Multimodel robust control of nonlinear plants: a case study

A multimodel controller design procedure is proposed and evaluated on a strongly nonlinear chemical process. The objective is to design a controller which achieves good quadratic (LQ) performance and robustness for an uncertain nonlinear plant. In order to capture both parametric and unstructured plant uncertainties, a multimodel process description is introduced, in which the plant is represented by a discrete set of linear models and associated norm-bounded uncertainties. The controller design problem is then stated as a multimodel mixed H2/H∞ problem for optimal quadratic (H2) performance subject to (H∞-type) robustness bounds for the multimodel plant description. The problem of finding a linear controller with the specified optimality and robustness properties lacks a closed solution, and it is therefore solved with parametric controller optimization techniques. The proposed controller design procedure is demonstrated on a simulated pH neutralization process, and is shown to give a linear controller with good performance and robustness characteristics. The achievable global performance is further improved by combining the proposed design procedure with controller scheduling. Two implementations of controller scheduling which satisfy a set of linearization conditions are presented and successfully tested on the neutralization process.