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AIAA Guidance, Navigation, and Control Conference

作者： Yokoyama, Nobuhiro Natl Def Acad Dept Aerosp Engn 1-10-20 Hashirimizu Yokosuka Kanagawa 2398686 Japan

ISBN: (数字)9781624104503

ISBN: (纸本)9781624104503

This paper presents a method to infer the intent of an aircraft by using inverse optimal control. Assuming that the observed or estimated trajectory of the target aircraft is the approximate local optimum, the current method calculates the weight of each term of the objective function that represents the flight's intent. The intent may include direct travel to a waypoint;circling around a waypoint;holding airspeed/heading/turn rate;avoiding certain regions such as those with adverse weather or special-use airspaces;and resolving conflicts with other aircraft. By incorporating the second-order optimality condition (i.e., the positive definiteness of the projected Hessian of the Lagrangian), the method approximately satisfies the sufficiency of the local optimality of the given trajectory. Moreover, the method also guarantees the uniqueness of the inferred intent. The effectiveness of the current method in terms of the reasonableness of the inferred intent as well as real-time applicability is demonstrated through numerical examples.

关键词： Optimal Control Light Aircraft Special Use Airspace Airspeed Inverse Problems Trajectory Based Operations Linear Quadratic Regulator Interacting Multiple Model optimization algorithm Air Traffic Controller

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Multi-objective reliability-based design optimization approach of complex structure with multi-failure modes

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AEROSPACE SCIENCE AND TECHNOLOGY 2017年 64卷 52-62页

作者： Song, Lu-Kai Fei, Cheng-Wei Wen, Jie Bai, Guang-Chen Beihang Univ Sch Energy & Power Engn Beijing 100191 Peoples R China Hongkong Polytechn Univ Dept Mech Engn Kowloon Hong Kong Peoples R China

To make multi-objective reliability-based design optimization (MORBDO) more effective for complex structure with multi-failure modes and multi-physics coupling, multiple response surface method (MRSM)-based artificial neural network (ANN) (ANN-MRSM) and dynamic multi-objective particle swarm optimization (DMOPSO) algorithm are proposed based on MRSM and MOPSO algorithm. The mathematical model of ANN-MRSM is established by using artificial neural network to fit the multiple response surface function. The DMOPSO algorithm is proposed by designing dynamic inertia weight and dynamic learning factors. The proposed approach is verified by the MORBDO of turbine blisk deformation and stress with respect to fluid-thermal-structure interaction from probabilistic analysis. The optimization design results show that the proposed approach has the promising potentials to improve computational efficiency with acceptable computational precision for the MORBDO of turbine blisk deformation and stress. Moreover, Pareto front curve and a set of viable design values of turbine blisk are obtained for the high-reliability high-performance design of turbine blisk. The presented efforts provide an effective approach for MORBDO of complex structures, and enrich mechanical reliability design theory as well. (C) 2017 Elsevier Masson SAS. All rights reserved.

关键词： Multi-objective reliability-based design optimization Multi-failure modes Multiple response surface method Artificial neural network Dynamic multi-objective particle swarm optimization algorithm

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Fast Procedure for the Nonlinear Analysis of BAW Resonators

Fast Procedure for the Nonlinear Analysis of BAW Resonators

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IEEE International Ultrasonics Symposium (IUS)

作者： Perea-Robles, Rafael Garcia-Pastor, David Mateu, Jordi Collado, Carlos Aigner, Robert UPC Barcelona Catalunya Spain Qorvo Apopka FL USA

ISBN: (纸本)9781538634257

This work presents the development of a Matlab software tool based on a non-iterative method for the nonlinear analysis of Bulk Acoustic Wave (BAW) resonators and filters. The procedure starts with the admittance matrix extraction of the distributed circuit that models a resonator. The aim of this procedure is to avoid high computation times and/or convergence problems that usually appear when performing Harmonic Balance (HB) simulations of very large circuits, as those resulting from a distributed model of a BAW resonator with a high discretization level. Moreover, the procedure allows to simulate the potential isolated contribution of each nonlinear coefficient that appear in the constitutive equations with a low penalty in terms of computation time. As an example, this analysis capability is integrated with ana* optimization algorithm that is able to find the first order nonlinear coefficients that better match the second harmonic (H2) broadband measurements of a device.

关键词： Nonlinear BAW AlN SiO2 Bragg Mirror nonlinearities second harmonic non-iterative method nonlinear coefficients optimization algorithm

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A Modified QPSO for Robotic Vehicle Path Planning

A Modified QPSO for Robotic Vehicle Path Planning

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IEEE Congress on Evolutionary Computation (IEEE CEC) as part of the IEEE World Congress on Computational Intelligence (IEEE WCCI)

作者： Fernandes, Pedro B. Limao de Oliveira, Roberto C. Fonseca Neto, Joao Viana Univ Fed Sul & Sudeste Para Comp & Elect Engn Fac Maraba Brazil Univ Fed Para Dept Elect Engn Belem Para Brazil Univ Fed Maranhao Dept Elect Engn Sao Luis Brazil

ISBN: (纸本)9781509060177

This paper describes the techniques used for an effective trajectory planning for mobile robots. For this purpose, it's proposed a new modified Quantum Behaved Particle Swarma* optimization algorithm. This new algorithm allows the creation of a particle swarm with a more diverse population, increasing the search scope within the space of solutions. Besides that, a technique called Straight-Line Method is also introduced in this work to efficiently reduce the number of points required for the route optimization on the vehicle navigation space. The tests and simulations presented indicate satisfactory results for the optimizations performed, and that the addressed techniques in this work can be applied to several types of autonomous vehicles.

关键词： trajectory planning optimization algorithm QPSO swarm computation autonomous vehicle

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Unified Multiobjective optimization Scheme for Aeroassisted Vehicle Trajectory Planning

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JOURNAL OF GUIDANCE CONTROL AND DYNAMICS 2018年第7期41卷 1521-1530页

作者： Chai, Runqi Savvaris, Al Tsourdos, Antonios Chai, Senchun Xia, Yuanqing Cranfield Univ Sch Aerosp Transport & Mfg Cranfield MK43 0AL Beds England Beijing Inst Technol Sch Automat Beijing 100081 Peoples R China

In this work, a multiobjective aeroassisted trajectory optimization problem with mission priority constraints is constructed and studied. To effectively embed the priority requirements into the optimization model, a specific transformation technique is applied and the original problem is then transcribed to a single-objective formulation. The resulting single-objective programming model is solved via an evolutionarya* optimization algorithm. Such a design is unlike most traditional approaches where the nondominated sorting procedure is required to be performed to rank all the objectives. Moreover, in order to enhance the local search ability of the optimization process, a hybrid gradient-based operator is introduced. Simulation results indicate that the proposed design can produce feasible and high-quality flight trajectories. Comparative simulations with other typical methods are also performed, and the results show that the proposed approach can achieve a better performance in terms of satisfying the prespecified priority requirements.

关键词： Vehicle Trajectories Trajectory optimization optimization algorithm Flight Trajectory Hybrid Genetic algorithm Aerodynamic Heating Angle of Attack Particle Swarm optimization Terminal Velocity Fuel Consumption

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Robust Airfoil optimization and the Importance of Appropriately Representing Uncertainty

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AIAA JOURNAL 2017年第11期55卷 3925-3939页

作者： Cook, Laurence W. Jarrett, Jerome P. Univ Cambridge Dept Engn Trumpington St Cambridge CB2 1PZ England

The importance of designing airfoils to be robust with respect to uncertainties in operating conditions is well recognized. However, often, the probability distribution of such uncertainties does not exist or is unknown, and a designer looking to perform a robust optimization is tasked with deciding how to represent these uncertainties within the optimization framework. This paper asks the following: How important is the choice of how to represent input uncertainties mathematically in robust airfoil optimization? It specifically compares probabilistically based aleatory uncertainties and interval-based epistemic uncertainties. This is first investigated by considering optimizations on several algebraic test problems, which illustrate the mechanisms by which the representation of uncertainty becomes significant in a robust optimization. This insight is then used to predict and subsequently demonstrate that, for two airfoil design problems, the advantage of doing a robust optimization over a deterministic optimization is similar, regardless of how the input uncertainties are represented mathematically. The benefit of this is potentially eliminating the time required to establish an accurate representation of the uncertainties from the preliminary stage of design, where time is a valuable resource.

关键词： NACA 0012 Probability Density Functions Aerodynamic Shape optimization Lift to Drag Ratio Lift Coefficient CFD Flow Conditions Shape optimization Robust Design optimization algorithm

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Aerodynamic optimization of a Single-Stage Axial Compressor with Stator Shroud Air Injection

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AIAA JOURNAL 2017年第8期55卷 2739-2754页

作者： Dinh, Cong-Truong Ma, Sang-Bum Kim, Kwang-Yong Inha Univ Dept Mech Engn 100 Inha Ro Incheon 22212 South Korea

The effects of stator shroud air injection on aerodynamic performance were investigated for a single-stage axial compressor. Multiobjective optimization of the air injector was performed to maximize the enhancements of the peak adiabatic efficiency and stall margin using three-dimensional Reynolds-averaged Navier-Stokes equations. The numerical results for adiabatic efficiency and the total pressure ratio were validated with experimental data for a smooth casing. The design variables were determined through a parametric study as the axial distance between stator leading edge and the injector, the radius of the injector surface curvature, the circumferential coverage of the injector, and the injection mass flow rate. The peak adiabatic efficiency and stall margin were selected as the objective functions. Kriging models were constructed using objective function values calculated at 45 design points, which were selected by Latin hypercube sampling to approximate the objective functions. The performances of two differenta* optimization algorithms were compared. The optimization results showed that an efficiency-oriented optimum design presented an increase of 2.47% in the peak adiabatic efficiency when compared with the compressor with a smooth casing, whereas a stall margin-oriented optimum design showed an increase of 1.13% in the stall margin.

关键词： Multistage Axial Compressors Mass Flow Rate Reynolds Averaged Navier Stokes Aerodynamic Performance Leading Edges optimization algorithm Kriging Model Particle Swarm optimization Surrogate Model Sound Pressure Level

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Flight Performance optimization of a Multilift Rotorcraft Formation

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JOURNAL OF AIRCRAFT 2017年第4期54卷 1521-1538页

作者： Enciu, J. Horn, J. F. Penn State Univ Dept Aerosp Engn University Pk PA 16802 USA

A numeric optimization is performed for maximizing the cruise performance of a multilift rotorcraft system. The optimization process locates the optimal relative positions of the formation rotorcraft. The optimization problem is formulated as a constrained nonlinear programming problem. Constraints on the distances between the formation rotorcraft are imposed in order to maintain safe separation distances. It is shown that, for every airspeed, an optimal formation geometry can be found that minimizes the rotorcraft power required. An optimization analysis for subsequent airspeeds yields an optimal recommended airspeed that is close to the "bucket" airspeed of the unloaded rotorcraft. The cable length is shown to have a secondary influence on optimization results. The improvement in the resulting multilift mission performance is demonstrated using a nonlinear simulation of the system. It is shown that the operational efficiency of the system can be significantly increased by adopting the optimization results.

关键词： Rotorcrafts True Airspeed Numerical optimization Flight Performance UH 60 Black Hawk Helicopter Aerodynamic Performance Aerodynamic Characteristics Heading Angle Angle of Sideslip optimization algorithm

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Closed-Loop optimization of Guidance Gain for Constrained Impact

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JOURNAL OF GUIDANCE CONTROL AND DYNAMICS 2017年第2期40卷 453-460页

作者： Liu, Xinfu Shen, Zuojun Lu, Ping Beijing Inst Technol Sch Aerosp Engn Beijing 100081 Peoples R China Beihang Univ Sch Aeronaut Sci & Engn Beijing 100191 Peoples R China San Diego State Univ Dept Aerosp Engn San Diego CA 92182 USA

The tightly constrained guidance problem of impact on a stationary target is considered, subject to look-angle and lateral-acceleration limits, as well as final impact-angle and look-angle constraints. Proportional-navigation guidance with a time-varying gain is proposed to address this problem. The problem has been formulated as an optimal-control problem, where the time-varying PN gain is regarded to be the control, subject to nonlinear engagement kinematics and all the inequality and terminal constraints. A successive solution approach is proposed to solve this nonlinear optimal-control problem as a sequence of convex optimal-control problems that can be numerically solved as second-order cone programs. Compared with standard direct-trajectory-optimization approaches based on general nonlinear-programming methods, the proposed method can solve the problem two orders of magnitude faster in terms of computational time. Compared with existing PN guidance approaches, the proposed method provides a more rigorous and systematic guidance approach, and assures the satisfaction of all guidance objectives in highly constrained but feasible scenarios.

关键词： Closed Loop Trajectory optimization Flight Path Angle Guidance Laws Engagement Kinematics Nonlinear Programming Proportional Navigation Velocity Profiles Aerodynamic Drag optimization algorithm

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optimization of thin-wall structures using hybrid gravitational search and Nelder-Mead algorithm

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MATERIALS TESTING 2016年第1期58卷 75-78页

作者： Yildiz, Ali Riza Kurtulus, Enes Demirci, Emre Yildiz, Betul Sultan Karagoz, Selcuk Bursa Tech Univ Dept Mech Engn Bursa Turkey Bursa Tech Univ Nat Sci & Engn Fac Bursa Turkey Bursa Tech Univ MPDOL Bursa Turkey Univ Michigan Ann Arbor MI 48109 USA Mississippi State Univ CAVS Mississippi State MS 39762 USA Yesilova Holding Istanbul Turkey Bursa Tech Univ Bursa Turkey

In literature, a lot of research works have been presented on crashworthiness in order to develop crash performance of vehicles and thin-wall structures. In this research, a new hybrida* optimization algorithm based on gravitational search algorithm and Nelder-Mead algorithm is introduced to improve crash performance of vehicles during frontal impact. The results show that the hybrid approach is very effective to develop crash performance of the vehicle components and thin-wall structures.

关键词： Thin-wall structures crashworthiness automotive optimization algorithm

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