Estimation Error Bounds: Including Unmodeled Dynamics

In Chapter 3, we derived convergent estimators of the system parameters using binary-valued observations. Our aim here is to obtain further bounds on estimation errors from unmodeled dynamics. In this book, unmodeled dynamics are treated as a deterministic uncertainty which is unknown but has a known bound in an appropriate space. Due to the coexistence of deterministic uncertainty from unmodeled dynamics and stochastic disturbances, we are treating necessarily a mixed environment. Consequently, estimation error characterization has a probabilistic measure that is compounded with a worst-case scenario over unmodeled dynamics, an idea introduced in our earlier work [101, 102].

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