Abstract
This paper addresses the problem of nonlinear robust adaptive output feedback controller for a class of underactuated aerial vehicles with input and output constraints. To solve the problem, the modular design strategy is proposed for the control design. By using the neural networks (NNs) to approximate system uncertainties and observers to reconstruct system states, robust adaptive output feedback controllers are developed. By using a combination of saturation functions and barrier functions, input and output constraints are simultaneously dealt with. The design methodology shows that a cascaded system of an input-to-state stable (ISS) subsystem driven by an ultimate bounded (UB) subsystem enjoys ultimate boundedness property. In addition, the tracking error converges to adjustable neighbourhoods of the origin.
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