For event-triggered control, the NCSs are generally continuously monitored and their preset triggering conditions are continuously checked, which is undesirable when the sampling cost is high. Considering this drawback, this chapter investigates a DMPC with self-triggered computation and communication strategy for NCSs with dynamically decoupled subsystems. Firstly, not only control performance but also communication cost are explicitly quantified in the cost function, such that control inputs and the triggering instant are simultaneously optimized and determined, which contributes to achieving a better trade-off between control performance and communication cost. It is noted that the optimized control problem is solved only at triggering instants. In this way, sensor nodes can be in sleep during two successive triggering instants, thereby improving the effectiveness of monitoring and checking. Secondly, only the first element of the solved control input sequence is applied to the subsystem and sent along with the current state to its neighbors for cooperation, so as to reduce communication load. Furthermore, the stability of the whole system is analyzed and sufficient conditions on design parameters are presented.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Self-Triggered DMPC of Networked Systems


    Contributors:


    Publication date :

    2022-10-04


    Size :

    19 pages




    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




    Dynamic Event-Triggered DMPC of Networked Systems

    Zou, Yuanyuan / Li, Shaoyuan | Springer Verlag | 2022


    Mixed Time/Event-Triggered DMPC of Networked Systems

    Zou, Yuanyuan / Li, Shaoyuan | Springer Verlag | 2022


    DMPC of Networked Systems with Event-Triggered Communication

    Zou, Yuanyuan / Li, Shaoyuan | Springer Verlag | 2022


    DMPC of Networked Systems with Event-Triggered Computation

    Zou, Yuanyuan / Li, Shaoyuan | Springer Verlag | 2022