Basic Research on Adaptive Model Algorithmic Control
Final rept. Feb 1982-Jun 1985
SCIENTIFIC SYSTEMS INC CAMBRIDGE MA
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The Model Algorithmic Control MAC method is investigated in terms of robustness and adaption to unknown or changing plants. The adaption method used is Canonical Variate Analysis CVA system identification. CVA is shown to provide system identification accuracy comparable to maximum likelihood and to provide an optimal selection of instrumental variables. Computationally CVA is a noniterative procedure that gives a numerically and statistically well conditioned solution to the system identification problem. A one-step-ahead MAC is explained using the classical root locus techniques. Conditions are developed for robustness of the controller to perturbations in the plant due to error in plant identification. Selection of an optimal sampling rate is based upon the control-ability and observability matrices. Simulations illustrating the above theory are presented using a Multi-Input Multi-Output MIMO missile aerodynamic model. Keywords multivariate analysis Digital control systems.
- Statistics and Probability