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Optimal Trajectory Design Accounting for Robust Stability of Path-Following Controller

JOURNAL OF GUIDANCE CONTROL AND DYNAMICS 2022年第8期45卷 1385-1398页

作者： Piprek, Patrick Hong, Haichao Holzapfel, Florian Tech Univ Munich Inst Flight Syst Dynam Garching Germany

This study presents an optimal control framework that designs an optimal trajectory while additionally accounting for the stability of a path-deviation error controller that is dependent on the states provided by the optimal trajectory. Thus, instead of designing the controller independent of the trajectory, the stability is enforced as part of the optimization constraints in connection with the optimal trajectory it should follow. This allows to trade off controller and trajectory optimally and thus permits an improved exploitation of the system capabilities. To achieve this goal, the classic trajectory optimization problem formulation is augmented by stability constraints and feedback gains, with the latter being used as optimization parameters. These stabilize the path-following error dynamics by means of gain scheduling and enforce desired response characteristics. Here, the response is shaped, for once, by enforcing limits on the position of the real and imaginary parts of the eigenvalues as well as by limiting their sensitivity. Especially the latter is a way of robustifying the feedback controller in the time domain. The applicability of the proposed method is shown in an aviation-related scenario by solving a missile guidance problem.

关键词： Model Predictive Control Trajectory optimization Missile Guidance Aviation Nonlinear Programming Handling Qualities Feedback Control Loop Unmanned Aerial Vehicle optimization algorithm Sensitivity Analysis

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Physics-Informed Deep Learning Approach to Solve Optimal Control Problem

Physics-Informed Deep Learning Approach to Solve Optimal Con...

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AIAA SciTech Forum

作者： Na, Kyung-Mi Lee, Chang-Hun Korea Adv Inst Sci & Technol Dept Aerosp Engn Daejeon 34141 South Korea

ISBN: (数字)9781624107115

ISBN: (纸本)9781624107115

The proposed method aims to construct optimal control solutions using physics-informed deep learning and optimal control theory. The methodology involves deriving differential equations and final constraints from the Euler-Lagrange equations. Physics-informed neural networks are then designed to match these differential equations and conditions. Additionally, a physics-informed deepONet is introduced to predict the final state when the control input is provided. The effectiveness of the proposed method is demonstrated through the application of the optimal impact time guidance problem. The method can find optimal solutions even with varying initial and final conditions. The obtained results are compared with those from a parametric optimization solver, and despite not using any optimal control solution data, the difference between them is relatively small. An important characteristic of the proposed method is that the neural networks are time-dependent and pre-trained, meaning that the solution is a continuous function of time and conditions and can be applied in real-time.

关键词： Hamilton Jacobi Bellman (HJB) Equations Neural Networks Flight Path Angle Numerical Integration Aerospace Engineering Nonlinear Dynamics Missile Guidance Unmanned Aerial Vehicle Spacecraft Trajectory optimization optimization algorithm

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On The Use of Risk Measures in Digital Twins to Identify Weaknesses in Structures

On The Use of Risk Measures in Digital Twins to Identify Wea...

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AIAA SciTech Forum

作者： Airaudo, Facundo Antil, Harbir Lohner, Rainald Rakhimov, Umarkhon George Mason Univ Ctr Computat Fluid Dynam Fairfax VA 22030 USA George Mason Univ Dept Phys Fairfax VA 22030 USA George Mason Univ Ctr Math & Artificial Intelligence CMAI Fairfax VA 22030 USA George Mason Univ Dept Math Sci Fairfax VA 22030 USA

ISBN: (数字)9781624107115

ISBN: (纸本)9781624107115

Given measurements from sensors and a set of standard forces, an optimization based approach to identify weakness in structures is introduced. The key novelty lies in letting the load and measurements to be random variables. Subsequently the conditional-value-at-risk (CVaR) is minimized subject to the elasticity equations as constraints. CVaR is a risk measure that leads to minimization of rare and low probability events which the standard expectation cannot. The optimization variable is the (deterministic) strength factor which appears as a coefficient in the elasticity equation, thus making the problem nonconvex. Due to uncertainty, the problem is high dimensional and, due to CVaR, the problem is nonsmooth. An adjoint based approach is developed with quadrature in the random variables. Numerical results are presented in the context of a plate, a large structure with trusses similar to those used in solar arrays or cranes, and a footbridge.

关键词： Digital Twins Sensors Poisson's Ratio Trusses Cumulative Distribution Function optimization algorithm Stiffness Matrices International Space Station Computational Modeling Aeroplane

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Creasing of thin, elastic plates for maximizing fundamental frequencies

Creasing of thin, elastic plates for maximizing fundamental ...

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AIAA SciTech Forum

作者： Vijayachandran, Avinkrishnan Ambika Oudghiri-Idrissi, Othman Danawe, Hrishikesh Mao, Xiaoming Arruda, Ellen Tol, Serife Waas, Anthony M. Univ Michigan Dept Aerosp Engn 1320 Beal Ave Ann Arbor MI 48109 USA Univ Michigan Dept Mech Engn 2350 Hayward St Ann Arbor MI 48109 USA Univ Michigan Dept Phys Randall Lab 450 Church St Ann Arbor MI 48109 USA Univ Michigan Dept Mech Engn Dept Biomed Engn Macromol Sci & Engn Program 2350 Hayward St Ann Arbor MI 48109 USA Univ Michigan Dept Aerosp Engn Dept Mech Engn 1320 Beal Ave Ann Arbor MI 48109 USA

ISBN: (数字)9781624107115

ISBN: (纸本)9781624107115

Crumpling, folding and introducing creases will increase the transverse stiffness of thin, elastic plates. In this study, fundamental frequency is used as a measure of the stiffness of the plate. A comprehensive study is introduced to show the effect of ordered, pyramidal crumples on the fundamental frequencies of these plates. It is observed that by introducing nine ordered creases in a square sheet of side 6in, an increase of 124% in the fundamental frequency is achieved with only a 0.5% increase in the total mass when compared to a flat plate. A structural optimization formulation is introduced to show that, under the constraints of the problem, a unique and unordered creasing in a thin plate can be obtained that maximizes the fundamental frequency of the structure. The results show a 176% increase in frequency with only 0.84% increase in mass compared to a flat sheet.

关键词： Structural optimization Artificial Neural Network MATLAB Computational Modeling Elastic Properties High Aspect Ratio Abaqus Structural Response Additive Manufacturing optimization algorithm

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Automated and Visually Interactive Navigation Analysis (AVINA) Software for Next Generation Cislunar Missions

Automated and Visually Interactive Navigation Analysis (AVIN...

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AIAA SciTech Forum

作者： Schadegg, Maximilian Doughty, Emily Hernandez, Sonia Seuber, Jill Continuum Space Syst Inc 600 Playhouse AlleySuite 400 Pasadena CA 91109 USA Australis Space Nav 6 Brierwood Pl Sydney NSW 2086 Australia

ISBN: (数字)9781624107115

ISBN: (纸本)9781624107115

This paper describes the Automated and Visually Interactive Navigation Analysis ("AVINA") software tool that allows users to evaluate navigation performance and optimize both tracking data schedules and statistical maneuver locations for a given deep space mission. The software back-end architecture, filter setup, and optimization algorithms are described. An example cislunar mission is chosen, and its user-supplied inputs and the software tool's outputs are detailed to demonstrate the capabilities of the tool.

关键词： optimization algorithm Spacecraft Mission Navigation Performance Software Tool Lunar Reconnaissance Orbiter Orbit Determination Earth Universal Space Network Monte Carlo Simulation Ground Station

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Task Scheduling optimization in Cloud Computing Based on Genetic algorithms

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Computers, Materials & Continua 2021年第12期69卷 3289-3301页

作者： Ahmed Y.Hamed Monagi H.Alkinani Faculty of Computers and Information Department of Computer ScienceSohag UniversitySohag82524Egypt Department of Computer Science and Artificial Intelligence College of Computer Science and EngineeringUniversity of JeddahJeddah21959Saudi Arabia

Task scheduling is the main problem in cloud computing that reduces system performance;it is an important way to arrange user needs and perform multiple *** computing is the most popular technology nowadays and has many research potential in various areas like resource allocation,task scheduling,security,privacy,*** improve system performance,an efficient task-scheduling algorithm is *** task-scheduling algorithms focus on task-resource requirements,CPU memory,execution time,and execution *** this paper,a task scheduling algorithm based on a Genetic algorithm(GA)has been presented for assigning and executing different *** proposed algorithm aims to minimize both the completion time and execution cost of tasks and maximize resource *** evaluate our algorithm’s performance by applying it to two examples with a different number of tasks and *** first example contains ten tasks and four processors;the computation costs are generated *** last example has eight processors,and the number of tasks ranges from twenty to seventy;the computation cost of each task on different processors is generated *** achieved results show that the proposed approach significantly succeeded in finding the optimal solutions for the three objectives;completion time,execution cost,and resource utilization.

关键词： Cloud computing task scheduling genetic algorithm optimization algorithm

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An improved deep learning model for soybean future price prediction with hybrid data preprocessing strategy

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FRONTIERS OF AGRICULTURAL SCIENCE AND ENGINEERING 2025年第2期12卷 208-230页

作者： Chen, Dingya Liu, Hui Li, Yanfei Duan, Zhu Cent South Univ Inst Artificial Intelligence & Robot IAIR Sch Traff & Transportat Engn Key Lab Traff Safety TrackMinist Educ Changsha 410075 Peoples R China Hunan Agr Univ Sch Mechatron Engn Changsha 410128 Peoples R China

The futures trading market is an important part of the financial markets and soybeans are one of the most strategically important crops in the world. How to predict soybean future price is a challenging topic being studied by many researchers. This paper proposes a novel hybrid soybean future price prediction model which includes two stages of data preprocessing and deep learning prediction. In the data preprocessing stage, futures price series are decomposed into subsequences using the ICEEMDAN (improved complete ensemble empirical mode decomposition with adaptive noise) method. The Lempel-Ziv complexity determination method was then used to identify and reconstruct high-frequency subsequences. Finally, the high frequency component is decomposed secondarily using variational mode decomposition optimized by beluga whale optimization algorithm. In the deep learning prediction stage, a deep extreme learning machine optimized by the sparrow search algorithm was used to obtain the prediction results of all subseries and reconstructs them to obtain the final soybean future price prediction results. Based on the experimental results of soybean future price markets in China, Italy, and the United States, it was found that the hybrid method proposed provides superior performance in terms of prediction accuracy and robustness.

关键词： Deep extreme learning machine hybrid data preprocessing optimization algorithm soybean future price prediction

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One-Parameter Optimal Flux Reconstruction Schemes for Adaptive Mesh Refinement

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AIAA JOURNAL 2022年第3期60卷 1440-1450页

作者： Chen, Long Zhou, Zhengyang Xia, Jian Nanjing Univ Aeronaut & Astronaut Key Lab Unsteady Aerodynam & Flow Control Nanjing 210016 Peoples R China China Acad Launch Vehicle Technol Beijing 100076 Peoples R China

High-order schemes with larger time-step limits can benefit from using adaptive mesh refinement grids. One-parameter optimal flux reconstruction schemes are obtained by minimizing the error associated with wave propagation over the range of resolvable wavenumbers using a novel objective function that accounts for the Courant-Friedrichs-Lewy limit and order of accuracy constraint. The novel schemes are parameterized by the Courant-Friedrichs-Lewy limit, which, if chosen properly, leads to the obtained optimal Courant-Friedrichs- Lewy-like well-known schemes. The schemes are obtained by the differential evolution optimization algorithm, which is combined with the flux reconstruction-discontinuous Galerkin scheme to enlarge the time step limit on adaptive mesh refinement grids. Two numerical experiments were performed to investigate the properties of the schemes, including advection of a Gaussian bump and isentropic Euler vortex. The results show that the new schemes are more suitable for adaptive mesh refinement in terms of accuracy, dissipation, and stability.

关键词： Adaptive Mesh Refinement Courant Friedrichs Lewy Advection Vortex Flow optimization algorithm Conservation Equations Data Structures Flow Velocity Inviscid Fluid Helicopters

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Analysis and optimization of a V-Shape Combined Pole Interior Permanent-Magnet Synchronous Machine With Temperature Rise and Demagnetization Considered

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IEEE ACCESS 2021年 9卷 64761-64775页

作者： Wang, Mingqiao Zhu, Haotian Zhou, Chengyu Zheng, Ping Tong, Chengde Harbin Inst Technol Sch Elect Engn & Automat Harbin 150001 Peoples R China Shanghai Aerosp Control Technol Inst Shanghai 201109 Peoples R China Harbin Inst Technol State Key Lab Robot & Syst Harbin 150001 Peoples R China

Interior permanent-magnet synchronous machines (IPMSMs) have the advantages of high efficiency, high power density and outstanding flux-weakening ability, which make them widely adopted in electric vehicles (EVs). Conventional IPMSMs using rare-earth permanent magnet (PM) materials face the problems of instable price and irreversible demagnetization under extreme operating conditions. To overcome these shortcomings, a V-shape combined pole IPMSM (VCP-IPMSM) is proposed, in which NdFeB PMs at the outer ends of V-shape pole are replaced by ferrite PMs. The improvement of the magnetic-pole scheme on air-gap flux density is analyzed, and the influences of the magnetic-pole geometries on electromagnetic performance are investigated. The thermal circuit model of VCP-IPMSM is established, and the demagnetization characteristics of the machine at different temperatures are analyzed, by which the thermal and demagnetization constraints of magnetic pole are obtained. The genetic algorithm based on response surface models is applied to optimize the magnetic-pole cost and electromagnetic torque simultaneously. Accordingly, with thermal and demagnetization constraints integrated with the optimization method, an optimum scheme is obtained. In comparison with the conventional IPMSM with single-material pole, the proposed VCP-IPMSM is proved to be able to promote the air-gap flux density quality, improve the anti-demagnetization ability at high temperature, and decrease the rare-earth PM consumption with the output torque remaining unchanged.

关键词： Magnetic flux Ferrites Demagnetization Coercive force Magnetic circuits Rotors Air gaps Combined pole V-shape pole interior permanent-magnet synchronous machine thermal circuit model demagnetization optimization algorithm

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Chaotic Local Search-Based Differential Evolution algorithms for optimization

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IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS 2021年第6期51卷 3954-3967页

作者： Gao, Shangce Yu, Yang Wang, Yirui Wang, Jiahai Cheng, Jiujun Zhou, MengChu Univ Toyama Fac Engn Toyama 9308555 Japan Sun Yat Sen Univ Dept Comp Sci Guangzhou 510275 Peoples R China Tongji Univ Key Lab Embedded Syst & Serv Comp Minist Educ Shanghai 200092 Peoples R China New Jersey Inst Technol Dept Elect & Comp Engn Newark NJ 07102 USA Macau Univ Sci & Technol Inst Syst Engn Macau Peoples R China

JADE is a differential evolution (DE) algorithm and has been shown to be very competitive in comparison with other evolutionary optimization algorithms. However, it suffers from the premature convergence problem and is easily trapped into local optima. This article presents a novel JADE variant by incorporating chaotic local search (CLS) mechanisms into JADE to alleviate this problem. Taking advantages of the ergodicity and nonrepetitious nature of chaos, it can diversify the population and thus has a chance to explore a huge search space. Because of the inherent local exploitation ability, its embedded CLS can exploit a small region to refine solutions obtained by JADE. Hence, it can well balance the exploration and exploitation in a search process and further improve its performance. Four kinds of its CLS incorporation schemes are studied. Multiple chaotic maps are individually, randomly, parallelly, and memory-selectively incorporated into CLS. Experimental and statistical analyses are performed on a set of 53 benchmark functions and four real-world optimization problems. Results show that it has a superior performance in comparison with JADE and some other state-of-the-art optimization algorithms.

关键词： optimization Chaos Convergence Sociology Statistics Logistics Search problems Chaotic local search (CLS) chaotic map differential evolution (DE) incorporation scheme optimization algorithm

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