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.

智能无人机器人系统最近因其具有探索不可访问且动态变化的环境的能力而获得普及。在这些环境中，这些车辆可能会遭受独特类型的干扰，这可能导致任务性能下降。本文描述了一种新型自适应控制的设计，开发和概念证明，该模型结合了模型参考和反馈线性化的概念，并通过活体生物体免疫系统响应中典型的非线性有界函数加以增强。提出了使用圆准则的拟议控制律稳定性的证明。循环仿真中的数字硬件以及实际的实现是使用万向节无微型飞行器飞行器来完成的，该飞行器使用推力矢量控制作动。