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Optimization of Monopod Offshore Tower under Uncertainties with Gradient-Based and Gradient-Free Optimization Algorithms

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ADVANCES IN STRUCTURAL ENGINEERING 2012年第12期15卷 2021-2032页

作者： Togan, Vedat Karadeniz Tech Univ Dept Civil Engn Trabzon Turkey

In the RBDO applications which include a reliability analysis and an optimization algorithm, sequential quadratic programming (SQP) is frequently used for the optimization. In this work, in addition to SQP, some heuristic algorithms such as Simulating Annealing (SA), Genetic Algorithms (GA) and Harmony Search (HS) are employed as optimization methods to demonstrate the performance, accuracy and efficiency of the corresponding methods in the RBDO process. The probabilistic constraints are evaluated by using Reliability Index Approach (RIA). The optimum design of a monopod offshore tower is presented as a numerical example to show the applicability of the proposed algorithm. Graphical and tabular forms are proposed to compare the efficiency of the optimization methods used in the Reliability Based Design Optimization (RBDO) process. As a result, heuristic algorithms exhibit good performance although they call many function evaluations including constraints and objective functions.

关键词： reliability-based optimization sequential quadratic programming heuristic algorithms offshore towers

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Optimization of an Occulter-Based Extrasolar-Planet-Imaging Mission

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JOURNAL OF GUIDANCE CONTROL AND DYNAMICS 2012年第1期35卷 172-185页

作者： Kolemen, Egemen Kasdin, N. Jeremy Princeton Plasma Phys Lab Princeton NJ 08543 USA Princeton Univ Mech & Aerosp Dept Princeton NJ 08544 USA

A novel approach to extrasolar-planet imaging uses a pair of satellites: a telescope and an occulter, where the latter is placed in the line of sight between the telescope and the star system to be imaged in order to enhance the telescope's imaging capability. The optimal configuration of this satellite formation around sun-Earth L2 halo orbits is studied. Trajectory optimization of the occulter motion between imaging sessions of different stars is performed using a range of different criteria and methods. Thus, the global optimization problem is transformed into a time-dependent traveling salesman problem. The time-dependent traveling salesman problem is augmented with various constraints that arrive from the mission, and this problem is solved by employing simulated annealing and branching algorithms. For a concrete understanding of the feasibility of the mission, the performance of an example spacecraft, the Small Missions for Advanced Research in Technology (SMART-1), is analyzed.

关键词： Earth Telescopes Small Missions for Advanced Research in Technology Trajectory Optimization Annealing Halo Orbit sequential quadratic programming Planetary Systems Fuel Consumption Terrestrial Planet Finder

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De Saint-Venant equations-based model assessment in model predictive control of open channel flow

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ADVANCES IN WATER RESOURCES 2012年第Dec.期49卷 37-45页

作者： Xu, M. Negenborn, R. R. van Overloop, P. J. van de Giesen, N. C. Delft Univ Technol Fac Civil Engn & Geosci Sect Water Resources Management NL-2628 CN Delft Netherlands Delft Univ Technol Fac Mech Maritime & Mat Engn Sect Marine & Transport Technol NL-2628 CD Delft Netherlands

Model predictive control (MPC) is a model-based control technique that uses an optimization algorithm to generate optimal control actions. Based on the model used in optimization, MPC approaches can be categorized as linear or nonlinear. Both classes have advantages and disadvantages in terms of control accuracy and computational time. A typical linear model in open channel water management is the Integrator Delay (ID) model, while a nonlinear model usually refers to the Saint-Venant equations. In earlier work, we proposed the use of linearized Saint-Venant equations for MPC, where the model is formulated in a linear time-varying format and time-varying parameters are estimated outside of the optimization. quadratic programming (QP) is used to solve the optimization problem. However, the control accuracy of such an MPC scheme is not clear. In this paper, we compare this approach with an MPC scheme that uses sequential quadratic programming (SQP) to solve the optimization problem. Because the estimation of the time-varying parameters is integrated in the optimization in SQP, the solutions from SQP-based MPC are expected to be superior to the solutions of QP-based approach. However, SQP can be computationally expensive. A simulation experiment illustrates that the QP-based MPC approach using a linearized Saint-Venant model has an accurate approximation of the control performance of SQP. Crown Copyright (C) 2012 Published by Elsevier Ltd. All rights reserved.

关键词： Model predictive control quadratic programming Open channel flow sequential quadratic programming Saint-Venant equations

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Optimisation of cutting conditions in machining of cobalt-based refractory material

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INTERNATIONAL JOURNAL OF MATERIALS & PRODUCT TECHNOLOGY 2012年第1-2期44卷 127-143页

作者： Lebaal, N. Schlegel, D. Folea, M. Univ Technol Belfort Montbeliard Res Inst Transportat Energy & Soc IRTES Mechatron Methods Models & Skills Lab M3M EA3318 F-90010 Belfort France Ecole Super Technol & Affaires F-90000 Belfort France Fac Technol Engn Dept Mfg Engn Brasov 2200 Romania

Milling a cobalt-based refractory material has been very little studied being proved to be very expensive due to rapid toolwear. The aim of this work was cost optimisation of cutting conditions in slot milling with carbide tools. It was used a Kriging interpolation technique of search space that avoids the local optima and decreases the function evaluation toward the global minimum. The objective and constraint functions taken into account were tool cost and surface roughness. Experimental results showed that optimal cutting conditions still led to an important abrasion of the tool, but minimised the adhesive wear at lower cutting speeds.

关键词： machining refractory material design of experiment optimisation response surface method RSM kriging sequential quadratic programming SQP

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Shape-based retrieval and analysis of 3D models using fuzzy weighted symmetrical depth images

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NEUROCOMPUTING 2012年 89卷 114-121页

作者： Zou, Kuan-Sheng Chan, Chee-Kooi Peng, Si-Xiang Luximon, Ameersing Chen, Zeng-Qiang Ip, Wai-Hung Nankai Univ Dept Automat Tianjin 300071 Peoples R China Hong Kong Polytech Univ Inst Text & Clothing Hong Kong Hong Kong Peoples R China Hong Kong Polytech Univ Dept Ind & Syst Engn Hong Kong Hong Kong Peoples R China

With the rapid development of 3D scanners, graphic accelerated hardware and 3D modeling tools, the application of 3D model databases is growing in both numbers and sizes, e.g. 3D body scans, head model and virtual mannequins. There is a pressing need for effective content-based 3D model retrieval methods. In this paper, a novel 3D model retrieval approach is proposed by using the Fuzzy Weighted Symmetrical Depth Images (FW-SDI). Firstly, three symmetrical planes of the 3D model are obtained based upon principal plane analysis and sequential quadratic programming, which are the distinctive characteristics of 3D model and perpendicular to each other. Secondly, three novel depth Images (NDI) and three depth differential images (DDI) are extracted by projecting the 3D surface to the proposed symmetrical planes. The Fourier descriptors of the novel depth Images and depth differential images are calculated. Finally, a fuzzy weighted procedure is conducted for combining the Fourier descriptors of NDI and DDI. Experiment results show that the proposed method can achieve better retrieval performance than others. (c) 2012 Elsevier B.V. All rights reserved.

关键词： Shape based retrieval Virtual mannequin Principal plane analysis sequential quadratic programming Fuzzy weighted

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Performance of an Autonomous Multi-Maneuver Algorithm for Lunar Trans-Earth Injection

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JOURNAL OF SPACECRAFT AND ROCKETS 2012年第1期49卷 165-174页

作者： Whitley, Ryan J. Ocampo, Cesar A. Williams, Jacob NASA Johnson Space Ctr Houston TX 77068 USA Univ Texas Austin Dept Aerosp Engn & Engn Mech Austin TX 78712 USA ERC Inc ESCG Houston TX 77058 USA

Using a fully analytic initial estimate, a self-starting algorithm that constructs a flyable multiburn maneuver sequence to transfer a spacecraft from a closed low-lunar parking orbit to a desired Earth-entry state is developed and implemented. The algorithm is built to support the need for a human spacecraft to abort anytime during the mission and return automatically from a variety of lunar mission scenarios. This study presents a large set of representative test cases for algorithm evaluation, including highly constrained Earth-entry interface states that return the spacecraft to a specific landing site. For all cases, an optimal finite-burn solution is obtained successfully in computation time suitable for real-time on-board operation.

关键词： Trans Earth Injection Earth Propellant Elliptical Orbit Flight Path Angle sequential quadratic programming Lift to Drag Ratio Thrust to Weight Ratio Algorithm Performance Search Algorithm

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A second-derivative SQP method with a 'trust-region-free' predictor step

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IMA JOURNAL OF NUMERICAL ANALYSIS 2012年第2期32卷 580-601页

作者： Gould, Nicholas I. M. Robinson, Daniel P. Univ Oxford Inst Math Oxford OX1 3LB England Rutherford Appleton Lab Computat Sci & Engn Dept Didcot OX11 0QX Oxon England

Gould and Robinson (2010, SIAM J. Optim., 20, 2023-2048;2010, SIAM J. Optim., 20, 2049-2079) introduced a second-derivative sequential quadratic programming method (S2QP) for solving nonlinear nonconvex optimization problems. We proved that the method is globally and locally superlinearly convergent under common assumptions. A critical component of the algorithm is the so-called predictor step, which is computed from a strictly convex quadratic program with a trust-region constraint. This step is essential for proving global convergence but its propensity to identify the optimal active set is paramount for achieving fast local convergence. Thus the global and local efficiency of the method is intimately coupled with the quality of the predictor step. In this paper we study the effects of removing the trust-region constraint from the computation of the predictor step. This is reasonable since the resulting problem is still strictly convex and thus well defined. Although it is interesting theoretically to verify that the same convergence guarantees hold when no trust-region constraint is used, our motivation is based on the practical behaviour of the algorithm. Preliminary numerical experience with S2QP indicates that the trust-region constraint occasionally degrades the quality of the predictor step and diminishes its ability to correctly identify the optimal active set. Moreover, removal of the trust-region constraint allows for re-use of the predictor step over a sequence of failed iterations, thus reducing computation. We show that the modified algorithm remains globally convergent and preserves local superlinear convergence provided that a nonmonotone strategy is incorporated.

关键词： nonlinear programming nonlinear inequality constraints sequential quadratic programming l(1)-penalty function nonsmooth optimization

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Neural Network-Based Trajectory Optimization for Unmanned Aerial Vehicles

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JOURNAL OF GUIDANCE CONTROL AND DYNAMICS 2012年第2期35卷 548-562页

作者： Horn, Joseph F. Schmidt, Eric M. Geiger, Brian R. DeAngelo, Mark P. Penn State Univ University Pk PA 16802 USA Piasecki Aircraft Corp Unmanned Aerial Vehicle Projects & Controls Essington PA 19029 USA

A direct trajectory optimization method that uses neural network approximation methods is presented. Neural networks are trained to approximate objective functions and vehicle dynamics. The neural network method reduces computational requirements by removing the need for collocation and providing fast computation of gradients when compared with direct and pseudospectral collocation methods. The method is shown to significantly reduce computational costs while resulting in trajectories comparable to those produced by direct collocation and pseudospectral methods. Because a neural network readily provides accurate computation of gradients, it removes the need for formulating analytical gradients;thus, the method is more easily extended to different types of applications with different objective functions and constraints. This paper demonstrates the flexibility of the neural network trajectory optimization approach through simulation of three cases: a single unmanned aerial vehicle operating a fixed camera, multiple unmanned aerial vehicles operating fixed cameras, and a single unmanned aerial vehicle operating a gimballed camera. The method's ability to produce tightly constrained trajectories is also demonstrated.

关键词： Trajectory Optimization Feedforward Neural Network UAV Chebyshev Pseudospectral Method Collocation Method Nonlinear programming MATLAB Bank Angle True Airspeed sequential quadratic programming

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ANN - SQP Approach For NOx Emission Reduction In Coal Fired Boiler

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INTERNATIONAL JOURNAL OF EMERGING ELECTRIC POWER SYSTEMS 2012年第3期13卷 1-14页

作者： Balamurugan, Ilamathi Gounder, Selladurai V. Kulendran, Balamurugan Tamilnadu Generat & Distribut Corp Ltd Hydro Training Inst Madras Tamil Nadu India Coimbatore Inst Technol Coimbatore Tamil Nadu India Inst Rd & Transport Technol Erode Tamil Nadu India

In this research paper, predictive modelling of NOx emission of a 210 MW capacity pulverized coal-fired boiler and combustion parameter optimization to reduce NOx emission in flue gas is proposed. The effects of oxygen concentration in flue gas, coal properties, coal flow, boiler load, air distribution scheme, flue gas outlet temperature and nozzle tilt were studied. The data collected from parametric field experiments were used to build a feed-forward back-propagation artificial neural net (ANN). The coal combustion parameters were used as inputs and NOx emission as outputs of the model. The ANN model was developed for full load condition and its predicted values were verified with the actual values. The algebraic equation containing weights and biases of the trained net was used as fitness function in sequential quadratic programming (SQP) to find the optimum level of input operating conditions for low NOx emission. The results proved that the proposed approach could be used for generating feasible operating conditions.

关键词： coal environmental studies neural networks sequential quadratic programming optimization

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Optimal trajectory planning for industrial robot along a specified path with payload constraint using trigonometric splines

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INTERNATIONAL JOURNAL OF AUTOMATION AND CONTROL 2012年第1期6卷 39-65页

作者： Chiddarwar, Shital S. Babu, N. Ramesh Indian Inst Technol Madras Dept Mech Engn Mfg Engn Sect Chennai 600036 Tamil Nadu India

This paper presents a general methodology for the offline planning of trajectory of a six axis serial robot along a specified path. The objective of trajectory planning is to minimise a cost function when subjected to joint angles, joint velocities, acceleration, jerks, torques and gripping force constraints by considering dynamic of the robot. A trigonometric spline is used to represent the trajectory. This non-linear constrained optimisation problem consists of 6 objectives, 67 constraints and 48 variables. The cost function is a weighted balance of travelling time, actuator torques, singularity avoidance, joint jerks, joint accelerations and gripping force. The optimisation problem is solved by using two methods, namely sequential quadratic programming and genetic algorithm. The proposed methodology is implemented for trajectory planning of six degree of freedom industrial robot and results obtained with two optimisation techniques are compared.

关键词： optimal trajectory planning SQP sequential quadratic programming trigonometric spline multi-objective optimisation GA genetic algorithm

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