Self-Triggered Model Predictive Control for Linear Systems With Switched Cost Functions

Self-Triggered Model Predictive Control for Linear Systems With Switched Cost Functions

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This paper 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 Musical Instruments 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 Cyclist Accessories - Body Armor reduced and Zeno behavior can be excluded.Moreover, asymptotic stability of the networked systems with model predictive control strategy is shown via average dwell-time technique.

Finally, the numerical simulation example is given to illustrate the effectiveness of the proposed methods.