge-Kutta numerical solver in order to verify the accuracy of the applied bio-inspired heuristics. To prove the worth of the scheme, a comprehensive statistical analysis is provided for the performance metrics based on root MSE, mean absolute error, Theil's inequality coefficient, Nash-Sutcliffe efficiency, variance account for, and the coefficient of determination (R-2).

关键词： Electric circuits Artificial neural networks Genetic algorithms sequential quadratic programming Hybrid computing

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Attitude Dynamics of Electric Sail from Multibody Perspective

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JOURNAL OF GUIDANCE CONTROL AND DYNAMICS 2018年第12期41卷 2633-2646页

作者： Liu, Fei Hu, Quan Liu, Yufei Beijing Inst Technol Sch Aerosp Engn Beijing 100081 Peoples R China Chinese Acad Space Technol Qian Xuesen Lab Space Technol Beijing 100094 Peoples R China

The electric sail is an innovative propellantless propulsion concept that gains continuous momentum from the solar wind. In this work, the electric sail's attitude dynamics is established from a multibody perspective. Firstly, the dynamics of a single charged tether is described by a dumbbell model. Comparisons with an elastic multipoint model show that the dumbbell model is simpler and accurate enough to describe the motion of tether when the spin rate meets a specific lower bound. Then, the electric sail's attitude dynamics model is established through Kane's method based on the dumbbell model of the tethers. Finally, a case study is performed for the electric sail. It is shown that a 4-kmradius electric sail with 12 tethers of which the voltage is 25 kV could provide the sailcraft with a characteristic acceleration of 0.1 mm/s(2). The results also indicate that the satellite bus's acceleration oscillates with the undiminished out-of-plane swing of the electric sail, in which the period and amplitude are in inverse proportional to the spin rate and its square, respectively. Besides, a dynamical equilibrium point for system's attitude exists when the electric sail is perpendicular to the solar wind. The presented work offers a basic referential model for the real-time feedback control problems of the electric sail's attitude.

关键词： Attitude Stabilization Low Thrust Propulsion Satellite Bus Solar Wind Electron Density Feedback Linearization Electrodynamic Tether Interplanetary Mission Roll Out Solar Array Electric Potential sequential quadratic programming

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Log Polynomial Velocity Profile for Vertical Landing

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JOURNAL OF GUIDANCE CONTROL AND DYNAMICS 2018年第7期41卷 1617-1623页

作者： Gautam, Alvika Ratnoo, Ashwini Sujit, P. B. Indraprastha Inst Informat Technol Delhi Dept Comp Sci Engn Delhi 110020 India Indian Inst Sci Dept Aerosp Engn Bangalore 560012 Karnataka India Indraprastha Inst Informat Technol Delhi Dept Elect & Commun Engn New Delhi 110020 India Loughborough Univ Aeronaut & Automot Engn Epinal Way Loughborough LE11 3TU Leics England

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A multi-stage optimization technique for simultaneous reconstruction of infrared optical and thermophysical parameters in semitransparent media

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INFRARED PHYSICS & TECHNOLOGY 2018年 92卷 219-233页

作者： Sun, Shuang-Cheng Qi, Hong Wang, Shen-Ling Ren, Ya-Tao Ruan, Li-Ming Harbin Inst Technol Sch Energy Sci & Engn 92 West Dazhi St Harbin 150001 Heilongjiang Peoples R China

A multi-stage optimization technique is proposed to simultaneously reconstruct the infrared optical and thermophysical parameters in semitransparent media. The coupled radiative-conductive heat transfer in two-dimensional absorbing, scattering and emitting medium is solved by the discrete ordinate method combined with finite volume method. The exit radiative intensity and temperature distribution on the boundary are served as input for the inverse analysis, and the sequential quadratic programming is used as the inverse technique. Since the measurement signals are much more sensitive to the infrared absorption and scattering coefficients than to the thermal conductivity of medium, the thermophysical property cannot be accurately reconstructed by the conventional method. The multi-stage optimization technique is developed to solve the inverse estimation tasks, through which the optical and thermophysical parameters are reconstructed in different stages based on different objective functions. All the retrieval results demonstrate that the multi-stage optimization technique is robust and effective in simultaneous estimation of absorption coefficient, scattering coefficient and thermal conductivity. The optical and thermophysical parameters can be reconstructed accurately even with measurement errors.

关键词： Multi-stage optimization technique Image reconstruction Infrared optical parameter Thermal conductivity sequential quadratic programming Inverse technique

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Robust Design of Tension Truss Antennas Against Variation in Tension Forces

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AIAA JOURNAL 2018年第8期56卷 3374-3381页

作者： Fu, Kangjia Du, Jianbin Li, Jinyou Zhao, Zhihua Tsinghua Univ Sch Aerosp Engn Beijing 100084 Peoples R China

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Hybrid optimization procedure applied to optimal location finding for piezoelectric actuators and sensors for active vibration control

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APPLIED MATHEMATICAL MODELLING 2018年 62卷 701-716页

作者： Yassin, Belkourchia Lahcen, Azrar Zeriab, Es-Sadek Mohamed Mohammed V Univ ENSET Dept Appl Math & Informat Res Ctr STISM2CS Rabat Morocco KAU Fac Engn Dept Mech Engn Jeddah Saudi Arabia

This paper presents an efficient hybrid optimization approach using a new coupling technique for solving the constrained optimization problems. This methodology is based on genetic algorithm, sequential quadratic programming and particle swarm optimization combined with a projected gradient techniques in order to correct the solutions out of domain and send them to the domain's border. The established procedures have been successfully tested with some well known mathematical and engineering optimization problems, also the obtained results are compared with the existing approaches. It is clearly demonstrated that the solutions obtained by the proposed approach are superior to those of existing best solutions reported in the literature. The main application of this procedure is the location optimization of piezoelectric sensors and actuators for active control, the vibration of plates with some piezoelectric patches is considered. Optimization criteria ensuring good observability and controllability based on some main eigenmodes and residual ones are considered. Various rectangular piezoelectric actuators and sensors are used and two optimization variables are considered for each piezoelectric device: the location of its center and shape orientation. The applicability and effectiveness of the present methodological approach are demonstrated and the location optimization of multiple sensors and actuators are successfully obtained with some main modes and residual ones. The shape orientation optimization of sensors observing various modes as well as the local optimization of multiple sensors and actuators are numerically investigated. The effect of residual modes and the spillover reduction can be easily analyzed for a large number of modes and multiple actuators and sensors. (C) 2018 Elsevier Inc. All rights reserved.

关键词： Coupled optimization Border correction procedure Genetic algorithm sequential quadratic programming Particle swarm optimization Multi-piezoelectric actuators and sensors Optimal placement and orientation

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