NN-based output feedback adaptive variable structure control for a class of non-affine nonlinear systems: A nonseparation principle design

Based on non-separation principle design and the application of Implicit Function Theorem, Mean Value Theorem, neural network parametrization and a simple linear observer, a new adaptive variable structure output feedback control is addressed for a class of non-affine nonlinear systems. In the presented scheme, many restrictive conditions, such as Lipschitz assumption, SPR (strictly positive realness) condition and contracting assumption are not required with the help of neural network parametrization. One of the main purposes of this work is to find out the relationships between the design parameters for observer and controller, and how to choose these design parameters in non-separation principle way. Semi-globally uniformly ultimate boundedness for the steady-state and transient performance is provided, and simulations verify the effectiveness of the proposed scheme.

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