Nonlinear control for plants with partial information via Takagi-Sugeno models: An application on the twin rotor MIMO system

Abstract

This work is concerned with the synthesis of nonlinear controllers for plants where full state information is not available. By means of the equivalent Takagi-Sugeno form of the nonlinear model, conditions were found that allow a parallel distributed compensation of the model to be constructed only with partial information of the state and no need of an observer. These conditions are expressed in terms of linear matrix inequalities which are efficiently solved by convex optimization techniques in commercially available software. The proposed approach is successfully applied to the stabilization of a twin rotor MIMO system and compared with another partial-information technique.