Numerical solution of different kinds of fractional-order optimal control problems using generalized Lucas wavelets and the least squares method

被引:1
|
作者
Sabermahani, S. [1 ]
Ordokhani, Y. [1 ]
Razzaghi, M. [2 ]
机构
[1] Alzahra Univ, Fac Math Sci, Dept Math, Tehran, Iran
[2] Mississippi State Univ, Dept Math & Stat, Mississippi State, MS USA
来源
关键词
fractional optimal control problems; fractional pantograph optimal control problems; generalized Lucas wavelets; least squares method; POLYNOMIALS; EXISTENCE;
D O I
10.1002/oca.3182
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Generalized Lucas wavelets (GLWs) have two more parameters (alpha$$ \alpha $$ and beta$$ \beta $$), comparing with some existing classical wavelet functions. In this manner, we have different types of wavelet functions (orthogonal and non-orthogonal) by choosing various values of parameters alpha$$ \alpha $$ and beta$$ \beta $$. Due to the impressive feature of the GLWs, we design a new computational method for the solution of fractional optimal control problems and fractional pantograph optimal control problems. This technique uses the GLWs and least squares method. The scheme includes expanding the required functions using GLW elements. We present new Riemann-Liouville and pantograph operational matrices for GLWs. Applying the operational matrices and least squares method, the considered problems lead to systems of algebraic equations, which can be solved numerically. A brief discussion of the error of the estimate used is investigated. Finally, some numerical experiments are exhibited to demonstrate the validity and applicability of the suggested scheme. The proposed algorithm is easy to implement and presents very accurate results. In this paper, we designed a new numerical method based on the generalized Lucas wavelet functions for solving two classes of optimal control problems, fractional optimal control problems and fractional pantograph optimal control problems. Generalized Lucas wavelets (GLWs) have two more parameters (alpha and beta) compared with some existing classical wavelet functions. In this manner, we have different types of wavelet functions (orthogonal and non-orthogonal) by choosing various values of parameters (alpha and beta). image
引用
收藏
页码:2702 / 2721
页数:20
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