Optimal control for fuzzy linear partial differential algebraic equations using Simulink

Abstract

In this paper, optimal control for fuzzy linear partial differential algebraic equations (FPDAE) with quadratic performance is obtained using Simulink. By using the method of lines, the FPDAE is transformed into a fuzzy differential algebraic equations (FDAE). Hence, the optimal control of FPDAE can be found out by finding the optimal control of the corresponding FDAE. The goal is to provide optimal control with reduced calculus effort by the solutions of the matrix Riccati differential equation (MRDE) obtained from Simulink. Accuracy of the solution of the Simulink approach to the problem is qualitatively better. The advantage of the proposed approach is that, once the Simulink model is constructed, it allows to evaluate the solution at any desired number of points spending negligible computing time and memory and the solution curves can be obtained from the model without writing any code. An illustrative numerical example is presented for the proposed method.

Solution Procedure for Systems of Partial Dierential-Algebraic Equations by NHPM and Laplace-Padé Resummation

“…Many complex technical systems throughout science and engineering are easily modeled by Partial Differential-Algebraic Equations (PDAEs). This type of equations arise in nanoelectronics [1], electrical networks [2], [3], [4], mechanical systems [5] and many other applications [6], [7], [8], [9], [10], [11], [12], [13], [14].…”