Application of recently developed neural network based adaptive output feedback controllers to a diverse range of problems both in simulations and experiments is investigated in this thesis.The purpose is to evaluate the theory behind the development of these controllers numerically and experimentally, identify the needs for further development in practical applications, and to conduct further research in directions that are identified to ultimately enhance applicability of adaptive controllers to real world problems.We mainly focus our attention on adaptive controllers that augment existing fixed gain controllers.A recently developed approach holds great potential for successful implementations on real world applications due to its applicability to systems with minimal information concerning the plant model and the existing controller.In this thesis the formulation is extended to the multi-input multi-output case for distributed control of interconnected systems and successfully tested on a formation flight wind tunnel experiment.The command hedging method is formulated for the approach to further broaden the class of systems it can address by including systems with input nonlinearities.Also a formulation is adopted that allows the approach to be applied to non-minimum phase systems for which non-minimum phase characteristics are modeled with sufficient accuracy and treated properly in the design of the existing controller.It is shown that the approach can also be applied to augment nonlinear controllers under certain conditions and an example is presented where the nonlinear guidance law of a spinning projectile is augmented.Simulation results on a high fidelity 6 degrees-of-freedom nonlinear simulation code are presented.The thesis also presents a preliminary adaptive controller design for closed loop flight control with active flow actuators.Behavior of such actuators in dynamic flight conditions is not known.To test the adaptive controller design in simulation, a fictitious actuator model is developed that fits experimentally observed characteristics of flow control actuators in static flight conditions as well as possible coupling effects between actuation, the dynamics of flow field, and the rigid body dynamics of the vehicle.
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Neural Network Based Adaptive Output Feedback Control: Applications and Improvements