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A hybrid gradient-based/metaheuristic method for Eurocode-compliant size, shape and topology optimization of steel structures

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ENGINEERING STRUCTURES 2021年 239卷 112137-112137页

作者： Dillen, Wouter Lombaert, Geert Schevenels, Mattias Katholieke Univ Leuven Fac Engn Sci Dept Architecture Kasteelpk Arenberg 1 B-3001 Leuven Belgium Katholieke Univ Leuven Fac Engn Sci Dept Civil Engn Kasteelpk Arenberg 40 B-3001 Leuven Belgium

The production and processing of building materials is responsible for a significant share of global greenhouse gas emissions. Nevertheless, in current building practice, a lot of material is wasted, because load-bearing structures are often grossly overdimensioned. Numerical optimization tools have the potential to reduce the consumption of structural materials, but the lack of customized algorithms prohibits their use in daily design practice. This is because real-life structural optimization problems are complex, involving both discrete and continuous design variables as well as large numbers of building code constraints. In the literature, such problems are usually solved using metaheuristic (often genetic) algorithms, although gradient-based algorithms are better suited for continuous design variables. In this article, a new hybrid gradient-based/metaheuristic algorithm is proposed. It combines gradient-based and metaheuristic methods in a nested approach, exploiting the strengths of both: the ability to handle discrete design variables and fast convergence in terms of continuous design variables. The applicability and usefulness of the new hybrid algorithm is demonstrated in two realistic case studies to minimize the weight of the structure, taking into account all relevant design rules of Eurocode 3. Within identical computing time, the hybrid algorithm obtains significant material savings compared to a conventional genetic algorithm.

关键词： Structural optimization Eurocode design Real-life optimization Genetic algorithm sequential quadratic programming Active set

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Nonlinear Model Predictive Control based Missile Guidance for Target Interception

Nonlinear Model Predictive Control based Missile Guidance fo...

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AIAA Science and Technology Forum and Exposition (AIAA SciTech)

作者： Bhattacharjee, Diganta Chakravarthy, Animesh Subbarao, Kamesh Univ Texas Arlington Dept Mech & Aerosp Engn Arlington TX 76019 USA Univ Texas Arlington Dept Mech & Aerosp Engn Box 19018 Arlington TX 76019 USA

ISBN: (数字)9781624105951

ISBN: (纸本)9781624105951

A nonlinear model predictive control (NMPC) based missile guidance algorithm for target interception is proposed. The planar engagement between a missile and a target is considered where both are assumed to be point masses. The lateral acceleration (or latax) commands for the missile are synthesized based on the numerical solutions to a quadratic program for the NPMC which does not require explicit information on the target acceleration. A cost function suitable for the problem is chosen and constraints are imposed on the latax, on the rate of change of latax, and on the relative velocity component along the line-of-sight (LOS). The quadratic program is shown to be a convex one. Suitable modifications are introduced in the quadratic program such that the guidance algorithm can accommodate constraint infeasibilities if required. Detailed simulations are included to illustrate the effectiveness of the proposed approach. Also, performance of the proposed guidance algorithm is compared with the performances of the pure proportional navigation (PPN) and a modified augmented proportional navigation (APN) (namely, augmented pure proportional navigation (APPN)) guidance laws. It is shown that the proposed guidance algorithm leads to performances comparable to the APPN guidance law, without requiring explicit knowledge of the target acceleration.

关键词： Model Predictive Control Missile Guidance Guidance Algorithms Control Guidance sequential quadratic programming Proportional Navigation Heading Angle Target Missiles Engagement Kinematics Nonlinear programming

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Multi-Stage Trajectory Optimization for Multiple Aircraft Approaching an Airport 18

Multi-Stage Trajectory Optimization for Multiple Aircraft Ap...

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18th European Control Conference (ECC)

作者： Semenov, Valeriy Kostina, Ekaterina Heidelberg Univ Fac Math & Comp Sci D-2019 Heidelberg Germany

ISBN: (纸本)9783907144022

In the paper, a multi-stage approach for numerical trajectory optimization of multiple aircraft in the vicinity of an airport is presented. The method for solving the problem consists of 5 stages where the first four solve the problem of ordering, fixing the final times and hierarchical distance separation, and the solution of the hierarchical formulation is then used as the initial guess for the combined problem with pairwise distance constraints. The approach proved to be very efficient in terms of computation speed resulting in computation time of less than 3 minutes for all stages of solving the trajectory optimization problem for 5 aircraft. The numerical experiments were carried out with MUSCOD-II optimization software.

关键词： Trajectory optimization flight dynamics multiple shooting sequential quadratic programming

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Optimal 3D-UAV Trajectory and Resource Allocation of DL UAV-GE Links with Directional Antennas

Optimal 3D-UAV Trajectory and Resource Allocation of DL UAV-...

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IEEE Global Communications Conference (GLOBECOM) on Advanced Technology for 5G Plus

作者： Vilor, Carles Diaz Jafarkhani, Hamid Univ Calif Irvine Ctr Pervasive Commun & Comp Irvine CA 92717 USA

ISBN: (纸本)9781728182988

Unmanned Aerial Vehicle (UAV) is a promising technology to solve many new challenging problems. It provides high maneuverability and control, low manufacturing cost with respect to other flying technologies and many other features. In particular, there is an increasing interest in UAVs in the field of wireless communications, due to their capacity to carry on transceivers and establish communication among UAVs, or between UAVs and ground base stations/users. In this work. we investigate a UAV deployment in which each flying vehicle serves a set of users, carrying directional antennas. To do so, we maximize the minimum downlink rate among the users that a UAV serves. Due to the non-convexity of the problem, we will divide it into four sub-problems. Afterwards, an iterative algorithm is proposed to optimize the four sub-problems by using the block coordinate descent method, successive convex approximation and sequential quadratic programming. Simulation results show that the addition of directional antennas results in a better performance in terms of throughput compared with omni-directional benchmarks.

关键词： UAV trajectory optimization directional antennas resource allocation successive convex approximation sequential quadratic programming block coordinate descent

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Research on Sliding Mode Active Disturbance Rejection Control and Thrust Allocation of Dynamic Positioning System

Research on Sliding Mode Active Disturbance Rejection Contro...

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Chinese Intelligent Automation Conference

作者： Piao, Zaiji Guo, Chen Dalian Maritime Univ Sch Marine Elect Engn Dalian Peoples R China

ISBN: (纸本)9789813290501;9789813290495

In order to further improve the control ability of dynamic positioning ship or platform under complex sea conditions, the controller and thrust allocation system of dynamic positioning are designed. A simplified three-degree-of-freedom MMG mathematical model is established for the pod full-rotation propeller used in most dynamic positioning ships. On the basis of retaining the advantages of active disturbance rejection control, the sliding mode variable structure control method is adopted to design the control law. The objective function and constraints of thrust allocation are designed based on the lowest energy consumption, and the sequential quadratic programming algorithm is used to calculate the real-time thrust allocation of each propeller. The simulation results of the ship dynamic positioning system in MATLAB show that the controller can maintain the stability and robustness of the system under the condition of external environment disturbance, and the results of the thrust allocation are reasonable, which has a certain reference value for the further study of the ship dynamic positioning control system.

关键词： Sliding mode control Dynamic positioning system Thrust allocation sequential quadratic programming

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Design of moth flame optimization heuristics for integrated power plant system containing stochastic wind

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APPLIED SOFT COMPUTING 2021年 104卷 107193-107193页

作者： Khan, Babar Sattar Raja, Muhammad Asif Zahoor Qamar, Affaq Chaudhary, Naveed Ishtiaq Univ Engn & Technol Peshawar Dept Elect Energy Syst Engn USPCAS E Peshawar Khyber Pakhtunk Pakistan COMSATS Univ Islamabad Dept Elect & Comp Engn Campus Attock Attock Pakistan Natl Yunlin Univ Sci & Technol Future Technol Res Ctr 123 Univ RdSect 3 Touliu 64002 Yunlin Taiwan Int Islamic Univ Dept Elect Engn Islamabad Pakistan

In this investigation, nature-inspired heuristic strategy exploiting moth flame optimization (MFO) algorithm combined with active-set algorithm (ASA), interior point algorithm (IPA) and sequential quadratic programming (SQP) are presented to take care of the enhancement issues of economic load dispatch (ELD) problem involving valve point loading effect (VPLE) and stochastic wind (SW). The strength of MFO algorithm is used as a global search mechanism that explore and exploit the entire search space while ASA, IPA and SQP are responsible for refinement of local optimum. The performance of the design system is based on 40 generating units including 37 thermal and 3 wind power units and is evaluated to verify the effectiveness of the scheme. The worth of the design integrated heuristic of MFO algorithm is endorsed through outcomes of the state of the art counterpart solvers in case of ELD problems integrated with wind power units in terms of cost minimization and computational complexity parameters. (C) 2021 Elsevier B.V. All rights reserved.

关键词： Moth flame optimization algorithm sequential quadratic programming Active-set algorithm Interior-point algorithm Economic load dispatch Integrated power systems

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Meyer wavelet neural networks to solve a novel design of fractional order pantograph Lane-Emden differential model

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CHAOS SOLITONS & FRACTALS 2021年 152卷

作者： Sabir, Zulqurnain Raja, Muhammad Asif Zahoor Guirao, Juan L. G. Saeed, Tareq Hazara Univ Dept Math & Stat Mansehra Pakistan Natl Yunlin Univ Sci & Technol Future Technol Res Ctr 123 Univ RdSect 3 Touliu 64002 Yunlin Taiwan Tech Univ Cartagena Hosp Marina Dept Appl Math & Stat Cartagena 30203 Spain King Abdulaziz Univ Fac Sci Dept Math Nonlinear Anal & Appl Math NAAM Res Grp POB 80203 Jeddah 21589 Saudi Arabia

The aim of this study is to design a singular fractional order pantograph differential model by using the typical form of the Lane-Emden model. The necessary details of the singular-point, fractional order and shape factor of the designed model are also provided. The numerical solutions of the designed model have been presented using the combination of the fractional Meyer wavelet (FMW) neural networks (NNs) modeling and optimization of global search with genetic algorithm (GA) supported with local search of sequential quadratic programming (SQP), i.e., FMWNN-GASQP. The strength of FMWNN is employed to design an objective function using the differential model along with its initial conditions of the singular fractional order pantograph model. The optimization of this objective function is performed using the integrated competence of GA-SQP. The verification, perfection and authentication of the singular fractional order pantograph model using fractional Meyer computing solver is observed for different cases through comparative studies from the available exact solutions which endorsed its robustness, convergence and stability. Moreover, the statistics observation with necessary explanations further authenticate the performance of the FMWNN-GASQP in terms of accuracy and reliability. (c) 2021 Elsevier Ltd. All rights reserved.

关键词： Singular fractional order pantograph model Shape factors Meyer wavelet neural models sequential quadratic programming Genetic algorithm Statistical analysis

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Solving a novel designed second order nonlinear Lane-Emden delay differential model using the heuristic techniques

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APPLIED SOFT COMPUTING 2021年 102卷 107105-107105页

作者： Sabir, Zulqurnain Guirao, Juan L. G. Saeed, Tareq Hazara Univ Dept Math & Stat Mansehra Pakistan Tech Univ Cartagena Hosp Marina Dept Appl Math & Stat Cartagena 30203 Spain King Abdulaziz Univ Fac Sci Dept Math Nonlinear Anal & Appl Math NAAM Res Grp POB 80203 Jeddah 21589 Saudi Arabia

The aim of the present study is to present a new model based on the nonlinear singular second order delay differential equation of Lane-Emden type and numerically solved by using the heuristic technique. Four different examples are presented based on the designed model and numerically solved by using artificial neural networks optimized by the global search, local search methods and their hybrid combinations, respectively, named as genetic algorithm (GA), sequential quadratic programming (SQP) and GA-SQP. The numerical results of the designed model are compared for the proposed heuristic technique with the exact/explicit results that demonstrate the performance and correctness. Moreover, statistical investigations/assessments are presented for the accuracy and performance of the designed model implemented with heuristic methodology. (C) 2021 Elsevier B.V. All rights reserved.

关键词： Delay differential equations Lane-Emden Artificial neural networks Nonlinear Genetic algorithm Statistical analysis sequential quadratic programming

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An Optimistic Solver for the Mathematical Model of the Flow of Johnson Segalman Fluid on the Surface of an Infinitely Long Vertical Cylinder

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MATERIALS 2021年第24期14卷 7798-7798页

作者： Khan, Naveed Ahmad Alshammari, Fahad Sameer Romero, Carlos Andres Tavera Sulaiman, Muhammad Mirjalili, Seyedali Abdul Wali Khan Univ Dept Math Mardan 23200 Pakistan Prince Sattam bin Abdulaziz Univ Dept Math Coll Sci & Humanities Al Kharj Al Kharj 11942 Saudi Arabia Univ Santiago Cali Fac Engn COMBA R&D Lab Cali 76001 Colombia Torrens Univ Australia Ctr Artificial Intelligence Res & Optimisat Brisbane Qld 4006 Australia Yonsei Univ Yonsei Frontier Lab Seoul 03722 South Korea

In this paper, a novel soft computing technique is designed to analyze the mathematical model of the steady thin film flow of Johnson-Segalman fluid on the surface of an infinitely long vertical cylinder used in the drainage system by using artificial neural networks (ANNs). The approximate series solutions are constructed by Legendre polynomials and a Legendre polynomial-based artificial neural networks architecture (LNN) to approximate solutions for drainage problems. The training of designed neurons in an LNN structure is carried out by a hybridizing generalized normal distribution optimization (GNDO) algorithm and sequential quadratic programming (SQP). To investigate the capabilities of the proposed LNN-GNDO-SQP algorithm, the effect of variations in various non-Newtonian parameters like Stokes number (S-t), Weissenberg number (W-e), slip parameters (a), and the ratio of viscosities ( f ) on velocity profiles of the of steady thin film flow of non-Newtonian Johnson-Segalman fluid are investigated. The results establish that the velocity profile is directly affected by increasing Stokes and Weissenberg numbers while the ratio of viscosities and slip parameter inversely affects the fluid's velocity profile. To validate the proposed technique's efficiency, solutions and absolute errors are compared with reference solutions calculated by RK-4 (ode45) and the Genetic algorithm-Active set algorithm (GA-ASA). To study the stability, efficiency and accuracy of the LNN-GNDO-SQP algorithm, extensive graphical and statistical analyses are conducted based on absolute errors, mean, median, standard deviation, mean absolute deviation, Theil's inequality coefficient (TIC), and error in Nash Sutcliffe efficiency (ENSE). Statistics of the performance indicators are approaching zero, which dictates the proposed algorithm's worth and reliability.

关键词： drainage problems Johnson Segalman model computational fluid dynamics weighted legendre neural networks hybrid soft computing generalized normal distribution optimization sequential quadratic programming

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Efficient Modal Design Variables for Optimization of Aero-Elastic Wing

Efficient Modal Design Variables for Optimization of Aero-El...

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AIAA Science and Technology Forum and Exposition (AIAA SciTech)

作者： Poole, D. J. Allen, C. B. Rendall, T. C. S. Univ Bristol Dept Aerosp Engn Bristol BS8 1TR Avon England

ISBN: (数字)9781624105951

ISBN: (纸本)9781624105951

Efficient multi-disciplinary optimization is presented for aero-structural wing optimization using efficient low-dimensional modal design variables. Orthogonal aerofoil design variables are derived in the geometric space via singular value decomposition. Orthogonality of design variables leads to a well-conditioned design space and encourages positive optimizer convergence. These are applied in a sectional fashion for fixed planform drag minimization of a flexible transonic wing. Shock-free solutions are demonstrated for the rigid wing, indicating suitability of the aerofoil modes for sectional-based wing optimization. However, these wings have poor performance when deformed under flight loads, hence full aeroelastic performance is taken into account. Encouragingly, shock-free solutions are again found. Loading is shifted outboard, leading to increased tip-deflection. Monotonic improvement in objective with increase in dimensionality is also observed.

关键词： Aerofoil Singular Value Decomposition Rigid Wings Aerodynamic Shape Optimization sequential quadratic programming Computational Fluid Dynamics Aerodynamic Performance Structural Modeling Aircraft Wing Design Structural Response

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