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Algorithms for model reference adaptive control were developed in recent years, and their stability and convergence properties have been investigated. Typical algorithms in continuous time involve strictly positive real conditions on the reference model, while similar discrete time algorithms do not require such conditions. We show how algorithms differ by the use of an input error versus an output...
We present schemes for both continuous and discrete time adaptive control of linear time invariant systems. which are partially known, along with analysis of their convergence properties.
The adaptive control of a class of large-scale systems formed of an arbitrary interconnection of subsystems with unknown parameters and bounded disturbances is investigated. New decentralized adaptive controllers are introduced which guarantee boundedness and convergence of the tracking errors to a bounded residual set when disturbances and interconnections are present. In the absence of disturbances,...
It is shown that the Geodwin-Ramadge-Caines method for adaptive control of discrete-time systems may be used for the identification of system parameters. An expression for the optimal gain constant is derived. Then, the algorithm may be modified to allow for improved convergence and maintenance of linear relationships of the unknown parameters of the system.
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