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Experimental Results of a Model Reference Adaptive Control Approach on an Interconnected Uncertain Dynamical System

The objective of this thesis is to show the experimental validation of recently proposed adaptive control architecture for uncertain dynamical systems. The experimental validation is conducted on a benchmark mechanical system setup composed of two carts, one actuated and one unactuated, physically interconnected through a spring. Specifically, an approach has been recently proposed to stabilize an overall interconnected system in the presence of unknown physical interconnections as well as system uncertainties in the context of model reference adaptive control. This uncertain dynamical system consists of actuated and unactuated portions physically interconnected to each other. In addition, the previous work enforces performance guarantees individually on both the actuated and unactuated portions of the interconnected system. In particular, a set-theoretic model reference adaptive control approach has been used in conjunction with linear matrix inequalities to enforce these performance guarantees that is restricting the respective system error trajectories of the actuated and unactuated dynamics inside a-priori, user defined compact sets. As stated above, the overarching contribution of this thesis is to present experimental results for the purpose of demonstrating the efficacy of the previously proposed approach on a benchmark mechanical system setup involving an actuated cart coupled with an unactuated cart through a spring in the presence of both unknown friction and unknown uncertainties. It is experimentally observed that utilizing the proposed approach stabilizes and restricts the respective system error trajectories of the interconnected system.