Feedforward of Measurable Disturbances to Improve Multi-Input Feedback Control

Abstract

The availability of multiple inputs (plants) can improve output performance by conveniently allocating the control bandwidth among them. Beyond that, the intervention of only the useful plants at each frequency implies the minimum control action at each input. Secondly, in single input control, the addition of feedforward loops from measurable external inputs has been demonstrated to reduce the amount of feedback and, subsequently, palliate its sideband effects of noise amplification. Thus, one part of the action calculated by feedback is now provided by feedforward. This paper takes advantage of both facts for the problem of robust rejection of measurable disturbances by employing a set of control inputs; a previous work did the same for the case of robust reference tracking. Then, a control architecture is provided that includes feedforward elements from the measurable disturbance to each control input and feedback control elements that link the output error to each control input. A methodology is developed for the robust design of the named control elements that distribute the control bandwidth among the cheapest inputs and simultaneously assures the prescribed output performance to correct the disturbed output for a set of possible plant cases (model uncertainty). The minimum necessary feedback gains are used to fight plant uncertainties at the control bandwidth, while feedforward gains achieve the nominal output response. Quantitative feedback theory (QFT) principles are employed. An example illustrates the method and its benefits versus a control architecture with only feedback control elements, which have much more gain beyond the control bandwidth than when feedforward is employed.