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

Abstract

Various techniques have been used to control or stabilize economic processes: from econometric models based on rational expectations (assuming that shifts in economic policy produce revised expectations of rational agents), to regulatory mechanisms, normally regarded as engineering tools. However, applying nonconventional techniques, such as fuzzy control, could provide more flexible alternatives to the conventional way. Presumably, the interest in applying fuzzy control to economic processes consists of at least two advantages: on one hand in prescribing control actions by linguistic descriptions and on the other hand in the capability of transition from linear to nonlinear modes of control, conjugated with fine-tuning procedures. This paper is intended to exemplify the latter opportunity. After briefly describing certain fundamental concepts of fuzzy control, we focus on the design of fuzzy linear controllers that emulate conventional modes of control in the first stage and on the refinement of such fuzzy controllers by making them progressively nonlinear in the second stage. As an application of fuzzy control to economic processes, we provide a fuzzy extension of the Phillips' stabilization model in two variants: for a closed economy as well as for an open economy. To implement the control schemata, tools like Matlab and Simulink are used.