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Optimal control for linear system using genetic programming
Author(s) -
Kumar A. Vincent Antony,
Balasubramaniam P.
Publication year - 2008
Publication title -
optimal control applications and methods
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.458
H-Index - 44
eISSN - 1099-1514
pISSN - 0143-2087
DOI - 10.1002/oca.852
Subject(s) - optimal control , linear quadratic regulator , riccati equation , algebraic riccati equation , genetic programming , control (management) , linear quadratic gaussian control , computer science , mathematical optimization , differential (mechanical device) , matrix (chemical analysis) , genetic algorithm , mathematics , linear control systems , control theory (sociology) , differential equation , linear system , artificial intelligence , engineering , mathematical analysis , materials science , aerospace engineering , composite material
Abstract In this paper, optimal control for a linear system with quadratic performance is obtained using genetic programming (GP). The goal is to find the optimal control with reduced calculus effort using non‐traditional methods. The obtained GP solution is compared with the traditional Runge–Kutta method. To obtain optimal control, the solution of matrix Riccati differential equation is computed based on grammatical evolution. The accuracy of the solution of the GP approach to the problem is qualitatively better than traditional methods. An illustrative numerical example is presented for the proposed method. Copyright © 2008 John Wiley & Sons, Ltd.