4.7 Article

Quantized H∞ Control for Nonlinear Stochastic Time-Delay Systems With Missing Measurements

Journal

IEEE TRANSACTIONS ON AUTOMATIC CONTROL
Volume 57, Issue 6, Pages 1431-1444

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TAC.2011.2176362

Keywords

H-infinity control; data missing; discrete time-delay systems; networked control systems (NCSs); nonlinear systems; quantized control; stochastic systems

Funding

  1. Engineering and Physical Sciences Research Council (EPSRC) of the U.K. [GR/S27658/01]
  2. Leverhulme Trust of the U.K.
  3. Royal Society of the U.K.
  4. National Natural Science Foundation of China [61028008, 61134009, 61104125, 60974030, 61074016]
  5. Alexander von Humboldt Foundation of Germany

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In this paper, the quantized H-infinity control problem is investigated for a class of nonlinear stochastic time-delay network-based systems with probabilistic data missing. A nonlinear stochastic system with state delays is employed to model the networked control systems where the measured output and the input signals are quantized by two logarithmic quantizers, respectively. Moreover, the data missing phenomena are modeled by introducing a diagonal matrix composed of Bernoulli distributed stochastic variables taking values of 1 and 0, which describes that the data from different sensors may be lost with different missing probabilities. Subsequently, a sufficient condition is first derived in virtue of the method of sector-bounded uncertainties, which guarantees that the closed-loop system is stochastically stable and the controlled output satisfies H-infinity performance constraint for all nonzero exogenous disturbances under the zero-initial condition. Then, the sufficient condition is decoupled into some inequalities for the convenience of practical verification. Based on that, quantized H-infinity controllers are designed successfully for some special classes of nonlinear stochastic time-delay systems by using Matlab linear matrix inequality toolbox. Finally, a numerical simulation example is exploited to show the effectiveness and applicability of the results derived.

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