Optimal control based on chaotic forecast and application on power systems

Due to chaotic time series internal certain regularity, their reconstructing chaotic attractors space has high precision short-term forecast. Therefore, a chaotic attractors space was reconstructed by the chaotic time series of nonlinear big-lagged system, the maximal Lyapunov exponent and the systemic forecast measure were calculated, and high precision short-term forecast was realized for this system. On the basis of these works, a optimal controller was designed by feedback rectification term and control input error being introduced into a performance function, and robust adaptive control was received to the nonlinear big-lagged system. The controller was applied to the unit load of power systems, the validity, the high-speed and the robustness were proved by the simulate results.