Remote computer control of an industrial process
P. Choquette, A.R.M. Noton, Chris Watson · Proceedings of the IEEE · 1970
The development of a nonlinear dynamic model of an industrial process is summarized. The model includes additive stochastic terms and not all the state variables were accessible. Nonlinear state estimation was approximated by a linearized Kalman filter and the control algorithm was from dynamic programming. The development of software and hardware for a remote on-line computer control experiment is then described, in which the industrial plant was connected to a process control computer some 130 miles away by a regular telephone channel.