Abstract
The issue of parameter convergence in multivariable adaptive control is addressed in a general framework. Parameter convergence is guaranteed if a certain design identity has a unique solution and if the inputs satisfy persistency of excitation conditions. The uniqueness of the solution of the design identity can be obtained, in general, by using parameterizations that, although nonminimal, are structured so as to guarantee uniqueness. This concept is illustrated with a direct adaptive pole placement algorithm, which is modified to guarantee uniqueness, and it is shown how the results can be used to establish stability and convergence properties of the algorithm.
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