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Considering of the nonlinear, time-variable and non-minimum phase character and the easy variance of hydro-turbine governing system's structure and parameters, a new adaptive inverse control method of hydro-turbine governing system based on the learning characteristic of neural network and the function approximation ability of the wavelet analysis is presented. It approximates the model and its inversion...
A nonaffine discrete-time system represented by the nonlinear autoregressive moving average with eXogenous input (NARMAX) representation with unknown nonlinear system dynamics is considered. An equivalent affinelike representation in terms of the tracking error dynamics is first obtained from the original nonaffine nonlinear discrete-time system so that reinforcement-learning-based near-optimal neural...
Several empirical studies have demonstrated the feasibility of employing neural networks as models of nonlinear dynamical systems. This paper develops the appropriate mathematical tools for synthesizing and analyzing stable neural network based identification and control schemes. Feedforward network architectures are combined with dynamical elements, in the form of stable filters, to construct a general...
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