Optimal control for stochastic linear quadratic singular Takagi-Sugeno fuzzy system using ant colony programming
Kumaresan Nallasamy · Neural, Parallel & Scientific Computations archive · 2010
In this paper, optimal control for stochastic linear singular Takagi-Sugeno (T-S) fuzzy system with quadratic performance is obtained using ant colony programming (ACP). To obtain the optimal control, the solution of matrix Riccati differential equation (MRDE) is computed by solving differential algebraic equation (DAE) using ACP approach. The solution of this novel method is compared with the traditional Runge Kutta (RK) method. An illustrative numerical example is presented for the proposed method.