Nakwan Kim

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We consider adaptive output feedback control of uncertain nonlinear systems, in which both the dynamics and the dimension of the regulated system may be unknown. However, the relative degree of the regulated output is assumed to be known. Given a smooth reference trajectory, the problem is to design a controller that forces the system measurement to track(More)
Several extensions to neural network (NN)-based adaptive output feedback control of nonlinear systems are developed. An extension from linearly to nonlinearly parameterized NNs is given for a direct adaptive output feedback approach. An extension that permits the introduction of e-modification in both the direct adaptive approach and an error-observer-based(More)
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