Robustness guarantees for linear control designs with an estimated nonlinear model error model

Much attention in robust identification and control has been focused on linear low order models approximating high order linear systems. We consider the more realistic situation with a linear model approximating a nonlinear system. We describe how a nonlinear model error model can be developed, that allows a complete linear design process that results in a closed loop system with performance robustness guarantees (in terms of gain from disturbance to output) against the nonlinear error. Clearly the design can be successful only if the linear model is a reasonably good approximation of the system. A particular aspect of the design process is to define a workable definition of 'practical stability' for robust control design, with possible non-linear model errors. We use affine norms for that purpose. Copyright (C) 2004 John Wiley Sons, Ltd.