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As nonlinearity and complexity of a nonlinear system increase, it may be more difficult to construct a controller by the mathematical control theory. In such cases, it is very effective to construct t...he controller by using Neural Network(NN), because NNs have capabilities of coping with the nonlinearity and complexity of the nonlinear systems. NN controllers are constructed through learning to minimize a criterion function under certain circumstances. But NN controllers may not work well under very different circumstances from those at learning stage. For example, NN controllers are usually made without considering disturbances because NN controllers do not have a means to supress their influences. So, in case of existing the disturbances NN controllers do not work well. In this paper a robust control system design method for the disturbances is discussed using second order derivatives of Universal Learning Network.続きを見る
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