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Journal ArticleDOI

An hp‐adaptive pseudospectral method for solving optimal control problems

TLDR
An hp‐adaptive pseudospectral method that iteratively determines the number of segments, the width of each segment, and the polynomial degree required in each segment in order to obtain a solution to a user‐specified accuracy.
Abstract
SUMMARY An hp-adaptive pseudospectral method is presented for numerically solving optimal control problems The method presented in this paper iteratively determines the number of segments, the width of each segment, and the polynomial degree required in each segment in order to obtain a solution to a userspecified accuracy Starting with a global pseudospectral approximation for the state, on each iteration the method determines locations for the segment breaks and the polynomial degree in each segment for use on the next iteration The number of segments and the degree of the polynomial on each segment continue to be updated until a user-specified tolerance is met The terminology ‘hp’ is used because the segment widths (denoted h) and the polynomial degree (denoted p) in each segment are determined simultaneously It is found that the method developed in this paper leads to higher accuracy solutions with less computational effort and memory than is required in a global pseudospectral method Consequently, the method makes it possible to solve complex optimal control problems using pseudospectral methods in cases where a global pseudospectral method would be computationally intractable Finally, the utility of the method is demonstrated on a variety of problems of varying complexity Copyright 2010 John Wiley & Sons, Ltd

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Journal ArticleDOI

A Survey of Motion Planning and Control Techniques for Self-Driving Urban Vehicles

TL;DR: In this article, the authors present a survey of the state of the art on planning and control algorithms with particular regard to the urban environment, along with a discussion of their effectiveness.
Posted Content

A Survey of Motion Planning and Control Techniques for Self-driving Urban Vehicles

TL;DR: The objective of this paper is to survey the current state of the art on planning and control algorithms with particular regard to the urban setting and to gain insight into the strengths and limitations of the reviewed approaches.
Journal ArticleDOI

GPOPS-II: A MATLAB Software for Solving Multiple-Phase Optimal Control Problems Using hp-Adaptive Gaussian Quadrature Collocation Methods and Sparse Nonlinear Programming

TL;DR: A general-purpose MATLAB software program called GPOPS--II is described for solving multiple-phase optimal control problems using variable-order Gaussian quadrature collocation methods.
Book ChapterDOI

Methods of Numerical Integration

TL;DR: Methods of numerical integration will lead you to always think more and more, and this book will be always right for you.
Journal ArticleDOI

An Introduction to Trajectory Optimization: How to Do Your Own Direct Collocation

Matthew Kelly
- 06 Nov 2017 - 
TL;DR: This paper is an introductory tutorial for numerical trajectory optimization with a focus on direct collocation methods, and provides an electronic supplement that contains well-documented MATLAB code for all examples and methods presented.
References
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Book

Spectral Methods in Fluid Dynamics

TL;DR: Spectral methods have been widely used in simulation of stability, transition, and turbulence as discussed by the authors, and their applications to both compressible and incompressible flows, to viscous as well as inviscid flows, and also to chemically reacting flows are surveyed.
Journal ArticleDOI

Spectral Methods in Fluid Dynamics.

TL;DR: In this article, the authors present a set of methods for the estimation of two-dimensional fluid flow, including a Fourier Galerkin method and a Chebyshev Collocation method.
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