Abstract
A pilot model based on Kalman filtering and optimal control is given which, because of its structure, provides for estimation of the plant state variables, the forcing functions, the time delay, and the neuromuscular lag. The inverse filter and control problem is considered where the noise and cost function parameters yield a frequency response which is in close agreement with that found experimentally. A good correspondence with sine-wave tracking is shown including "eyes closed" tracking.

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