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Mobile robot path planning method combined improved artificial potential field with optimization algorithm

High Technology Letters 2011年第2期17卷 160-165页

作者：赵杰 Yu Zhenzhong Yan Jihong Gao Yongsheng Chen Zhifeng State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin 150080 P. R. China

To overcome the shortcomings of the traditional artificial potential field method in mobile robot path planning, an improved artificial potential field model （IAPFM） was established, then a new path planning method combining the IAPFM with optimization algorithm （trust region algorithm） is proposed. Attractive force between the robot and the target location, and repulsive force between the robot and the obstacles are both converted to the potential field intensity; and filled potential field is used to guide the robot to go out of the local minimum points ; on this basis, the effect of dynamic obstacles velocity and the robot＇s velocity is consid thers and the IAPFM is established, then both the expressions of the attractive potential field and the repulsive potential field are obtained. The trust region algorithm is used to search the minimum value of the sum of all the potential field inten- sities within the movement scope which the robot can arrive in a sampling period. Connecting of all the points which hare the minimum intensity in every sampling period constitutes the global optimization path. Experiment result shows that the method can meet the real-time requirement, and is able to execute the mobile robot path planning task effectively in the dynamic environment.

关键词： trust region optimization algorithm path planning artificial potential field mobile robot potential field intensity

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Application of numerical optimisation to support engineering design 58

Application of numerical optimisation to support engineering...

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58th AIAA/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference, 2017

作者： Keskin, Akin Engineering Capability Rolls-Royce plc PO Box 31 DerbyDE24 8BJ United Kingdom

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Multi-Vth technique based on potential critical paths for NBTI effect and leakage tradeoff 13

Multi-Vth technique based on potential critical paths for NB...

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2017 13th IEEE International Conference on Electronic Measurement & Instruments (ICEMI)

作者： Zhang Yao Yi Maoxiang Wang Keke Wu Qingwu Ding Li Liang Huaguo Department of Electronic Science and Applied Physics Hefei University of Technology

ISBN: (纸本)9781509050369;9781509050352

NBTI-induced PMOS transistor aging has become an important influence factor of the circuit reliability in the current technological dimension. In this paper, Multi-Vth technique based on potential critical paths for NBTI effect and leakage tradeoff is proposed. The potential critical paths can be found at the preset timing margin and the critical gates in the potential critical paths can be replaced with the low threshold voltage type through the optimization algorithm mentioned in our paper. The experimental results on ISCAS85 benchmark circuits at 45 nm node show that the after-aging delay improvement rate is up to 12.95%, which is obviously better than the current multi-threshold voltage scheme. Simultaneously, the leakage power overhead is less. Our method is more effective for the larger circuit in the anti-aging aspect.

关键词： Negative bias temperature instability(NBTI) potential critical paths Multi-threshold voltage optimization algorithm

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Robust design of high speed natural-laminar-flow airfoil for high lift 55

Robust design of high speed natural-laminar-flow airfoil for...

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55th AIAA Aerospace Sciences Meeting

作者： Huan, Zhao Zheng-Hong, Gao Chao, Wang Yuan, Gao Northwestern Polytechnical University Xi’an city China

ISBN: (数字)9781624104473

ISBN: (纸本)9781624104473

The design of high-performance Natural-Laminar-Flow (NLF) airfoil over a range of Mach numbers and lift coefficients is demonstrated using robust design based on probabilistic approach. It is very difficult for optimization of high speed NLF airfoil to maintain laminar region and control shock formation over a range of conditions, while robust design is the perfectly efficient way. The γ-Reθt transition model is combined with the shear stress transport (SST) k-ω turbulence model to predict the transition region for a laminar-turbulent boundary layer. The Kriging surrogate model and global optimization algorithm are integrated to solve a lift-constrained drag minimization problem for NLF airfoil. The analysis of uncertainty is employed by polynomial chaos expansion, the result of single point optimization shows that the optimized airfoil holds a rooftop pressure distribution, and the upper surface of optimized airfoil maintains a laminar region of 60% chord. However, the increase of Mach number and angle of attack (AOA) may lead to shock formation on the upper surface, which will yield a drastic increase of the drag coefficient. After optimizing off-design performance over a range of Mach numbers, the drag-divergence Mach number is improved by 0.03. However, the lift coefficient curve against AOA shows a “plateau” at certain AOA above the design point, which is indicated that certain separation bubbles occur on the upper surface. Finally, a robust design over a range of Mach numbers and lift coefficients is conducted which yield an optimized airfoil with a good off-design performance. The result shows that robust design of high speed NLF airfoil for high lift should consider different uncertainty parameters simultaneously. © 2017 by the American Institute of Aeronautics and Astronautics, Inc.

关键词： Robust Design Natural Laminar Flow Airfoil Aerodynamic Force Coefficients Aerodynamic Performance Laminar Separation Bubble Surrogate Model Turbulence Models optimization algorithm Shear Stress

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A multi-population hybrid Genetic Programming System

A multi-population hybrid Genetic Programming System

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作者： Bernardo Gil Camara Galvao Universidade Nova de Lisboa

学位级别：硕士

In the last few years, geometric semantic genetic programming has incrementedits popularity, obtaining interesting results on several real life applications. Nevertheless,the large size of the solutions generated by geometric semantic geneticprogramming is still an issue, in particular for those applications in which readingand interpreting the final solution is desirable. In this thesis, a new paralleland distributed genetic programming system is introduced with the objective ofmitigating this drawback. The proposed system (called MPHGP, which stands forMulti-Population Hybrid Genetic Programming) is composed by two types of subpopulations,one of which runs geometric semantic genetic programming, whilethe other runs a standard multi-objective genetic programming algorithm that optimizes,at the same time, fitness and size of solutions. The two subpopulationsevolve independently and in parallel, exchanging individuals at prefixed synchronizationinstants. The presented experimental results, obtained on five real-lifesymbolic regression applications, suggest that MPHGP is able to find solutionsthat are comparable, or even better, than the ones found by geometric semanticgenetic programming, both on training and on unseen testing data. At the sametime, MPHGP is also able to find solutions that are significantly smaller than theones found by geometric semantic genetic programming.

关键词： Machine Learning Statistics Computational Intelligence Genetic Programming Genetic algorithm Evolutionary algorithm optimization algorithm optimization Problem Overfitting Semantic Awareness Multi-Objective System Hybrid Genetic Programming Parallel and Distributed

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Performance indices and evaluation of algorithms in building energy efficient design optimization

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ENERGY 2016年第0期114卷 100-112页

作者： Si, Binghui Tian, Zhichao Jin, Xing Zhou, Xin Tang, Peng Shi, Xing Southeast Univ Sch Architecture 2 Si Pai Lou Nanjing 210096 Jiangsu Peoples R China Minist Educ Key Lab Urban & Architectural Heritage Conservat Nanjing Jiangsu Peoples R China

Building energy efficient design optimization is an emerging technique that is increasingly being used to design buildings with better overall performance and a particular emphasis on energy efficiency. To achieve building energy efficient design optimization, algorithms are vital to generate new designs and' thus drive the design optimization process. Therefore, the performance of algorithms is crucial to achieving effective energy efficient design techniques. This study evaluates algorithms used for building energy efficient design optimization. A set of performance indices, namely, stability, robustness, validity, speed, coverage, and locality, is proposed to evaluate the overall performance of algorithms. A benchmark building and a design optimization problem are also developed. Hooke-Jeeves algorithm, Multi Objective Genetic algorithm II, and Multi-Objective Particle Swarm optimization algorithm are evaluated by using the proposed performance indices and benchmark design,problem. Results indicate that no algorithm performs best in all six areas. Therefore, when facing an energy efficient design problem, the algorithm must be carefully selected based on the nature of the problem and the performance indices that matter the most. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： optimization algorithm Performance index and evaluation Energy efficient design Building optimization

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A Novel optimization Technique to Improve Gas Recognition by Electronic Noses Based on the Enhanced Krill Herd algorithm

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SENSORS 2016年第8期16卷 1275-1275页

作者： Wang, Li Jia, Pengfei Huang, Tailai Duan, Shukai Yan, Jia Wang, Lidan Southwest Univ Coll Elect & Informat Engn Chongqing 400715 Peoples R China

An electronic nose (E-nose) is an intelligent system that we will use in this paper to distinguish three indoor pollutant gases (benzene (C6H6), toluene (C7H8), formaldehyde (CH2O)) and carbon monoxide (CO). The algorithm is a key part of an E-nose system mainly composed of data processing and pattern recognition. In this paper, we employ support vector machine (SVM) to distinguish indoor pollutant gases and two of its parameters need to be optimized, so in order to improve the performance of SVM, in other words, to get a higher gas recognition rate, an effective enhanced krill herd algorithm (EKH) based on a novel decision weighting factor computing method is proposed to optimize the two SVM parameters. Krill herd (KH) is an effective method in practice, however, on occasion, it cannot avoid the influence of some local best solutions so it cannot always find the global optimization value. In addition its search ability relies fully on randomness, so it cannot always converge rapidly. To address these issues we propose an enhanced KH (EKH) to improve the global searching and convergence speed performance of KH. To obtain a more accurate model of the krill behavior, an updated crossover operator is added to the approach. We can guarantee the krill group are diversiform at the early stage of iterations, and have a good performance in local searching ability at the later stage of iterations. The recognition results of EKH are compared with those of other optimization algorithms (including KH, chaotic KH (CKH), quantum-behaved particle swarm optimization (QPSO), particle swarm optimization (PSO) and genetic algorithm (GA)), and we can find that EKH is better than the other considered methods. The research results verify that EKH not only significantly improves the performance of our E-nose system, but also provides a good beginning and theoretical basis for further study about other improved krill algorithms' applications in all E-nose application areas.

关键词： EKH electronic nose optimization algorithm decision weighting factor indoor pollutant gas

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Semi-Inverse Design optimization Method for Film-Cooling Arrangement of High-Pressure Turbine Vanes

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JOURNAL OF PROPULSION AND POWER 2016年第3期32卷 659-673页

作者： Chi, Zhongran Liu, Haiqing Zang, Shusheng Shanghai Jiao Tong Univ Sch Mech Engn Shanghai 200240 Peoples R China Chinese Acad Sci Shanghai Adv Res Inst Shanghai 201210 Peoples R China

A semi-inverse design optimization method for the film-cooling arrangement of high-pressure turbine first-stage vanes is initiated based on a combinatorial optimization algorithm, a one-dimensional heat conduction model, and computational fluid dynamics methods, in which inlet temperature distortion, radiation, and inlet swirl are all considered simultaneously. This semi-inverse design optimization method can optimize the total coolant amount of the film-cooling structure while ensuring an acceptable metal temperature distribution, which finally provides a scattered and nonuniform arrangement of the film-cooling holes and a minimal coolant amount. The optimization methodology is tested on the General Electric energy-efficient engine first-stage vane under a high thermal load, and the optimization result is verified by the conjugate heat transfer computational fluid dynamics simulations. As for the optimized cooling structure, a significant improvement of cooling performance is observed while the total coolant amount is slightly reduced compared with the prototype. It is also found that neglecting each of the three factors (inlet temperature distortion, radiation, and inlet swirl) could result in a significantly different film-cooling arrangement while maintaining the overall cooling performance, which highlights the capability of the semi-inverse design optimization method at various design conditions.

关键词： Convective Cooling Turbine Inlet Temperature Computational Fluid Dynamics Simulation Coolant Heat Transfer Coefficients Wall Temperature Temperature Distribution optimization algorithm Numerical Modeling Mass Flow

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algorithm for optimal well placement in geothermal systems based on TOUGH2 models

Algorithm for optimal well placement in geothermal systems b...

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作者： Dagur Helgason Reykjavik University

学位级别：硕士

In a world of ever increasing use of renewables geothermal has lagged behind and has seen little growth compared to other renewables due in part to its high capital cost. Geothermal wells account for about a third of the capital cost and it is therefore important to ensure the highest possible success rate and value creation from these wells. In order to address this, an algorithm has been developed that utilizes a numerical TOUGH2 model of a geothermal system to evaluate the optimal well placement based on a net present value estimation. The algorithm was tested using a hypothetical model and found the optimal wells to be in the hottest parts of the model at depth and in the upper heat zone, directly above the heat source in both cases. The algorithm was also subjected to a sensitivity and processing time analysis with the hypothetical model as an input model. The sensitivity analysis showed that the models results were most sensitive to changes in reinjection enthalpy, discount rate and the power plants thermal efficiency. The processing time analysis showed that the algorithm can potentially be run in a reasonable enough time to serve as a tool for decision making.

关键词： Geothermal TOUGH2 optimization algorithm well placement reservoir engineering

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Geometric Approach to the Perpendicular Thrust Case for Trajectory optimization

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JOURNAL OF GUIDANCE CONTROL AND DYNAMICS 2016年第5期39卷 1059-1068页

作者： Iorfida, E. Palmer, P. L. Roberts, M. Univ Surrey Surrey Space Ctr Fac Engn & Phys Sci Guildford GU2 7XH Surrey England Univ Surrey Dept Math Fac Engn & Phys Sci Guildford GU2 7XH Surrey England African Inst Math Sci POB 176 Bagamoyo Pwani Tanzania

For the case of impulsive thrust trajectories, Lawden's primer vector theory gives a set of necessary conditions that determines if intermediate impulses have to be applied in order to obtain a fuel optimal trajectory. In this paper, a novel approach is presented in which, through the representation of the primer vector in polar coordinates, a separation of the in-plane and out-of-plane components occurs. This procedure gives a complete analytic solution for the out-of-plane component of the primer vector, which is shown to be independent of the semimajor axis of the transfer orbit. In the case where the initial and final thrusts are both perpendicular to the orbital plane, the optimality of the transfer arc is fully analyzed. The analytic correlations between the boundary conditions on the transfer orbit and the profile of the primer vector are derived. In particular, the novel approach allows the development of a simple procedure based on a graphical representation from which, given only the initial and final position vectors, the optimality of the transfer orbit can be determined.

关键词： Thrust Trajectory optimization Deep Space Maneuver Polar Coordinate System Boundary Value Problems Orbital Elements Propellant Earth Interplanetary Trajectories optimization algorithm

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