ROBUST OUTPUT TRACKING FOR UNCERTAIN STRICT-FEEDBACK SYSTEMS WITH UNKNOWN VIRTUAL CONTROL COEFFICIENTS

摘要

In this paper, a class of single-input single-output nonlinear systems in strict-feedback form with unknown virtual control coefficients is considered. The nonlinearities in the system dynamics are taken to be unknown, and are approximated in terms of radial basis functions (using a particular neural-net architecture). The only crucial assumption made on the unknown part of the system is that the parameters representing the neural network architecture and the virtual control coefficients lie in some known compact sets. In this setup, a robust state-feedback controller is designed, under which the system output tracks a given signal arbitrarily well, and all signals in the closed-loop system remain bounded. Moreover, a relevant disturbance attenuation inequality is satisfied by the closed-loop signals.