One Step Anti-Windup Design for a Class of Time-Delayed Cellular Neural Networks

Zha, Miao; He, Huacan

doi:10.1109/imcec.2018.8469524

Cited by 1 publication

(1 citation statement)

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“…Both time-delays and input saturation were mentioned but it did not discuss the distribute time-delays. Zha et al [47] proposed an algebraic antiwindup compensation design for a class of time-delayed CNNs. It is similar to this paper but it did not discuss the distribute time-delays.…”

Section: Introductionmentioning

confidence: 99%

Anti-windup compensation design for a class of distributed time-delayed cellular neural networks

He¹,

Zha²,

Bian³

2019

Jsee

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Both time-delays and anti-windup (AW) problems are conventional problems in system design, which are scarcely discussed in cellular neural networks (CNNs). This paper discusses stabilization for a class of distributed time-delayed CNNs with input saturation. Based on the Lyapunov theory and the Schur complement principle, a bilinear matrix inequality (BMI) criterion is designed to stabilize the system with input saturation. By matrix congruent transformation, the BMI control criterion can be changed into linear matrix inequality (LMI) criterion, then it can be easily solved by the computer. It is a one-step AW strategy that the feedback compensator and the AW compensator can be determined simultaneously. The attraction domain and its optimization are also discussed. The structure of CNNs with both constant timedelays and distribute time-delays is more general. This method is simple and systematic, allowing dealing with a large class of such systems whose excitation satisfies the Lipschitz condition. The simulation results verify the effectiveness and feasibility of the proposed method.

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Section: Introductionmentioning

confidence: 99%