Robust Estimation and Failure Detection for Linear Systems

This work presents a concise treatment of robust estimation, with a thorough presentation of Kalman filtering. The robust game theoretic/ H filtering theory is developed, making it possible to design estimators that are more general than Kalman filters and are robust to model uncertainties and/or rapid model variations. Intended for students, researchers or engineers with an interest in filtering or failure detection, this work offers classical and advanced theories and design methods and allows them to benefit from robust control theoretic developments since the early 1980s. Control researchers and engineers should also find the work relevant, as it demonstrates how development in their discipline affects these two neighbouring fields.