A Minimum Variance, Time Optimal, Control System Model of Human Lens Accommodation

Experimental data relating ciliary nerve stimulation and lens motion are used to identify the open-loop plant dynamics of the lens accommodation system via a parameter identication variation of the Kalman filter equations. Using the resultant minimum variance plant model, experimental closed-loop responses of the human accommodative system are predicted by synthesizing the system closed-loop controller. The resultant control signals are shown to minimize the time required to change the refractive state of the eye. The plant dynamic model and the closed-loop model are further verified by comparing their frequency responses to experimental data. The optimal performance of the lens system is compared to analogous performance of another ocular control system, and a possible general theory of optimal control is discussed.