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Finite-Time<i>H</i><sub>∞</sub>State Estimation for Two-Time-Scale Complex Networks Under Stochastic Communication Protocol

Xiongbo Wan, Yong‐Zhi Li, Yuqing Li, Min Wu

2020IEEE Transactions on Neural Networks and Learning Systems76 citationsDOI

Abstract

The issue of finite-time <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$H_{\infty }$ </tex-math></inline-formula> state estimation is studied for a class of discrete-time nonlinear two-time-scale complex networks (TTSCNs) whose measurement outputs are transmitted to a remote estimator via a bandwidth-limited communication network under the stochastic communication protocol (SCP). To reflect different time scales of state evolutions, a new discrete-time TTSCN model is devised by introducing a singular perturbation parameter (SPP). For the sake of avoiding/alleviating the undesirable data collisions, the SCP is adopted to schedule the data transmissions, where the transition probabilities involved are assumed to be partially unknown. By constructing a new Lyapunov function dependent on the information of the SCP and SPP, a sufficient condition is derived which ensures that the resulting error dynamics is stochastically finite-time bounded and satisfies a prescribed <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$H_{\infty }$ </tex-math></inline-formula> performance index. By resorting to the solutions of several matrix inequalities, the gain matrices of the state estimator are given and the admissible upper bound of the SPP can be evaluated simultaneously. The performance of the designed state estimator is demonstrated by two examples.

Topics & Concepts

EstimatorDiscrete time and continuous timeScheduleBounded functionUpper and lower boundsLyapunov functionComputer scienceNonlinear systemMathematicsControl theory (sociology)Applied mathematicsState (computer science)Mathematical optimizationAlgorithmStatisticsMathematical analysisArtificial intelligenceQuantum mechanicsControl (management)PhysicsOperating systemStability and Control of Uncertain SystemsDistributed Control Multi-Agent SystemsNeural Networks Stability and Synchronization
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