The problem of observer design is addressed for outputinjection nonlinear systems. A major difficulty with this class of systems is that the state equation involves an output-dependent term that is explicitly dependent on unknown parameters. As the output is only accessible to measurement at sampling times, the outputdependent term turns out to be (almost all time) subject to a double uncertainty, making previous adaptive observers inappropriate. Presently, a new hybrid adaptive observer is designed and shown to be exponentially convergent under ad-hoc conditions.
The problem of observer design is addressed for a class of triangular nonlinear systems in presence of output measurement sampling and time-delay. A major difficulty with the considered nonlinear systems is that the state matrix is dependent on the "undelayed output signal" which is not accessible to measurement, making existing observers inapplicable. A new observer is designed where the effects of time-delay and sampling are compensated for using an output predictor. Defined by a couple of first-order ordinary differential equations (ODEs), the present predictor turns out to be much simpler compared to previous predictors involving output and state predictors. Using the small gain technique, sufficient conditions for the observer to be exponentially convergent are established in terms of the maximum time-delay and sampling interval.
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