The attitude control of a spacecraft is integral to achieving mission success. However, failures in actuators such as reaction wheels are detrimental and can often lead to an early end of mission. We propose a Lyapunov-based adaptive controller that can estimate and compensate for reaction wheels degradation simultaneously. The controller incorporates an adaptive update control law with a gradient-based term and an integral concurrent learning term that collects input/output data for online estimation of uncertain parameters. The proposed controller guarantees attitude tracking and minimal loss of control authority under faulty reaction wheel performance. The controllers performance is tested through a variety of numerical simulations as well as a software-in-the-loop test, where the adaptive controller is run in Python via ROS2, while the environment is simulated in Simulink.