Optimal control for a linear quadratic neuro Takagi--Sugeno fuzzy singular system using genetic programming

Abstract

Optimal control for a linear neuro Takag--Sugeno fuzzy singular system with quadratic performance is obtained using genetic programming (gp). To obtain the optimal control, the solution of a matrix Riccati differential equation is computed by solving a differential algebraic equation using the gp approach. The obtained solution is equivalent or very close to the exact solution of the problem. The accuracy of the solution computed by the gp approach is qualitatively better than the traditional Runge--Kutta method. An illustrative numerical example is presented for the proposed method. References

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