Optimal stochastic control of nonlinear systems
John H. Seinfeld · AIChE Journal · 1970
Abstract An algorithm is proposed for the feedback control of nonlinear systems, the observations of which are corrupted with noise of unknown statistics. The feedback loop contains a nonlinear Kalman filter, which produces sequential least‐square estimates of the state of the system, and a controller designed to minimize an instantaneous performance criterion based on the state estimates. The scheme requires the on‐line integration of n(n + 3)/2 differential equations, where n is the number of unknown states and parameters. The scheme is applied to the feedback control of a CSTR with a first‐order exothermic reaction the temperature measurements of which are corrupted with random noise.