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w i are quadrature weights, and; x i are the roots of the nth Legendre polynomial. This choice of quadrature weights w i and quadrature nodes x i is the unique choice that allows the quadrature rule to integrate degree 2n − 1 polynomials exactly. Many algorithms have been developed for computing Gauss–Legendre quadrature rules.
Gauss–Legendre methods are implicit Runge–Kutta methods. More specifically, they are collocation methods based on the points of Gauss–Legendre quadrature. The Gauss–Legendre method based on s points has order 2s. [1] All Gauss–Legendre methods are A-stable. [2] The Gauss–Legendre method of order two is the implicit midpoint rule.
These are named after Rehuel Lobatto [7] as a reference to the Lobatto quadrature rule, but were introduced by Byron L. Ehle in his thesis. [8] All are implicit methods, have order 2 s − 2 and they all have c 1 = 0 and c s = 1.
The Gauss–Legendre methods use the points of Gauss–Legendre quadrature as collocation points. The Gauss–Legendre method based on s points has order 2s. [2] All Gauss–Legendre methods are A-stable. [3] In fact, one can show that the order of a collocation method corresponds to the order of the quadrature rule that one would get using the ...
This exact rule is known as the Gauss–Legendre quadrature rule. The quadrature rule will only be an accurate approximation to the integral above if f (x) is well-approximated by a polynomial of degree 2n − 1 or less on [−1, 1]. The Gauss–Legendre quadrature rule is not typically used for integrable functions with endpoint singularities ...
There are a very large number of ideas that fall under the general banner of pseudospectral optimal control. [7] Examples of these are the Legendre pseudospectral method, the Chebyshev pseudospectral method, the Gauss pseudospectral method, the Ross-Fahroo pseudospectral method, the Bellman pseudospectral method, the flat pseudospectral method and many others.
An enhancement to the Chebyshev pseudospectral method that uses a Clenshaw–Curtis quadrature was developed. [18] The LPM uses Lagrange polynomials for the approximations, and Legendre–Gauss–Lobatto (LGL) points for the orthogonal collocation. A costate estimation procedure for the Legendre pseudospectral method was also developed. [19]
The Gauss–Legendre method with s stages has order 2s, so its stability function is the Padé approximant with m = n = s. It follows that the method is A-stable. [34] This shows that A-stable Runge–Kutta can have arbitrarily high order. In contrast, the order of A-stable linear multistep methods cannot exceed two. [35]