Acceleration autopilot for a guided spinning rocket via adaptive output feedback

Uncertainties in control effectiveness, and moment coefficients are among the practical challenges in control of flight vehicles. Adaptive control is known as a proper method to handle uncertain systems, and has been used in numerous applications to improve system performance in the presence of system uncertainties. This paper presents a new method of synthesizing an acceleration autopilot for a guided spinning rocket, which is a class of uncertain, non-square multi-input/multi-output system. Firstly, a nonlinear and coupled six-degree-of-freedom (6-DoF) dynamic model is established, which is used to evaluate the performance of the proposed adaptive autopilot during the whole operating cycle. Secondly, a simple design procedure based on square-up method and linear matrix inequality (LMI) is proposed to design the autopilot, allowing a globally stable adaptive output feedback law to be generated. Finally, the adaptive output feedback autopilot is applied to the nonlinear 6-DoF dynamic model and it is shown to result in stable tracking in the presence of uncertainties.