NANAFeb 13, 2018

Generalized Lagrangian Jacobi-Gauss-Radau collocation method for solving a nonlinear 2-D optimal control problem with the classical diffusion equation

arXiv:1802.047799 citationsh-index: 37
Originality Synthesis-oriented
AI Analysis

For researchers in optimal control and numerical methods, this is an incremental extension of existing collocation methods to a specific class of 2D problems.

The paper introduces a Generalized Lagrangian Jacobi-Gauss-Radau collocation method to solve a nonlinear 2D optimal control problem governed by a classical diffusion equation, reducing it to a parameter optimization problem. Numerical results demonstrate accuracy and efficiency, but no concrete numbers are provided.

In this paper, a nonlinear 2D Optimal Control Problem (2DOCP) is considered. The quadratic performance index of a nonlinear cost function is endowed with the state and control functions. In this problem, the dynamic constraint of the system is given by a classical diffusion equation. This article is concerned with a generalization of Lagrangian functions. Besides, a Generalized Lagrangian Jacobi-Gauss-Radau (GLJGR)-collocation method is introduced and applied to solve the aforementioned 2DOCP. Based on initial and boundary conditions, the time and space variables t and x are considered Jacobi-Gauss-Radau points clustered on first or end of interval respectively. Then, to solve the 2DOCP, Lagrange Multipliers are used and the optimal control problem is reduced to a parameter optimization problem. Numerical results demonstrate its accuracy, efficiency, and versatility of the presented method.

Foundations

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