A Sampled-Data Approach to Nonlinear Dynamic Inversion Adaptive Control
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2018, American Institute of Aeronautics and Astronautics Inc, AIAA. All right reserved. Sampled-data control laws that are synthesized in a continuous-time framework are vulnerable to the destabilizing effect of sampling if it is not properly accounted for. This is a well documented phenomenon. For sampled-data systems that are nonlinear, the inability to model the system with an exact discrete time representation presents another challenge in achieving stabilization. This paper develops a nonlinear dynamic inversion adaptive control technique which is capable of controlling nonlinear sampled-data systems without linearizing the system dynamics, and is robust to model and parameter uncertainties. The system is approximated using a nonlinear discretization scheme and it is shown that there exists a controller sample time T for which both the discrete approximation and the true continuous time system will be stabilized. This sampled-data nonlinear dynamic inversion adaptive control technique is demonstrated on a nonlinear F-16 aircraft simulation.
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2018 AIAA Guidance, Navigation, and Control Conference
