A hyperstable neural network for the modelling and control of nonlinear systemsWarwick, K., Zhu, Q. M. and Ma, Z. (2000) A hyperstable neural network for the modelling and control of nonlinear systems. Sadhana: Academy Proceedings in Engineering Sciences, 25 (2). pp. 169-180. ISSN 0256-2499 Full text not archived in this repository. It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing. To link to this item DOI: 10.1007/BF02703757 Abstract/SummaryA multivariable hyperstable robust adaptive decoupling control algorithm based on a neural network is presented for the control of nonlinear multivariable coupled systems with unknown parameters and structure. The Popov theorem is used in the design of the controller. The modelling errors, coupling action and other uncertainties of the system are identified on-line by a neural network. The identified results are taken as compensation signals such that the robust adaptive control of nonlinear systems is realised. Simulation results are given.
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