A multiple model adaptive estimator (MMAE) has been formulated to estimate the state of a dynamic system modeled by a linear stochastic differential equation, from which measurements, described as a noise-corrupted space-time point process functionally related to that state, are extracted. Assumed certainty equivalence is used to combine such an estimator with the LQ full-state feedback controller to synthesize a practical, implementable controller. Performance of the estimator and resultant controller characteristics are investigated via simulation as a function of approximation method used to limit the full-scale estimator to finite dimensionality and also as a function of important parameters defining the dynamics and observation processes.
MMAE-Based Control with Space-Time Point Process Observations
IEEE Transactions on Aerospace and Electronic Systems ; AES-21 , 3 ; 292-300
1985-05-01
2158478 byte
Article (Journal)
Electronic Resource
English
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