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Meeting	ACGS Committee Meeting 113 - Englewood, Colorado - March 2014
Agenda Location	6 SUBCOMMITTEE B – MISSILES AND SPACE 6.3 Optimal LQG Synthesis for Simplified Models and Model Replacement – Non-Separable Control and Estimation Algorithm Design
Title	Optimal LQG Synthesis for Simplified Models and Model Replacement – Non-Separable Control and Estimation Algorithm Design
Presenter	David Geller
Affiliation	Utah State University
Available Downloads*	presentation
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Abstract	The optimal linear-quadratic-Gaussian synthesis design approach and the associated separation principle are investigated for the case where the algorithm design model is a simplified version of the underlying system model. Performance of the simplified algorithms in the full-state system environment is formulated in terms of an augmented state vector consisting of the system state vector and the simplified algorithm state vector. Assuming linear control and estimation laws, a calculus of variations/Hamiltonian approach is used to determine the necessary conditions for the optimal controller and estimator gains for the simplified algorithms. Results show that the optimal solution is not separable, i.e., the optimal controller and estimator gains are coupled and cannot be computed independently. A numerical example of an infinite horizon control and estimation problem clearly shows the advantages of using the non-separable coupled solutions.