@inproceedings{10f7aa7f339247478d8c4d6765af27d3,

title = "Adaptively controlling nonlinear continuous-time systems using neural networks",

abstract = "Layered neural networks are used in a nonlinear adaptive control problem. The plant is an unknown feedback-linearizable continuous-time system, represented in a state space form. A transformation is made on the plant to decompose the plant into two parts: The first part is modeled and controlled by multilayer neural networks. The second part is unobservable and can not be directly influenced by the control; this part is assumed to be stable. The control law is defined in terms of the neural network model to control the plant to track a reference command. The network parameters are updated on-line according to the tracking error. A theorem is given on the convergence of i) the tracking error and ii) the weight updating. The simulation is performed using Advanced Continuous Simulation Language (ACSL).",

author = "Fu-Chuang Chen and Liu, {Chen Chung}",

year = "1992",

month = dec,

day = "1",

doi = "10.23919/ACC.1992.4792016",

language = "English",

isbn = "0780302109",

series = "Proceedings of the American Control Conference",

publisher = "Publ by American Automatic Control Council",

pages = "46--50",

booktitle = "Proceedings of the American Control Conference",

note = "null ; Conference date: 24-06-1992 Through 26-06-1992",

}