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Design of neuro-computing paradigms for nonlinear nanofluidic systems of MHD Jeffery-Hamel flow

JOURNAL OF THE TAIWAN INSTITUTE OF CHEMICAL ENGINEERS 2018年 91卷 57-85页

作者： Mehmood, Ammara Nouman-Ul-Haq Zameer, Aneela Ling, Sai Ho Raja, Muhammad Asif Zahoor Pakistan Inst Engn & Appl Sci Dept Elect Engn Islamabad Pakistan Riphah Int Univ Dept Phys Islamabad Pakistan PIEAS Dept Comp & Informat Sci Islamabad 45650 Pakistan Univ Technol Dept Engn & IT Ctr Hlth Technol Sch Biomed Engn Sydney NSW Australia COMSATS Inst Informat Technol Dept Elect Engn Attock 43600 Pakistan

In this paper, a neuro-heuristic technique by incorporating artificial neural network models (NNMs) optimized with sequential quadratic programming (SQP) is proposed to solve the dynamics of nanofluidics system based on magneto-hydrodynamic (MHD) Jeffery-Hamel (JHF) problem involving nano-meterials. Original partial differential equations associated with MHD-JHF are transformed into third order ordinary differential equations based model. Furthermore, the transformed system has been implemented by the differential equation NNMs (DE-NNMs) which are constructed by a defined error function using logsigmoid, radial basis and tan-sigmoid windowing kernels. The parameters of DE-NNM of nanofluidics system are optimized with SQP algorithm. To illustrate the performance of the proposed system, MHD-JHF models with base-fluid water mixed with alumina, silver and copper nanoparticles for different Hartman numbers, Reynolds numbers, angles of the channel and volume fractions with three different proposed DE-NNMs are designed to evaluate. For comparison purpose, the proposed results with reference numerical solutions of Adams solver illustrate their worth. Statistical inferences through different performance indices are given to demostrate the accuracy, stability and robustness of the stochastic solvers. (C) 2018 Taiwan Institute of Chemical Engineers. Published by Elsevier B.V. All rights reserved.

关键词： Magneto-hydrodynamic Jeffery-Hamel flow Artificial neural networks Nanofluids Neurocomputing sequential quadratic programming

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The method for optimisation of gas compressors performance in gas storage systems

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INTERNATIONAL JOURNAL OF OIL GAS AND COAL TECHNOLOGY 2018年第1期17卷 12-33页

作者： Warchol, Michal Swirski, Konrad Ruszczycki, Blazej Wojdan, Konrad Transit Technol SA Warsaw Poland Warsaw Univ Technol Inst Heat Engn Warsaw Poland Polish Acad Sci Nencki Inst Expt Biol Warsaw Poland

We present a computational method for achieving an optimal operation of compressor units used in industrial gas storage systems. The proposed method is capable to operate with a mix of compressor types (i.e., with different operational parameters, different power drives, and different types of construction, e.g., reciprocal and turbocompressors). The goal of the optimisation is to find an optimal compressors configuration and distribution of the compressor loads for each instance of time. The proposed method is based on conversion of a multidimensional discrete-continuous optimisation problem into a set of independent combinatorial and nonlinear optimisation problems. We derive the mathematical foundations of the algorithms. The exemplary results of the application are presented.

关键词： optimisation compressor station dynamic programming sequential quadratic programming SQP gas storage

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Tentacle-Based Guidance for Entry Flight with No-Fly Zone Constraint

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JOURNAL OF GUIDANCE CONTROL AND DYNAMICS 2018年第4期41卷 996-1005页

作者： Liang, Zixuan Ren, Zhang Beihang Univ Sch Astronaut Beijing 100191 Peoples R China Beihang Univ Sch Automat Sci & Elect Engn Beijing 100191 Peoples R China

A tentacle-based guidance method has been proposed for entry flights with the no-fly zone constraint. The proposed method is applicable to zones in general shapes. Simulations have been conducted for four entry missions with various no-fly zones. Results show that the tentacle is capable of suggesting a feasible path for the vehicle. The lateral guidance logic, which combines the tentacle feedback and the heading error, is able to fly the vehicle to the target without entering the no-fly zones. The longitudinal tracking law performs well in following the reference trajectory. Therefore, the proposed guidance method can satisfy both the conventional constraints and the additional no-fly zone constraint. Moreover, the guidance method is demonstrated to be effective when the detection of the threat is delayed, which means that it does not rely on the prior knowledge of no-fly zones. To guarantee the computational performance for guidance commands, the guidance method generates only two tentacles in each lateral guidance cycle.

关键词： Aerodynamic Coefficients Lift Coefficient Active Disturbance Rejection Control Flight Path Angle Lift to Drag Ratio Mobile Robots Earth Algebraic Riccati Equation Heading Angle sequential quadratic programming

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A REGULARIZED FACTORIZATION-FREE METHOD FOR EQUALITY-CONSTRAINED OPTIMIZATION

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SIAM JOURNAL ON OPTIMIZATION 2018年第2期28卷 1613-1639页

作者： Arreckx, Sylvain Orban, Dominique Ecole Polytech GERAD Montreal PQ H3C 3A7 Canada Ecole Polytech Dept Math & Ind Engn Montreal PQ H3C 3A7 Canada

We propose a method for equality-constrained optimization based on a problem in which all constraints are systematically regularized. The regularization is equivalent to applying an augmented Lagrangian method but the linear system used to compute a search direction is reminiscent of regularized sequential quadratic programming. A limited-memory BFGS approximation to second derivatives allows us to employ iterative methods for linear least squares to compute steps, resulting in a factorization-free implementation. We establish global and fast local convergence under weak assumptions. In particular, we do not require the LICQ and our method is suitable for degenerate problems. Preliminary numerical experiments show that a factorization-based implementation of our method exhibits significant robustness while a factorization-free implementation, though not as robust, is promising. We briefly discuss generalizing our framework to other classes of methods and to problems with inequality constraints.

关键词： sequential quadratic programming regularization augmented Lagrangian limited-memory BFGS factorization-free method

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A semismooth sequential quadratic programming method for lifted mathematical programs with vanishing constraints

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COMPUTATIONAL MATHEMATICS AND MATHEMATICAL PHYSICS 2011年第6期51卷 919-941页

作者： Izmailov, A. F. Pogosyan, A. L. Moscow MV Lomonosov State Univ Fac Computat Math & Cybernet Moscow 119991 Russia

Mathematical programs with vanishing constraints are a difficult class of optimization problems with important applications to optimal topology design problems of mechanical structures. Recently, they have attracted increasingly more attention of experts. The basic difficulty in the analysis and numerical solution of such problems is that their constraints are usually nonregular at the solution. In this paper, a new approach to the numerical solution of these problems is proposed. It is based on their reduction to the so-called lifted mathematical programs with conventional equality and inequality constraints. Special versions of the sequential quadratic programming method are proposed for solving lifted problems. Preliminary numerical results indicate the competitiveness of this approach.

关键词： mathematical program with vanishing constraints lifted problem mathematical program with complementarity constraints constraint qualifications optimality conditions sequential quadratic programming

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Optimal fractional order adaptive controllers for AVR applications

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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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