Jianyun Cao

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The second buffer method is put forward to deal with the wrong order of data packets. The Markov characteristic of delay in networked control systems is analyzed. The evaluation method of element in state transition matrix is given when the wrong order of data packet is considered. Jump linear systems methods arc used to analyze the stability of networked(More)
Network-induced delay occurs while exchanging data among devices connected to the shared medium in networked control systems. The realizing methods and conditions of transforming the random time delay to a deterministic time delay are proposed. Basing on the idea of step transforming, the asymptotic stable controller is designed. Basing on the idea of state(More)
Luenberger-like H/sub /spl infin// observer-based compensator design for MIMO bilinear continuous-time systems is discussed via bang-bang control input. Both full-order and reduced-order H/sub /spl infin// observer-based compensators are obtained. These compensators guarantee the stability of the estimations as well as provide disturbance attenuation for(More)
In this paper, robust H/sub /spl infin// control problem is investigated for a class of uncertain linear discrete-time systems with norm-bounded nonlinear uncertainties. The class of systems can be treated as linear nominal parts with nonlinear perturbations on both states and control inputs. By means of linear matrix inequality technique, an approach has(More)
  • Jianyun Cao
  • 2012 Fourth International Conference on…
  • 2012
Using Malmquist index, this paper measures total factor productivity (TFP) of modern service industry in Yangtze River Delta and Pearl River Delta during 2000-2008, analyzes the sources and trends of TFP growth. Conclusions are made as follows: TFP of modern service industry grew rapidly and had a downward trend in the two zones, and the source of economic(More)
In this paper, nonlinear characteristic of a multivariable magnetic suspension system is formulated, and a modified scheme of nonlinear multivariable internal model control (IMC) is put forward, based on neural network inversion. With radial basis function neural network (RBFNN) approximating inversion of the system, the compound system is linearised and(More)
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