IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 1 Methods to Design Robust Controllers against Nonlinear and Multiple Uncertainties by Use of Neural Networks Como, Italy July 24-July 27 ISBN: 0-7695-0619-4
In general, both unstructured and structured uncertainties coexist in an uncertain system. Therefore, methods in which either type of uncertainties can be treated are not enough, and it is not assured that designed controller scans stabilize the uncertain system. Moreover, methods to design controllers, which have robust performance even if the system is mutated, are also required. In this paper, methods to design robust controllers for a nonlinear system where both unstructured and structured uncertainties, that is, multiple uncertainties exist. A neural network is effective in designing such a controller, and robustness can be drawn from the training. Effectiveness of proposed some numerical simulations show methods.
Citation:
Hiroaki Nakanishi, Koichi Inoue, "Methods to Design Robust Controllers against Nonlinear and Multiple Uncertainties by Use of Neural Networks," ijcnn, vol. 1, pp.1254, IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 1, 2000 Usage of this product signifies your acceptance of the Terms of Use. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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