Control of linear jump systems in noise

The equations of state evolution of a linear-jump system have a hybrid structure in which a modal-state process indexes the model of dynamic evolution of the base state. When the state measurements are noisy, the intrinsic nonlinearities in the system make it difficult to achieve acceptable performance with control algorithms based upon conventional estimators. Effective control reconfiguration requires that the correlation between the state and modal errors be computed. This paper presents an estimation algorithm that can be used in this context. It is shown by an example that closed-loop performance is improved when certain cross moments are utilized.

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