Disturbance rejection for singular semi-Markov jump neural networks with input saturation

作者：

Highlights：

• An IEID-based non-fragile control problem for SSMJNNs subject to external disturbances and input saturation is formulated.

• A new effective control algorithm is developed to select the gain matrices of the state feedback controller and observer.

• An IEID estimator is implemented to ensure the exponential stability of the considered SSMJNN with disturbance rejections.

• Sufficient conditions are derived for non-fragile controller design of the system under study by using the LMI approach.

摘要

•An IEID-based non-fragile control problem for SSMJNNs subject to external disturbances and input saturation is formulated.•A new effective control algorithm is developed to select the gain matrices of the state feedback controller and observer.•An IEID estimator is implemented to ensure the exponential stability of the considered SSMJNN with disturbance rejections.•Sufficient conditions are derived for non-fragile controller design of the system under study by using the LMI approach.

论文关键词：Singular neural networks,Non-fragile control,Improved equivalent-input-disturbance,Semi-Markov jump,Input saturation

论文评审过程：Received 26 December 2020, Revised 15 March 2021, Accepted 13 April 2021, Available online 8 May 2021, Version of Record 8 May 2021.

论文官网地址：https://doi.org/10.1016/j.amc.2021.126301