Abstract
A new strategy for stabilization of one-dimensional dynamic objects with a priori unknown mathematical model is presented. For a given control law, the stabilization strategy consists in determination of the times when the control law changes and its reversal at these times, on the basis of a fuzzy knowledge base that takes into account the nature of the variation of the “distance” relative to an equilibrium point. The derivatives of the “distance” and such concepts as “approach” and “departure” are also used. Aggregation of the input phase variables and the use of generalized concepts of the theory of Lyapunov stability make it possible to construct a sufficiently general and, at the same time, simple fuzzy regulator with two aggregated inputs and piecewise-continuous output signals.
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