Solution of matrix Riccati differential equation for the linear quadratic singular system using neural networks

In this paper, the solution of the matrix Riccati differential equation (MRDE) for the linear quadratic singular system is obtained using neural networks. The goal is to provide optimal control with reduced calculus effort by comparing the solutions of the MRDE obtained from well-known traditional methods like Runge–Kutta, Runge–Kutta Butcher and non-traditional method neural network. The neural training is performed using Levenberg–Marquardt algorithm. Accuracy of the solution of the neural network approach to the problem is qualitatively better. The advantage of the proposed approach is that, once the network is trained, it allows instantaneous evaluation of solution at any desired number of points spending negligible computing time and memory. An illustrative numerical example for the proposed method is given.