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—This paper presents a unifying framework for the problem of robust global regulation via output feedback for non-linear systems with integral input-to-state stable inverse dynamics, subject to possibly unknown control direction. The contribution of the paper is twofold. Firstly, we consider the problem of global regulation, instead of global asymptotic(More)
Controlling non-affine non-linear systems is a challenging problem in control theory. In this paper, we consider adaptive neural control of a completely non-affine pure-feedback system using radial basis function (RBF) neural networks (NN). An ISS-modular approach is presented by combining adaptive neural design with the backstepping method, input-to-state(More)
for the "nancial support during his stay in Sydney University for his sabbatical leave in 1998. Abstract This paper describes an application of nonlinear decentralized robust control (Guo, Jiang & Hill, 1998) to large-scale power systems. Decentralized power controllers are designed explicitly to maintain transient stable closed-loop systems. For the "rst(More)
—The theory of power systems dynamics has been developed largely from detailed studies of the dynamics of simple system structures with emphasis on the effects of modeling details of the dynamics. In contrast, the recent study in the science of complex networks, motivated by numerous real-world examples in various areas including power systems, employs(More)