U-model-based adaptive control for a class of stochastic non-linear dynamic plants with unknown parameters
by Xueli Wu, Lei Liu, Quanmin Zhu, Wenxia Du, Bin Wang, Jianhua Zhang
International Journal of Modelling, Identification and Control (IJMIC), Vol. 13, No. 3, 2011

Abstract: In this paper, an adaptive control algorithm within a U-model framework is developed for controlling a class of stochastic non-linear discrete-time models with unknown parameters. With the authors' previous justification, the control-oriented model not only represents a wide range of smooth (polynomial) non-linear dynamic plants (without using linearisation approximation at all), but also makes almost all linear control system design techniques directly applicable to non-linear dynamic plants (with a root solver bridging the linear design and calculation of controller output). A new recursive least squares algorithm is derived and its convergence is proved for the online estimation of time-varying parameters. For initial bench test, a pole placement controller for non-linear stochastic polynomial models is designed using the corresponding linear design technique. Accordingly a step by step procedure is listed to implement the adaptive control operation. A number of simulated case studies are conducted to illustrate the efficiency of the claimed insight and design procedure.

Online publication date: Sat, 21-Mar-2015

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