Bio-Inspired Feedback Linearized Adaptive Control For a Thrust Vectoring Free-Flyer Vehicle

Intelligent unmanned robotic systems have recently gained popularity due to their ability to potentially explore inaccessible and dynamically changing environments. In these environments, these vehicles might be subjected to unique types of disturbances that may lead to mission performance degradation. This paper describes the design, development and proof of concept of a novel adaptive control that combines concepts from model reference and feedback linearization and it is augmented via nonlinear bounded functions typical in immune system responses of living organisms. Proof of stability of the proposed control law using Circle Criterion is presented. Numerical hardware in the loop simulations along with actual implementation are performed using a gimbaled mini-free flyer vehicle that uses thrust vectoring control actuation. A set of performance index metrics are used to quantify and assess the performance of the adaptive control system which shows stabilizing capabilities in the presence of system disturbances and uncertainties.