This paper Cuddle Kits investigates the self-triggered model predictive control for networked linear systems.The self-triggered mechanism is designed based on switched cost functions, which can be used to enhance systems performance and are more appropriate for complex industrial requirements in contrast with a single cost function approach.The model predictive controller is designed by solving an optimization problem and the self-triggered condition is designed.
With the proposed self-triggered mechanism, much network computation and communication burden are reduced and Zeno behavior can be excluded.Moreover, asymptotic stability of the networked systems with model predictive control Bosch Logixx HBM56B551B Built-In Double Electric Oven strategy is shown via average dwell-time technique.Finally, the numerical simulation example is given to illustrate the effectiveness of the proposed methods.