An approach to model-following controller design based on a stabilized digital inverse system

Abstract

This article explains our approach to designing a model-following controller based on a stabilized digital inverse system. We use an inter-sample auxiliary observation output from the model as an input to the inverse system. We then design the inverse system for minimum and non-minimum phase plants. In order to reposition the unstable poles of the inverse system on a stable region, we determine the optimal gain vector using a linear quadratic regulator. We confirm the effectiveness of our proposed method by performing simulations for several plants and conducting an experiment with a direct current motor.

A study on a new criterion for minimum-energy perfect control in the state-space framework

“…12,13 For instance, an application of various nonsquare parameter/polynomial matrices in the inverse model–based control algorithms, including the minimum variance/perfect control procedure, makes such control laws more robust. 14–16 In particular, it can be observed in case of multivariable systems, having different numbers of input and output variables. 17,18 For such plants, the use of so-called degrees of freedom of nonunique right inverses gives quantifiable minimum-energy benefits, in opposite to the unique T - inverse , for which the said control algorithm often does not exist.…”