Abstarct: In this thesis, the design and implementation of a Self-Tuning Regulator (STR) for a two-wheeled balancing robot is investigated. Due to its inherent structure, the two-wheeled robot exhibits severe instability and non-minimum phase behavior, making it a prime candidate for testing novel control methods. The primary objective of the research is to evaluate the performance of the STR under various conditions.Initially, dynamic modeling and discretization of the system are performed to establish the necessary groundwork for controller design. In the first step, the STR is implemented on the variables θ (angle) and δ (angular velocity). The results indicate that in this configuration, the STR successfully stabilizes the unstable dynamics and ensures adequate tracking performance. The control signals also remain within the operational limits of the actuators. Furthermore, the Recursive Least Squares (RLS) adaptive identification algorithm converges rapidly and stabilizes the parameters within fixed intervals.Subsequently, to simulate conditions closer to reality, a cascade structure comprising an inner loop for controlling θ and an outer loop for controlling x is designed. Although it was theoretically expected that this approach could ensure simultaneous stability and tracking, simulation results revealed that the STR alone was insufficient to guarantee stable performance under these conditions. The variable x experienced divergence, and the inner loop for θ lost its stability as well.