Diminishing the discipline gap : restorative justice as a promising alternative in one urban school
Cost and performance requirements are driving military and commercial systems to highly integrated, optimized systems which require more sophisticated, highly complex controls. To realize benefits 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 models and determine the uncertainty of those models to predict performance and stability. A process of model and control algorithm validation for a dc-dc boost converter circuit based on acceptance sampling is presented here. The verification and validation process described in this dissertation is based on MIL-STD 3022 with emphasis on requirements settings and the validation process. To minimize the cost of experimentation and simulation, design of experiments is used extensively to limit the amount of data taken without losing information.The key contribution of this dissertation include the process for model and control algorithm validation specifically a method for decomposing the problem into a model validation stage and a control algorithm validation stage. The other contributions include a metric for differentiating between strong validation data and weak validation data, projection of model and control uncertainty limits to areas where experimental data has not been taken, and an improved means of tolerance interval calculation for non-parametric distributions.