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|Title:||Quantized control design for cognitive radio networks modeled as nonlinear semi-Markovian jump systems|
|Citation:||IEEE Transactions on Industrial Electronics, 2015; 62(4):2330-2340|
|Publisher:||Institute of Electrical and Electronics Engineers|
|Fanbiao Li, Peng Shi, Ligang Wu, Michael V. Basin, and Cheng-Chew Lim|
|Abstract:||This paper is concerned with the quantized control design problem for a class of semi-Markovian jump systems with repeated scalar nonlinearities. A semi- Markovian system of this kind has been transformed into an associated Markovian system via a supplementary variable technique and a plant transformation. A sufficient condition for associated Markovian jump systems is developed. This condition guarantees that the corresponding closed-loop systems are stochastically stable and have a prescribed H∞ performance. The existence conditions for full- and reduced-order dynamic output feedback controllers are proposed, and the cone complementarity linearization procedure is employed to cast the controller design problem into a sequential minimization one, which can be solved efficiently with existing optimization techniques. Finally, an application to cognitive-radio systems demonstrates the efficiency of the new design method developed.|
|Keywords:||Cognitive radio (CR) network; output feedback control; quantization; repeated scalar nonlinearity; semi-Markovian jump systems (S-MJSs)|
|Rights:||© 2014 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission.|
|Appears in Collections:||Electrical and Electronic Engineering publications|
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