A comparative study of normalized and unnormalized tuning errors in parameter-adaptive control

Simple examples are used to give a detailed account of the essential differences in structure between adaptive algorithms of the normalized and unnormalized types. It is explained why only the latter readily generalize to nonlinear process models with nonglobal Lipschitz nonlinearities. It is shown that one of these algorithms is capable of stabilizing linear process models with different relative degrees.<>