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In Chapters 7 and 8 we saw how adaptive control may be used as a systematic design tool to develop dynamic controllers for systems with a great deal of uncertainty while still being able to achieve good closed-loop performance. The techniques presented there, however, assumed that full state information is available for feedback. In this chapter we will extend these tools to develop adaptive output-feedback controllers for both stabilization and tracking. First, for systems with parametric uncertainties, we will provide a brief account of the adaptive output-feedback backstepping technique developed by Kanellakopoulos, Kokotovi6, and Morse. | Stable Adaptive Control and Estimation for Nonlinear Systems Neural and Fuzzy Approximator Techniques. Jeffrey T. Spooner Manfredi Maggiore Raul Ordonez Kevin M. Passino Copyright 2002 John Wiley Sons Inc. ISBNs 0-471-41546-4 Hardback 0-471-22113-9 Electronic Chapter 11 Adaptive Output Feedback Control Overview In Chapters 7 and 8 we saw how adaptive control may be used as a systematic design tool to develop dynamic controllers for systems with a great deal of uncertainty while still being able to achieve good closed-loop performance. The techniques presented there however assumed that full state information is available for feedback. In this chapter we will extend these tools to develop adaptive output-feedback controllers for both stabilization and tracking. First for systems with parametric uncertainties we will provide a brief account of the adaptive output-feedback backstepping technique developed by Kanellakopoulos Kokotovic and Morse for more details the reader is referred to 115 . Next we will show how to employ the separation principle previously developed to extend the techniques seen in Chapters 7 and 8 to the output feedback framework. Recall that in the spirit of a separation principle one seeks to construct output-feedback controllers recovering the performance of given state-feedback controllers. This is advantageous in practice because the tools available to design output-feedback controllers without a separation principle are rather limited and work for restricted classes of nonlinear systems see . Section while by separating the state estimation from the control design phase one can exploit available state feedback design tools for quite general classes of systems. On the other hand the implementation of a state estimator requires some knowledge about the plant and in the adaptive control case restricts the class of uncertainties affecting the system. These issues play a major role now and will somewhat limit the generality of the .

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