Event‐triggered output feedback H_∞ control for networked control systems

Abstract

Summary This paper investigates event‐triggered output feedback H∞ control for a networked control system. Transmitted through a network under an event‐triggered scheme, the sample outputs of the plant are used to drive the dynamical output feedback controller to generate a new control signal in the discrete‐time domain. The discrete‐time control signals are also transmitted through the network to drive the plant. As a result of two types of transmission delays, the controlled plant and the dynamical output feedback controller are driven by the discrete‐time outputs and control signals at different instants of time. An interval decomposition method is introduced to place the controlled plant and the output feedback controller into the same updated time interval but with updated signals at different instants. Based on a proper Lyapunov‐Krasovskii functional, sufficient conditions are derived to ensure H∞ performance for the controlled plant. Finally, numerical simulations are used to demonstrate the practical utility of the proposed method.

Generalized sliding event‐triggered control for dissipative performance of Markov switching dynamic systems

“…The characteristics of linear adjustment and exponential adjustment of triggering frequency in the generalized sliding event-triggered scheme are included due to the flexibility of the parameters 𝜖 0 , 𝜖 1 , 𝜖 2 compared to the studies. 32,33 Through mathematical conditions of the scheme, it is not difficult to analyze that 𝜖 0 is used for linear adjustment and 𝜖 1 , 𝜖 2 for exponential adjustment. Further, the setting of 𝜖 1 makes the current triggering time instant have a strong correlation with the previous triggering time instant except the classic triggering error, which reflects a twofold triggering adjustment.…”

“…Remark The characteristics of linear adjustment and exponential adjustment of triggering frequency in the generalized sliding event‐triggered scheme are included due to the flexibility of the parameters $$$ {\epsilon}_0 $$$, $$$ {\epsilon}_1 $$$, $$$ {\epsilon}_2 $$$ compared to the studies 32,33 . Through mathematical conditions of the scheme, it is not difficult to analyze that $$$ {\epsilon}_0 $$$ is used for linear adjustment and $$$ {\epsilon}_1 $$$, $$$ {\epsilon}_2 $$$ for exponential adjustment.…”

The ℓ∞/p$$ {\ell}_{\infty /p} $$‐gains for discrete‐time observer‐based event‐triggered systems

“…As an extension of the $$$ {H}_{\infty } $$$ analysis of the typical feedback control systems, 20‐25 the gain from $$$ {\ell}_2 $$$ to $$$ {\ell}_2 $$$ of observer‐based ETSs is described in References 18 and 19 through the linear matrix inequality (LMI) approach. However, taking the $$$ {\ell}_2 $$$ space as in References 18 and 19 is confined itself to decaying signals, and thus some practical problems cannot be tackled by using the arguments in those studies.…”