Synthesis of Zonal Control of Nonlinear Dynamic Objects Taking into Account their History and Current State

In the work, we propose an approach to feedback control for nonlinear objects with lumped parameters, which involves dividing the entire set of the object’s potential phase states into a finite number of subsets or zones. In this approach, the synthesized controls are based not on the measured phase state values directly, but rather on the zonal values of the parameters corresponding to the zone associated with the current and past object’s measured states. We have derived necessary optimality conditions for zonal values of feedback control parameters, as well as conducted computational experiments on various test problems, which confirmed the efficiency of the proposed approach to controlling nonlinear dynamic objects.