A neuro approach to solve fuzzy Riccati differential equations

Autor: M. Z. M. Kamali, Kurunathan Ratnavelu, N. Kumaresan, Mohammad Shazri Shahrir
Rok vydání: 2015
Předmět:
Zdroj: AIP Conference Proceedings.
ISSN: 0094-243X
Popis: There are many applications of optimal control theory especially in the area of control systems in engineering. In this paper, fuzzy quadratic Riccati differential equation is estimated using neural networks (NN). Previous works have shown reliable results using Runge-Kutta 4th order (RK4). The solution can be achieved by solving the 1st Order Non-linear Differential Equation (ODE) that is found commonly in Riccati differential equation. Research has shown improved results relatively to the RK4 method. It can be said that NN approach shows promising results with the advantage of continuous estimation and improved accuracy that can be produced over RK4.
Databáze: OpenAIRE