We consider a networked control system consisting of a physical plant, an actuator, a sensor, and a controller that is connected to the actuator and sensor via a communication network. The plant is described by a linear discrete-time system subject to additive disturbances. In order to reduce the required number of communications in the system, we propose a robust self-triggered model predictive controller based on rollout techniques that robustly asymptotically stabilizes a certain periodic sequence of sets in the state space while guaranteeing robust satisfaction of hard state and input constraints. At periodically occurring scheduling times, the self-triggered model predictive control algorithm determines the times at which the control input and plant measurement are updated in the time span until the next scheduling time. We establish a certain upper bound on the average sampling rate in the closed-loop system. Moreover, we show how increasing the asymptotic bound on the system state, which is a design parameter in the control scheme, can be used to further reduce the average number of communications in the system.
Communication scheduling in robust self-triggered MPC for linear discrete-time systems
2015-10-01
Brunner , F D , Gommans , T M P , Heemels , W P M H & Allgöwer , F 2015 , ' Communication scheduling in robust self-triggered MPC for linear discrete-time systems ' , IFAC-PapersOnLine , vol. 28 , no. 22 , pp. 132-137 . https://doi.org/10.1016/j.ifacol.2015.10.319
Article (Journal)
Electronic Resource
English
DDC: | 629 |
Launcher attitude control: discrete-time robust design and gain-scheduling
Tema Archive | 2003
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