Abstract: Making use of the conceptual and computational similarities between the Karmarkar method and the Kalman filter a controller system is capable of handling the observer function, the minimum time controller function and the minimum energy controller function. The system includes an element that has the computational structure of a Kalman filter. The inputs of this element are qualitatively controlled to deliver the desired results to the remaining computation elements. In a controller for an LP control task, the element develops the dual vector signal used in the affine scaling algorithm by applying information to it as if its task were to estimate the states of a system whose observable output is D.sub.x(k) c, the input is O, the observation noise covariance matrix R is close to zero, the transition matrix is I and the matrix that describes the relationship between the measurable parameters and the observable output is A.sup.T D.sub.x(k).