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A Neuro Approach to Solve Fuzzy Riccati Differential Equations

机译:解决模糊Riccati微分方程的神经方法

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摘要

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 Nonlinear 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.
机译:最佳控制理论的应用特别是在工程控制系统领域。本文使用神经网络(NN)估计模糊二次Riccati差分方程。以前的作品使用runge-kutta第4阶(RK4)显示了可靠的结果。通过求解在Riccati微分方程中的第一阶非线性微分方程(ode)来实现解决方案。研究表明,RK4方法相对较好地显示出改善的结果。可以说,NN方法显示有前途的结果,具有连续估计的优点和改善可以在RK4上产生的精度。

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