@article{(Open Science Index):https://publications.waset.org/pdf/15731, title = {Fuzzy Control of Macroeconomic Models}, author = {Andre A. Keller}, country = {}, institution = {}, abstract = {The optimal control is one of the possible controllers for a dynamic system, having a linear quadratic regulator and using the Pontryagin-s principle or the dynamic programming method . Stochastic disturbances may affect the coefficients (multiplicative disturbances) or the equations (additive disturbances), provided that the shocks are not too great . Nevertheless, this approach encounters difficulties when uncertainties are very important or when the probability calculus is of no help with very imprecise data. The fuzzy logic contributes to a pragmatic solution of such a problem since it operates on fuzzy numbers. A fuzzy controller acts as an artificial decision maker that operates in a closed-loop system in real time. This contribution seeks to explore the tracking problem and control of dynamic macroeconomic models using a fuzzy learning algorithm. A two inputs - single output (TISO) fuzzy model is applied to the linear fluctuation model of Phillips and to the nonlinear growth model of Goodwin.}, journal = {International Journal of Economics and Management Engineering}, volume = {2}, number = {5}, year = {2008}, pages = {450 - 459}, ee = {https://publications.waset.org/pdf/15731}, url = {https://publications.waset.org/vol/17}, bibsource = {https://publications.waset.org/}, issn = {eISSN: 1307-6892}, publisher = {World Academy of Science, Engineering and Technology}, index = {Open Science Index 17, 2008}, }