Chapter 7Variance-Constrained Dissipative Control with Degraded Measurements

It is well recognized that, in real-world engineering practice, the sensors have always been confronted with different kinds of failures due to various reasons, such as the erosion caused by severe circumstance, abrupt changes of working conditions, intense external disturbances, internal component constraints, and aging. The unavoidable sensor failures often occur in a probabilistic way that give rise to the measurements degradation phenomenon. In this case, the sampling output might contain incomplete information. Such a phenomenon has been firstly described in the literature by a binary switching sequence satisfying a conditional probability distribution. Recently, a more general model for missing measurement phenomenon has been proposed where the missing probability for each sensor is governed by an individual random variable satisfying a certain probability distribution over the interval c07-math-001. Such a model is ideal in reflecting multiple missing measurements or multiple measurements degraded due to different failure probabilities of different sensors. So far, all the available results have been concerned with either linear or deterministic systems. When it comes to relatively more complicated systems, such as nonlinear stochastic systems, the phenomenon of multiple degraded measurements has not yet received ...

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