Performance-Barrier Event-Triggered Control of a Class of Reaction-Diffusion PDEs
<|reference_start|>Performance-Barrier Event-Triggered Control of a Class of Reaction-Diffusion PDEs: We employ the recent performance-barrier event-triggered control (P-ETC) for achieving global exponential convergence of a class of reaction-diffusion PDEs via PDE backstepping control. Rather than insisting on a strictly monotonic decrease of the Lyapunov function for the closed-loop system, P-ETC allows the Lyapunov function to increase as long as it remains below an acceptable performance-barrier. This approach integrates a performance residual, the difference between the value of the performance-barrier and the Lyapunov function, into the triggering mechanism. The integration adds flexibility and results in fewer control updates than with regular ETC (R-ETC) that demands a monotonic decrease of the Lyapunov function. Our P-ETC PDE backstepping design ensures global exponential convergence of the closed-loop system in the spatial L^2 norm, without encountering Zeno phenomenon. To avoid continuous monitoring of the triggering function that generates events, we develop periodic event-triggered and self-triggered variants (P-PETC and P-STC, respectively) of the P-ETC. The P-PETC only requires periodic evaluation of the triggering function whereas the P-STC preemptively computes the time of the next event at the current event time using the system model and continuously available system states. The P-PETC and P-STC also ensure a Zeno-free behavior and deliver performance equivalent to that of the continuous-time P-ETC which requires continuous evaluation of the triggering function, in addition to the continuous sensing of the state. We provide numerical simulations to illustrate the proposed technique and to compare it with R-ETC associated with strictly decreasing Lyapunov functions.<|reference_end|>
@article{rathnayake2024performance-barrier,
    title={Performance-Barrier Event-Triggered Control of a Class of
  Reaction-Diffusion PDEs},
    author={Bhathiya Rathnayake, Mamadou Diagne, Jorge Cortes, Miroslav Krstic},
    journal={arXiv preprint arXiv:2407.08178},
    year={2024},
    archivePrefix={arXiv},
    eprint={2407.08178},
    primaryClass={eess.SY cs.SY math.OC}
}