Visual Deterministic Classification of the States of the Controlled Object in the N-dimensional State Space

Abstract

Proposed was a method enabling the operator supervising the controlled object to classify visually its state represented by a point in the i>n-dimensional Euclidean state space. The method relies on the class of nonlinear normalized maps of the points of the i>n-dimensional Euclidean space onto plane.