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Linear quadratic Gaussian algorithm

Chapter 12 considers the combination of optimal control with state and parameter estimation. The separation principle is developed, which states that the design of a control problem with measurement and model uncertainty can be treated by first performing a Kalman filter estimate of the states and then developing the optimal control law based upon the estimated states. For linear regulator problems, the problem is known as the linear quadratic Gaussian (LQG) problem. The inclusion of model parameter identification results in adaptive control algorithms. [Pg.2]


See other pages where Linear quadratic Gaussian algorithm is mentioned: [Pg.216]    [Pg.217]    [Pg.302]    [Pg.334]    [Pg.335]    [Pg.13]    [Pg.282]    [Pg.493]   
See also in sourсe #XX -- [ Pg.335 ]




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