4.7 Article

Adaptive Synchronization for Networked Parabolic PDE Systems With Uncertain Nonlinear Actuator Dynamics

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TCSI.2023.3244345

关键词

Synchronization; Actuators; Mathematical models; Heating systems; Uncertainty; Lyapunov methods; Distributed algorithms; parabolic PDE; multi-agent systems; actuator dynamics; nonlinearity; uncertainty

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This article focuses on the synchronization control of networked uncertain parabolic partial differential equations (PDEs) with uncertain nonlinear actuator dynamics. A novel passive identifier is designed to estimate the states and unknown parameters, and a synchronization controller is presented based on the passive identifier and Lyapunov function method to ensure synchronization control and boundedness of closed-loop signals for cascaded parabolic PDE systems. The effectiveness of the obtained results is illustrated using simulation.
This article focuses on the synchronization control of networked uncertain parabolic partial differential equations (PDEs) with uncertain nonlinear actuator dynamics. Compared to existing networked PDE systems, control input occurs in ordinary differential equation (ODE) subsystems rather than in PDE ones. Compared to existing results, where the exact system parameters must be known for the entire system, this paper further considers parabolic PDE-ODE systems with unknown parameters affecting the interior of the PDE domain. Due to the unknown parameters and uncertain nonlinear actuator dynamics, the existing distributed algorithms and stability analysis tools cannot be utilized to solve the synchronization problem of cascaded parabolic systems. To address this difficulty, this study designs a novel passive identifier to estimate the states and unknown parameters. Subsequently, based on the passive identifier and Lyapunov function method, a synchronization controller is presented for cascaded parabolic PDE systems to ensure that the synchronization control and the boundedness of all the closed-loop signals are achieved. Lastly, the effectiveness of the obtained results is illustrated using simulation.

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