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<i>H</i>∞ Pinning Control of Complex Dynamical Networks Under Dynamic Quantization Effects: A Coupled Backward Riccati Equation Approach

Shuai Liu, Zidong Wang, Licheng Wang, Guoliang Wei

2020IEEE Transactions on Cybernetics56 citationsDOI

Abstract

In this article, a pinning control strategy is developed for the finite-horizon <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> synchronization problem for a kind of discrete time-varying nonlinear complex dynamical network in a digital communication circumstance. For the sake of complying with the digitized data exchange, a feedback-type dynamic quantizer is introduced to reflect the transformation from the raw signals into the discrete-valued ones. Then, a quantized pinning control scheme takes place on a small fraction of the network nodes with the hope of cutting down the control expenses while achieving the expected global synchronization objective. Subsequently, by resorting to the completing-the-square technique, a sufficient condition is established to ensure the finite-horizon <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> index of the synchronization error dynamics against both quantization errors and external noises. Moreover, a controller design algorithm is put forward via an auxiliary <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$H_{2}$ </tex-math></inline-formula> -type criterion, and the desired controller gains are acquired in terms of two coupled backward Riccati equations. Finally, the validity of the presented results is verified via a simulation example.

Topics & Concepts

Control theory (sociology)Quantization (signal processing)Synchronization (alternating current)Controller (irrigation)Riccati equationNonlinear systemMathematicsAlgebraic Riccati equationComputer scienceControl (management)Topology (electrical circuits)AlgorithmPartial differential equationMathematical analysisCombinatoricsQuantum mechanicsAgronomyPhysicsBiologyArtificial intelligenceNeural Networks Stability and SynchronizationDistributed Control Multi-Agent SystemsNonlinear Dynamics and Pattern Formation
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