Haris E. Psillakis

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In this paper, for a class of single-input-single-output (SISO) uncertain nonlinear systems, adaptive neural tracking controllers designed for digital computer implementation are proposed. The overall scheme can be considered as a sampled-data adaptive neural control system. As an intermediate result, it is proven that, for a sufficiently small sampling(More)
In this paper, a nonlinear extension of the Georgiou-Smith system is considered and robustness results are proved for a nonlinear PI controller with respect to fast parasitic first-order dynamics. More specifically, for a perturbed nonlinear system with sector bounded nonlinearity and unknown control direction, sufficient conditions for global boundedness(More)
This note examines the robustness properties of the nonlinear PI control method to ignored actuator dynamics. It is proven that global boundedness and regulation can be achieved for sector bounded non-linear systems with unknown control directions if the actuator dynamics are sufficiently fast and the nonlinear PI control gain is chosen from a subclass of(More)
In this brief, an adaptive neural network (NN) controller is proposed for multiple-input-multiple-output (MIMO) nonlinear systems with triangular control structure and unknown control directions. Deadzones are employed in the projection-based NN weight learning laws and the Nussbaum parameter update laws with levels tuned by an innovative switching logic(More)
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