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检索条件"主题词=Sequential Quadratic Programming"

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Neuro-Evolutionary Control for Optimal Dynamic Soaring

Neuro-Evolutionary Control for Optimal Dynamic Soaring

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AIAA Science and Technology Forum and Exposition (AIAA SciTech)

作者： Perez, Ruben E. Arnalt, Jose Jansen, Peter W. Royal Mil Coll Canada Dept Mech & Aerosp Engn Kingston ON K7K 7B4 Canada

ISBN: (数字)9781624105951

ISBN: (纸本)9781624105951

Dynamic soaring is a flying technique that extracts energy from purely horizontal winds and their vertical wind gradients and represents one of the specific strategies that is utilized by birds to minimize energy expenditure during flight. Dynamic soaring cycles allow for persistent flight in a specific area making it of particular interest in application to Small Unmanned Aerial Vehicles (SUAVs). Most trajectory studies in dynamic soaring rely on direct methods to solve the trajectory optimization problem, which do not guarantee robustness to exogenous changes, such as wind profiles variations, for practical implementation on SUAVs. In this paper we introduce the use of an Neuro Evolution of Augmented Topologies (NEAT) algorithm which evolves a neural network control structure for optimal dynamic soaring flight trajectories. Compared to existing approaches the simplest possible neural structure is obtained requiring only sparse training information. Additionally, the control obtained is simple enough to be implemented directly in real time even for simple autopilot boards and maintains a large degree of robustness to changes in wind profile conditions.

关键词： Dynamic Soaring Artificial Neural Network Pseudospectral Optimal Control Unmanned Aerial Vehicle Wind Gradient Autopilot Flight Trajectory sequential quadratic programming Reinforcement Learning Lagrange Multipliers

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A new Method for Dynamic Economic Emission Dispatch Problem

A new Method for Dynamic Economic Emission Dispatch Problem

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IEEE Congress on Evolutionary Computation (IEEE CEC)

作者： Huang, Chia-Ling Jao, Chen-Wei Zhang, Xianyong Yeh, Wei-Chang Chung, Vera Yuk Ying Wang, Jinhai Yang, Jun Jiang, Yun-Zhi Kainan Univ Dept Logist & Shipping Management Taoyuan 33857 Taiwan Natl Tsing Hua Univ Dept Ind Engn & Engn Management Hsinchu 300 Taiwan Guangdong Polytech Normal Univ Sch Automat Guangzhou Guangdong Peoples R China Natl Tsing Hua Univ Dept Ind Engn & Engn Management Integrat & Collaborat Lab Hsinchu 300 Taiwan Univ Sydney Sch Informat Technol Sydney NSW 2006 Australia Foshan Univ Coll Elect & Informat Engn Foshan 528000 Peoples R China South China Univ Technol Sch Math Guangzhou Guangdong Peoples R China Guangdong Polytechn Normal Univ Sch Math & Syst Sci Guangzhou 510006 Guangdong Peoples R China

ISBN: (纸本)9781728121536

The Dynamic Economic Emission Dispatch Problem (DEED) is a well-known problem in the study of thermal power generation. The goal of the DEED is to meet the demand change by arranging the capacities of power generators to reduce fuel cost and emission. In recent years, the high environmental awareness, the decreasing petrochemical energy, and the increasing energy demand such that the DEED is more important and popular than before. Most of algorithms for the DEED are either limited by less than ten power generators or without considering the power generation limit. The former is impractical due to that the number of power generators in current thermal power plants can be up to 14;the latter results in infeasible solutions. To overcome the above two obstacles, a new algorithm called the SSO-DE-SQP hybrid with the Simplified Swarm Optimization (SSO), Differential Evolution (DE), and sequential quadratic programming (SQP) is developed to solve the larger-size DEED with the power generation limit. The performance of the SSO-DE-SQP is demonstrated by comparing with two existing well-known methods: DE-SQP and PSO-SQP with up to 15 generators for the DEED.

关键词： Dynamic Economic Emission Dispatch Problem Fuel cost and Emission Simplified Swarm Optimization Differential Evolution algorithm sequential quadratic programming

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Pulsed Array of Spiral Antennas for Scanned Energy Pattern with Low Side Lobes

Pulsed Array of Spiral Antennas for Scanned Energy Pattern w...

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IEEE International Symposium on Antennas and Propagation / USNC/URSI National North American Radio Science Meeting

作者： Reyna, Alberto Panduro, Marco A. Univ Autonoma Tamaulipas UAMRR Reynosa Tamaulipas Mexico

ISBN: (纸本)9781479978151

this document presents a design approach of a pulsed antenna array of circularly polarized two-arm log spiral antennas. The design is addressed as an optimization of the antenna positions in order to obtain a scanned energy pattern with low side lobes in time domain. It is utilized the well-known sequential quadratic programming for the optimization. The results revealed good performance of the pulsed antenna array for ultra wide band, circular polarization and scanning properties.

关键词： Pulsed antenna arrays Spiral antenna Energy pattern sequential quadratic programming

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Classification-assisted Memetic Algorithms for Solving Optimization Problems with Restricted Equality Constraint Function Mapping

Classification-assisted Memetic Algorithms for Solving Optim...

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IEEE Congress on Evolutionary Computation (CEC)

作者： Handoko, Stephanus Daniel Keong, Kwoh Chee Soon, Ong Yew Chan, Jonathan Nanyang Technol Univ Sch Comp Engn Singapore 639798 Singapore King Mongkuts Univ Technol Thonburi Sch Informat Technol Bangkok Thailand

ISBN: (纸本)9781424478354

The success of Memetic Algorithms (MAs) has driven many researchers to be more focused on the efficiency aspect of the algorithms such that it would be possible to effectively employ MAs to solve computationally expensive optimization problems where single evaluation of the objective and constraint functions may require minutes to hours of CPU time. One of the important design issues in MAs is the choice of the individuals upon which local search procedure should be applied. Selecting only some potential individuals lessens the demand for functional evaluations hence accelerates convergence to the global optimum. In recent years, advances have been made targeting optimization problems with single equality constraint h(x) = 0. The presence of previously evaluated candidate solutions with different signs of constraint values within some localities thus allows the estimation of the constraint boundary. An individual will undergo local search only if it is sufficiently close to the approximated boundary. Elegant as it may seem, the approach had unfortunately assumed that every constraint function maps the design variables to optimize into unbounded real values. This, however, may not always be the case in practice. In this paper, we present a strategy to efficiently solve constrained problems with a single equality constraint;the function of which maps the design variables into restricted (either strictly non-negative or strictly non-positive) real values only.

关键词： Evolutionary computation memetic algorithms genetic algorithms sequential quadratic programming equality-constrained optimization computationally-expensive problems classification support vector machine

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Modal Correlation Analysis and Optimization of Space Adapter 2

Modal Correlation Analysis and Optimization of Space Adapter

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2nd International Conference on Robotics and Automation Engineering (ICRAE)

作者： Luo Haitao Wang Zhengyin Fu Jia Wang Peng Wang Wei Chen Shipeng Chinese Acad Sci Shenyang Inst Automat Shenyang 110016 Liaoning Peoples R China Northeastern Univ Sch Mech Engn Shenyang 110023 Liaoning Peoples R China

ISBN: (纸本)9781538613061

Through the correlation analysis between the experimental modal and the finite element modal analysis, the finite element model can be modified and optimized so that a more accurate finite element model can be obtained, and the accuracy of strength, stiffness and frequency response analysis can be guaranteed. First, the experimental modal of the adapter is obtained by hammering method of LMS Test. lab. Then the correlation between the model and the finite element model is analyzed. Finally, the sequential quadratic programming (SQP) is used to correct and optimize finite element model of the adapter. This method has been proved to be reliable by practice. What's more, this method also has certain practical significance of engineering.

关键词： correlation analysis hammering method sequential quadratic programming correct and optimize

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Trim Strategies for Over-Actuated Vehicle Configurations During Conceptual Design

Trim Strategies for Over-Actuated Vehicle Configurations Dur...

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AIAA Aviation Forum and Exposition

作者： Beals, Nathan Govindarajan, Bharath DEVCOM Army Res Lab Weap & Mat Res Div Aberdeen Proving Gnd MD 21005 USA Indian Inst Technol Madras Dept Aerosp Engn Chennai 600036 Tamil Nadu India

ISBN: (数字)9781624106101

ISBN: (纸本)9781624106101

Techniques allowing for robust six degree-of-freedom vehicle trim are explored within the iterative rotorcraft sizing framework HYDRA. An optimization-based approach allows designers to find an acceptable local minimum solution of the trim problem for over-actuated vehicle configurations for which an infinite number of trim solutions exist. The performance and robustness of optimization algorithms suitable for the minimization of a nonlinear objective function subject to design variable bounds and equality constraints are compared using both a four degree-of-freedom and a six degree-of-freedom vehicle trim problems. The SciPy implementation of the sequential least squares programming algorithm was found to converge to a target objective function value up to 96% faster than a trust region algorithm for both problems. The six degree-of-freedom trim methodology using sequential least squares programming was then applied to the problem of sizing an omni-directional ocotocopter to be able to complete a mission taking into account multiple motor/rotor failures during the flight.

关键词： Three Degrees of Freedom Rotor Wings sequential quadratic programming Hexacopter Aircraft Configurations Pitching Moment Anti Torque Rotor Fixed Wing Aircraft Quadrotor Control Surfaces

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A Factor Graph Approach to Estimation and Model Predictive Control on Unmanned Aerial Vehicles

A Factor Graph Approach to Estimation and Model Predictive C...

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International Conference on Unmanned Aircraft Systems (ICUAS)

作者： Ta, Duy-Nguyen Kobilarov, Marin Dellaert, Frank Georgia Inst Technol Inst Robot & Intelligent Machines Atlanta GA 30332 USA Johns Hopkins Univ Lab Computat Sensing & Robot Baltimore MD 21218 USA

ISBN: (纸本)9781479923762

In this paper, we present a factor graph framework to solve both estimation and deterministic optimal control problems, and apply it to an obstacle avoidance task on Unmanned Aerial Vehicles (UAVs). We show that factor graphs allow us to consistently use the same optimization method, system dynamics, uncertainty models and other internal and external parameters, which potentially improves the UAV performance as a whole. To this end, we extended the modeling capabilities of factor graphs to represent nonlinear dynamics using constraint factors. For inference, we reformulate sequential quadratic programming as an optimization algorithm on a factor graph with nonlinear constraints. We demonstrate our framework on a simulated quadrotor in an obstacle avoidance application.

关键词： Factor Graph Unmanned Aerial Vehicle drone honey bees Obstacle avoidance vehicle factor A Line graph nonlinear constraint Optimization algorithms Collision avoidance sequential quadratic programming Model predictive control Predictive control Nonlinear Dynamics

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An Efficient Heuristic Algorithm for Flexible Job-Shop Scheduling Problem with Due Windows 18

An Efficient Heuristic Algorithm for Flexible Job-Shop Sched...

引用

IEEE 18th International Conference on Automation Science and Engineering (IEEE CASE)

作者： Ai, Yi Wang, Mengying Xue, Xiaoguang Yan, Chao-Bo Xi An Jiao Tong Univ State Key Lab Mfg Syst Engn Xian 710049 Shaanxi Peoples R China Xi An Jiao Tong Univ Sch Automat Sci & Engn Fac Elect & Informat Engn Xian 710049 Shaanxi Peoples R China Beijing Special Engn & Design Inst Beijing 100028 Peoples R China

ISBN: (数字)9781665490429

ISBN: (纸本)9781665490429

Constructing intelligent manufacturing systems and optimizing scheduling management is of economic significance. To apply the flexible job-shop scheduling problem to specific manufacturing fields, such as the food fermentation industry and aerospace industry, in which each product is required to be delivered within its due window, this paper establishes the mixed-integer nonlinear programming model for the flexible job-shop scheduling problem with due windows and develops a bi-level closed-loop heuristic algorithm to minimize the weighted earliness or tardiness. In the upper level, the genetic algorithm is used to optimize each job's processing path and sequence iteratively. In the lower level, the sequential quadratic programming determines the start time for each operation of each job by solving a nonlinear programming problem. The convergence of the algorithm is analyzed. Experimental results show that the algorithm can efficiently solve the optimal solution or approximate optimal solution of the problem. As a general idea of dividing integer and continuous solution space, the algorithm is robust to the field and details of the problem.

关键词： Due window flexible job-shop scheduling problem genetic algorithm sequential quadratic programming

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Computational developments of ψ-learning

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5th SIAM International Conference on Data Mining

作者： Liu, Sijin Shen, Xiaotong Wong, Wing Hung Ohio State Univ Dept Stat Columbus OH 43210 USA

ISBN: (纸本)9780898715934

One central problem in science and engineering is predicting unseen outcome via relevant knowledge gained from data, where accuracy of generalization is the key. In the context of classification, we argue that higher generalization accuracy is achievable via psi-learning, when a certain class of non-convex rather than convex cost functions are employed. To deliver attainable higher generalization accuracy, we propose two computational strategies via a global optimization technique-difference convex programming, which relies on a decomposition of the cost function into a difference of two convex functions. The first strategy solves sequential quadratic programs. The second strategy, combining this with the method of Branch-and-Bound, is more computationally intensive but is capable of producing global optima. Numerical experiments suggest that the algorithms realize the desired generalization ability of psi-learning.

关键词： DC programming global optimization sequential quadratic programming support vectors

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Fast Quantum Gate Control with Trajectory Optimization 12

Fast Quantum Gate Control with Trajectory Optimization

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12th IFAC Symposium on Advanced Control of Chemical Processes (ADCHEM)

作者： Hu, Shouliang Li, Ming Chen, Chunlin Dong, Daoyi Australian Natl Univ Sch Engn Canberra ACT Australia Guangdong Univ Technol Sch Automat Guangzhou Guangdong Peoples R China Nanjing Univ Sch Management & Engn Nanjing Peoples R China Australian Natl Univ Sch Engn CIICADA Lab Canberra ACT Australia

Fast quantum control helps reduce the influence of unavoided disturbances and hence plays a vital role in practical quantum technology and chemical reactions. Instead of optimizing the terminal cost like standard optimal quantum control methods, this paper formulates the problem as a trajectory optimization problem, and implements the sequential quadratic programming algorithm to search for short control fields. The core idea is to minimize the cumulative intermediate error to incentivize early achievement of the designed gate. The numerical result on the Toffoli gate demonstrates the effectiveness of the proposed method. Copyright (C) 2024 The Authors.

关键词： quantum gate trajectory optimization sequential quadratic programming

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