Dynamic Output Feedback Fuzzy Control of Large-Scale Nonlinear Networked Systems: A Two-Channel Triggering Approach

Abstract

Decentralized output-feedback (DOF) event-triggering control for large-scale nonlinear networked systems is examined in this paper. The Takagi-Sugeno model is applied to describe each nonlinear subsystem, where it shares the communication information through networks. A DOF control scheme with event-triggering is proposed, where two event-triggering mechanisms are placed in the sensor and in the actuator, respectively. Our goal is to design the DOF controller, which not only guarantees the stability of closed-loop control system but also reduces the data communication in the sensor-to-controller channels and controller-to-actuator channels. First, a novel model transformation is presented, where the closed-loop control system is reconstructed as a constant-delay system with extra feedback interconnections. By introducing a relaxing Lyapunov-Krasovskii functional combining with the scaled small gain theorem, the co-design consisting of the controller gains, event-triggered parameter, and sampled period is derived in the form of linear matrix inequality. The effectiveness of the proposed method is validated via a numerical example.