A Generalized Robust Control Framework Utilizing Dimensional Analysis

Most engineered systems designed under heavy external constraints share similar dynamics. Using a dimensionless model as system representation, a dimensionless robust controller can be designed and implemented for a class of dynamically similar systems that are different in size. Dimensionless transformations of time scale, inputs and outputs determine a nominal plant model and plant-to-plant uncertainties in a dimensionless form. Using parameter-dependent normalization, a normalized dimensionless model can be derived that has low level of plant-to-plant uncertainties. The benefit of this dimensional analysis is demonstrated by the analysis of a passenger vehicle model for yaw rate control with a database consisting of 36 sets of vehicle data.