Trajectory Optimization Applied to Space Rendezvous

2013 ◽  
Vol 756-759 ◽  
pp. 3466-3470
Author(s):  
Xu Min Song ◽  
Qi Lin
Keyword(s):  
Simulated Annealing ◽  
Optimization Model ◽  
Trajectory Optimization ◽  
Optimization Problem ◽  
Optimization Method ◽  
Nonlinear Constraints ◽  
Design Variables ◽  
Adaptive Simulated Annealing ◽  
Simulation Results

The trajcetory plan problem of spece reandezvous mission was studied in this paper using nolinear optimization method. The optimization model was built based on the Hills equations. And by analysis property of the design variables, a transform was put forward , which eliminated the equation and nonlinear constraints as well as decreaseing the problem dimensions. The optimization problem was solved using Adaptive Simulated Annealing (ASA) method, and the rendezvous trajectory was designed.The method was validated by simulation results.

scholarly journals Trajectory optimization of UAV based on Hp-adaptive Radau pseudospectral method

2021 ◽  
Vol 0 (0) ◽  
pp. 0
Author(s):  
Yi Cui ◽  
Xintong Fang ◽  
Gaoqi Liu ◽  
Bin Li
Keyword(s):  
Trajectory Planning ◽  
Trajectory Optimization ◽  
Optimization Problem ◽  
Tracking Error ◽  
Pseudospectral Method ◽  
Planning Problem ◽  
A Algorithm ◽  
Planning Scheme ◽  
Path Search ◽  
Simulation Results

<p style='text-indent:20px;'>Unmanned Aerial Vehicles (UAVs) have been extensively studied to complete the missions in recent years. The UAV trajectory planning is an important area. Different from the commonly used methods based on path search, which are difficult to consider the UAV state and dynamics constraints, so that the planned trajectory cannot be tracked completely. The UAV trajectory planning problem is considered as an optimization problem for research, considering the dynamics constraints of the UAV and the terrain obstacle constraints during flight. An hp-adaptive Radau pseudospectral method based UAV trajectory planning scheme is proposed by taking the UAV dynamics into account. Numerical experiments are carried out to show the effectiveness and superior of the proposed method. Simulation results show that the proposed method outperform the well-known RRT* and A* algorithm in terms of tracking error.</p>

scholarly journals A trajectory design method for RLV via artificialmemory-principle optimization

2018 ◽  
Vol 189 ◽  
pp. 10019
Author(s):  
Hao Li ◽  
Changzhu Wei
Keyword(s):  
Trajectory Optimization ◽  
Optimization Problem ◽  
Optimization Problems ◽  
Memory Cell ◽  
Optimization Method ◽  
Alternative Solution ◽  
Trajectory Design ◽  
Memory State ◽  
Artificial Memory

A trajectory optimization method for RLV based on artificial memory principles is proposed. Firstly the optimization problem is modelled in Euclidean space. Then in order to solve the complicated optimization problem of RLV in entry phase, Artificial-memory-principle optimization (AMPO) is introduced. AMPO is inspired by memory principles, in which a memory cell consists the whole information of an alternative solution. The information includes solution state and memory state. The former is an evolutional alternative solution, the latter indicates the state type of memory cell: temporary, short-and long-term. In the evolution of optimization, AMPO makes a various search (stimulus) to ensure adaptability, if the stimulus is good, memory state will turn temporary to short-term, even long-term, otherwise it not. Finally, simulation of different methods is carried out respectively. Results show that the method based on AMPO has better performance and high convergence speed when solving complicated optimization problems of RLV.

scholarly journals A Multi-Level Optimization Method for Elastic Constants Identification of Composite Laminates

2019 ◽  
Vol 9 (20) ◽  
pp. 4267
Author(s):  
Chien Yang Huang ◽  
Tai Yan Kam
Keyword(s):  
Optimal Design ◽  
Elastic Constants ◽  
Composite Laminates ◽  
Composite Laminate ◽  
Optimization Problem ◽  
Optimization Method ◽  
Global Minimization ◽  
Minimization Problems ◽  
Design Variables ◽  
Multi Level

A new and effective elastic constants identification technique is presented to extract the elastic constants of a composite laminate subjected to uniaxial tensile testing. The proposed technique consists of a new multi-level optimization method that can solve different types of minimization problems, including the extraction of material constants of composite laminates from given strains. In the identification process, the optimization problem is solved by using a stochastic multi-start dynamic search minimization algorithm at the first level in order to obtain the statistics of the quasi-optimal design variables for a set of randomly generated starting points. The statistics of the quasi-optimal elastic constants obtained at this level are used to determine the reduced feasible region in order to formulate the second-level optimization problem. The second-level optimization problem is then solved using the particle swarm algorithm in order to obtain the statistics of the new quasi-optimal elastic constants. The iteration process between the first and second levels of optimization continues until the standard deviations of the quasi-optimal design variables at any level of optimization are less than the prescribed values. The proposed multi-level optimization method, as well as several existing global optimization algorithms, is used to solve a number of well-known mathematical minimization problems to verify the accuracy of the method. For the adopted numerical examples, it has been shown that the proposed method is more efficient and effective than the adopted global minimization algorithms to produce the exact solutions. The proposed method is then applied to identify four elastic constants of a [0°/±45°]s composite laminate using three strains in 0°, 45°, and 90° directions, respectively, of the composite laminate subjected to uniaxial testing. For comparison purposes, several existing global minimization techniques are also used to solve the elastic constants identification problem. Again, it has been shown that the proposed method is capable of producing more accurate results than the adopted available methods. Finally, experimental data are used to demonstrate the applications of the proposed method.

Optimization of Highly Loaded Fan Rotor Based on Throughflow Model

2007 ◽  
Author(s):  
Hong Wu ◽  
Qiushi Li ◽  
Sheng Zhou
Keyword(s):  
Mass Flow ◽  
Total Pressure ◽  
Pressure Ratio ◽  
Optimization Method ◽  
Design Variables ◽  
Adaptive Simulated Annealing ◽  
Throughflow Model ◽  
Important Design ◽  
Total Pressure Ratio ◽  
Highly Loaded

This paper presents an optimization method for fan/compressor which couples throughflow model solving axisymmetric Euler equations with adaptive simulated annealing (ASA) algorithm. One of the advantages of this optimization method is that it spends much less time than 3D optimization due to the rapid solving of throughflow model. In addition, the optimization space is quite extensive because more design variables can be adjusted in throughflow phase, such as swirl distribution, hub curve and sweep. To validate this optimization method, a highly loaded fan rotor with pressure ratio of 3.06 as a baseline is optimized. During the optimization process, the objective function is total pressure ratio, moreover, mass flow and efficiency are selected as the constraint conditions. Three important design variables including swirl distribution, hub curve and sweep are parameterized using Bezier curve, and then optimized in throughflow model independently, finally the optimum designs are validated using 3D viscous CFD solver. It is shown that pressure ratio and rotor loading can be improved further through optimizing swirl distribution, however, hub and sweep curves take more effects on mass flow and efficiency respectively. The optimization results demonstrate the advantage and feasibility of this optimization method.

Assignment and layout integration optimization for simplified satellite re-entry module component layout

2017 ◽  
Vol 233 (12) ◽  
pp. 4287-4301 ◽  
Author(s):  
Zhi-Zheng Xu ◽  
Chong-Quan Zhong ◽  
Hong-Fei Teng
Keyword(s):  
Evolutionary Algorithm ◽  
Optimization Model ◽  
Optimization Problem ◽  
Optimization Method ◽  
Layout Design ◽  
Layout Optimization ◽  
Optimization Process ◽  
Supporting Surface ◽  
Computational Performance ◽  
Component Layout

Previous studies of satellite module component (equipment) layout optimization usually initialized a component assignment in the initialization stage, which kept constant in following optimization process. The invariable component assignment will restrict the further improvement in layout optimization. To overcome this deficiency, an assignment and layout integration optimization method is presented for multi-module or supporting surface satellite module component layout design. The assignment and layout integration optimization model and the component reassignment model are built. The component reassignment model is solved by algorithms with new heuristic rule, and the integration optimization model itself is solved by evolutionary algorithm. The purpose of this article is to improve the computational performance of algorithms for multi-module or supporting surface satellite module component layout optimization. The proposed method is applied to a simplified satellite re-entry module component layout optimization problem to illustrate its effectiveness.

An Optimization Method for Design of Subambient Pressure Shaped Rail Sliders

1999 ◽  
Vol 121 (3) ◽  
pp. 575-580 ◽  
Author(s):  
Dong-Hoon Choi ◽  
Tae-Sik Kang
Keyword(s):  
Design Methodology ◽  
Optimization Method ◽  
Flying Height ◽  
Air Bearing ◽  
Bearing Surface ◽  
Programming Technique ◽  
Design Synthesis ◽  
Method Of Feasible Directions ◽  
Design Variables ◽  
Simulation Results

This study proposes a design methodology for determining configurations of subamient pressure shaped rail sliders by using a nonlinear programming technique in order to meet the desired flying characteristics over the entire recording band. The desired flying characteristics considered in this study are to minimize the variation in flying height from a target value, to keep the pitch angle within a suitable range, and to ensure that the outside rail flies lower than the inside rail even with the roll distribution due to manufacturing process. The design variables selected are recess depth, geometry of the air bearing surface, and pivot location in the transverse direction of the slider. The method of feasible directions in Automated Design Synthesis (ADS) is utilized to automatically find the optimum design variables which simultaneously meet all the desired flying characteristics. To validate the suggested design methodology, a computer program is developed and applied to a 30 percent/15 nm twin rail slider and a 30 percent/15 nm tri-rail slider. Simulation results for both sliders demonstrated the effectiveness of the proposed design methodology by showing that the flying characteristics of the optimally designed sliders are enhanced in comparison with those of the initial ones.

The Response Surface Single Loop Reliability-Based Design Optimization Method With Reliability Requirement on System Failure

2016 ◽  
Author(s):  
Rami Mansour ◽  
Mårten Olsson
Keyword(s):  
Design Optimization ◽  
Response Surface ◽  
Optimization Problem ◽  
Optimization Method ◽  
Reliability Based Design Optimization ◽  
Single Loop ◽  
Reliability Based Design ◽  
Design Variables ◽  
Reliability Method ◽  
Deterministic Solution

In reliability-based design optimization (RBDO), an optimal design which minimizes an objective function while satisfying a number of probabilistic constraints is found. As opposed to deterministic optimization, statistical uncertainties in design variables and design parameters have to be taken into account in the design process in order to achieve a reliable design. In the most widely used RBDO approaches, the First-Order Reliability Method (FORM) is used in the probability assessment. This involves locating the Most Probable Point (MPP) of failure, or the inverse MPP, either exactly or approximately. If exact methods are used, an optimization problem has to be solved, typically resulting in computationally expensive double loop or decoupled loop RBDO methods. On the other hand, locating the MPP approximately typically results in highly efficient single loop RBDO methods since the optimization problem is not necessary in the probability assessment. However, since all these methods are based on FORM, which in turn is based on a linearization of the deterministic constraints at the MPP, they may suffer inaccuracies associated with neglecting the nonlinearity of deterministic constraints. In a previous paper presented by the authors, the Response Surface Single Loop (RSSL) Reliability-based design optimization method was proposed. The RSSL-method takes into account the non-linearity of the deterministic constraints in the computation of the probability of failure and was therefore shown to have higher accuracy than existing RBDO methods. The RSSL-method was also shown to have high efficiency since it bypasses the concept of an MPP. In RSSL, the deterministic solution is first found by neglecting uncertainties in design variables and parameters. Thereafter quadratic response surface models are fitted to the deterministic constraints around the deterministic solution using a single set of design of experiments. The RBDO problem is thereafter solved in a single loop using a closed-form second order reliability method (SORM) which takes into account all elements of the Hessian of the quadratic constraints. In this paper, the RSSL method is used to solve the more challenging system RBDO problems where all constraints are replaced by one constraint on the system probability of failure. The probabilities of failure for the constraints are assumed independent of each other. In general, system reliability problems may be more challenging to solve since replacing all constraints by one constraint may strongly increase the non-linearity in the optimization problem. The extensively studied reliability-based design for vehicle crash-worthiness, where the provided deterministic constraints are general quadratic models describing the system in the whole region of interest, is used to demonstrate the capabilities of the RSSL method for problems with system reliability constraints.

scholarly journals DESIGNING NETWORK OF CITY PUBLIC TRANSPORT ON THE BASIS OF ADDITIVE METHOD

2020 ◽  
Vol 2020 (1) ◽  
pp. 158-162
Author(s):  
Ol'ga Lebedeva
Keyword(s):  
Public Transport ◽  
Optimization Model ◽  
Design Problem ◽  
Optimization Problem ◽  
Optimization Process ◽  
Economic Criterion ◽  
Special Software ◽  
Urban Public Transport ◽  
Simulation Results ◽  
Entire Network

The article describes the main features of the optimization model, which can be used to design a network of urban public transport. Design tasks can be solved using a model that allows you to redesign a part of the network or the entire network as a whole. The model consists of an additive procedure in which the decision to include a route in the network or increase the interval of movement is based on an economic criterion - an estimate of the Lagrange multiplier for the optimization problem. The main advantage of the model is that the design problem is solved only through the optimization process. The optimization process remains understandable, and the model does not require the use of special software. The simulation results are given in the article.

scholarly journals Optimizing Virtual Private Network Design Using a New Heuristic Optimization Method

2012 ◽  
Vol 2012 ◽  
pp. 1-9 ◽  
Author(s):  
Hongbing Lian ◽  
András Faragó
Keyword(s):  
Genetic Algorithm ◽  
Simulated Annealing ◽  
Design Optimization ◽  
Optimization Problem ◽  
Optimization Methods ◽  
Optimization Method ◽  
Virtual Private Network ◽  
Successful Model ◽  
Search Speed ◽  
Private Network

In virtual private network (VPN) design, the goal is to implement a logical overlay network on top of a given physical network. We model the traffic loss caused by blocking not only on isolated links, but also at the network level. A successful model that captures the considered network level phenomenon is the well-known reduced load approximation. We consider here the optimization problem of maximizing the carried traffic in the VPN. This is a hard optimization problem. To deal with it, we introduce a heuristic local search technique called landscape smoothing search (LSS). This study first describes the LSS heuristic. Then we introduce an improved version called fast landscape smoothing search (FLSS) method to overcome the slow search speed when the objective function calculation is very time consuming. We apply FLSS to VPN design optimization and compare with well-known optimization methods such as simulated annealing (SA) and genetic algorithm (GA). The FLSS achieves better results for this VPN design optimization problem than simulated annealing and genetic algorithm.

A recursive implementation of the ALIENOR optimization method

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Daniele Peri
Keyword(s):  
Design Methodology ◽  
Large Scale ◽  
Optimization Problem ◽  
Design Space ◽  
Optimization Method ◽  
Fine Tuning ◽  
Content Type ◽  
Design Variables ◽  
Scale Optimization ◽  
Similar Paper

PurposeA recursive scheme for the ALIENOR method is proposed as a remedy for the difficulties induced by the method. A progressive focusing on the most promising region, in combination with a variation of the density of the alpha-dense curve, is proposed.Design/methodology/approachALIENOR method is aimed at reducing the space dimensions of an optimization problem by spanning it by using a single alpha-dense curve: the curvilinear abscissa along the curve becomes the only design parameter for any design space. As a counterpart, the transformation of the objective function in the projected space is much more difficult to tackle.FindingsA fine tuning of the procedure has been performed in order to identity the correct balance between the different elements of the procedure. The proposed approach has been tested by using a set of algebraic functions with up to 1,024 design variables, demonstrating the ability of the method in solving large scale optimization problem. Also an industrial application is presented.Originality/valueIn the knowledge of the author there is not a similar paper in the current literature.

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