Capturing and Tuning Nonlinear Characteristics of Economic Stabilization Systems by Fuzzy Control Techniques

Various techniques have been used to control or stabilize economic processes:from econometric models based on rational expectations (assuming that shiftsin economic policy produce revised expectations of rational agents), toregulatory mechanisms, normally regarded as engineering tools. However,applying nonconventional techniques, such as fuzzy control, could provide moreflexible alternatives to the conventional way. Presumably, the interest inapplying fuzzy control to economic processes consists of at least twoadvantages: on one hand in prescribing control actions by linguisticdescriptions and on the other hand in the capability of transition from linearto nonlinear modes of control, conjugated with fine-tuning procedures. Thispaper is intended to exemplify the latter opportunity. After brieflydescribing certain fundamental concepts of fuzzy control, we focus on thedesign of fuzzy linear controllers that emulate conventional modes of controlin the first stage and on the refinement of such fuzzy controllers by makingthem progressively nonlinear in the second stage. As an application of fuzzycontrol to economic processes, we provide a fuzzy extension of the Phillips'stabilization model in two variants: for a closed economy as well as for anopen economy. To implement the control schemata, tools like Matlab andSimulink are used.

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