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In this paper, first an analytical model of a synchronous generator with a pulsed constant power load (CPL) is developed and numerically compared with a detailed simulation model. The analytical model is shown to possess good predictive abilities, thus enabling its use for control purposes. Second, the generator has a proportionalintegral (PI) control inner-loop, whose task is to regulate the generator’s output voltage to a desired reference. A novel outer-loop predictive reference governor (PRG) is designed and tested via simulation. The PRG uses the analytical model to predict the output behavior of the generator over a short time window, and continuously modifies the reference given to the inner-loop in order to maintain stringent steady-state requirements, in spite of demanding power requirements at the CPL. Simulation results illustrate the significant performance advantages of using the PRG versus using the inner-loop PI controller alone.

Cost and performance requirements are driving military and commercial systems to become highly integrated, optimized systems which require more sophisticated, highly complex controls. To realize benefits of those complex controls and make confident decisions, the validation of both plant and control models becomes critical. To quickly develop controls for these systems, it is beneficial to develop plant models and determine the uncertainty of those models to predict performance and stability of the control algorithms. A process of model and control algorithm validation for a dc-dc boost converter circuit based on acceptance sampling is presented here. The validation process described in this paper is based on MIL-STD 3022 with emphasis on requirements settings and the testing process. The key contribution of this paper is the process for model and control algorithm validation, specifically a method for decomposing the problem into model and control algorithm validation stages.