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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)
—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)
One of the amazing successes of biological systems is their ability to "learn by doing" and so adapt to their environment. In this paper, first, a deterministic learning mechanism is presented, by which an appropriately designed adaptive neural controller is capable of learning closed-loop system dynamics during tracking control to a periodic reference(More)
— A frame work of dissipativity theory for switched systems using multiple storage functions and multiple supply rates is set up. The exchange of " energy " between the activated subsystem and an inactivated subsystem is characterized by cross supply rates. Stability is reached when all supply rates are non-positive, as long as the total exchanged energy(More)