Derivative-Free Adaptive Control serves as a compendium of the authors' scholarship on the development of and theory for adaptive control, referred to herein as Derivative-Free Model Reference Adaptive Control (DF-MRAC). Previous methods of Model Reference Adaptive Control (MRAC) were based on the underlying assumption that plant model uncertainty can be approximated by a set of state dependent basis functions that are parameterized by an unknown but constant set of weights. In DF-MRAC, the viewpoint taken is that ideal weights may be time varying and, in fact, one can do away with the need for choosing a set of basis functions. The book presents a set of reproducible examples that illustrate the important features and advantages of DF-MRAC over conventional MRAC methods, and points out the many circumstances that exist for which a constant parameterization of uncertainty may be difficult or impossible to achieve, particularly in the case of unmodeled dynamics, time varying uncertainties, and exogenous disturbances that may be acting on the system being controlled. Geared toward graduate students, scholars, and experienced designers in the industry, the book clearly illustrates the benefits offered by DF-MRAC by contrasting it with Derivative-Based MRAC. It includes easy to follow and implementable examples, and collects existing results on this subject in one volume.