Fuzzy H Filter Design for Nonlinear Discrete-Time Systems with Multiple Time-Delays

Part of the Control Engineering book series (CONTRENGIN)


The problem of robust H filtering for systems with uncertain external disturbances and measurement noises has been of great interests [7, 18, 21]. The advantage of using an H filter over a Kalman filter is that no statistical assumption about the noise signals is required. In robust H filtering, the noise signals are assumed to be arbitrary with bounded energy (or average power). H filters are designed by minimizing signal estimation errors for bounded disturbances and noises of the worst case. Thus, H filters are more robust than Kalman filters. Moreover, the H filtering approach provides both a guaranteed noise attention level and a strong robustness against unmodeled dynamics.


IEEE Transaction Fuzzy System Linear Matrix Inequality Fuzzy Model Extended Kalman Filter 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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