Methods of state estimation in the presence of uncertain but bounded impacts, called robust, have been developed in attempts to cope with processes affected by unpredictable disturbances. This chapter develops the theory of robust finite impulse response (FIR) state estimation for LTI systems operating under disturbances in the presence of initial and measurement errors. As the approach suggests, the state estimator becomes robust if it is tuned for maximum disturbance. Numerical suboptimal algorithms can be designed to compute the gains for H 2 FIR predictors using linear matrix inequality. The chapter looks at the two most elaborate H 2 /H ∞ FIR algorithms: hybrid a posteriori H 2 /H ∞ FIR filter, and hybrid H 2 /H ∞ FIR predictor. The game theory robust approach, can also be seen as an artificial intelligence tool because it obeys some game rule rather than dealing with the estimator transfer function and impulse response.
Robust FIR State Estimation Under Disturbances
Optimal and Robust State Estimation ; 275-320
2022-08-09
46 pages
Article/Chapter (Book)
Electronic Resource
English
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