A canonical optimal control problem for linear systems with timevarying coefficients is considered in the class of discrete controls. On the basis of linear programming methods, two primal and two dual methods of constructing optimal open-loop controls are proposed. A method of synthesis of optimal feedback control is described. Results are illustrated by a fourth-order problem; estimates of ef...

This paper is concerned with process identification by curve fitting step responses. Both open-loop and closed-loop identification are studied using simulated data for typical examples as well as experimental data from a laboratory plate heat exchanger. Timedomain curve fitting utilizing efficient local optimization techniques is employed to find the parameters of the process model. Process mod...

We examined accommodative vergence eye movements under conditions in which feedback about retinal-image slip was and was not present (i.e. closed-loop and open-loop conditions). We found that (a) in both conditions the two eyes started to move at the same time; (b) in the open-loop condition, vergence continued in both eyes; and (c) in the closed-loop condition, vergence continued in the occlud...

-For conventional op amps design open loop poles are usually in the left-half plane. For amplifiers with negative impedance gain enhancement the open loop pole is adjustable and it can be in the left-half plane or in the right-half plane. In this paper, we justify that it does not require a left-half plane open loop pole for designing a stable close loop amplifier. As a matter of fact, the ampl...

Used as a wavefront corrector, a liquid crystal spatial modulator (LC-SLM) has good repeatability and linearity, which are essential for open-loop adaptive optics, and the open-loop optical system can increase the light energy efficiency by a factor of two for the LC-SLM and improve the system bandwidth. In order to test the performance of the LC-SLM in open-loop correction, an indoor closed-lo...

Closed-loop control relies on sensory feedback that is usually assumed to be free . But if sensing incurs a cost, it may be costeffective to take sequences of actions in open-loop mode. We describe a reinforcement learning algorithm that learns to combine open-loop and closed-loop control when sensing incurs a cost. Although we assume reliable sensors, use of open-loop control means that action...

Sensor management is a stochastic control problem where the control mechanism is directed at the generation of observations. Typically, sensor management attempts to optimize a certain statistic derived from the posterior distribution of the state, such as covariance or entropy. However, these statistics often depend on future measurements which are not available at the moment the control decis...