Stabilizability of Stochastic Linear Systems with Finite Feedback Data Rates
SIAM Journal on Control and Optimization
Brief paper: On the model-based approach to nonlinear networked control systems
Automatica (Journal of IFAC)
Networked Control Systems: Theory and Applications
Networked Control Systems: Theory and Applications
ACC'09 Proceedings of the 2009 conference on American Control Conference
Schedulability analysis for CAN-based networked control systems with dynamic bandwidth management
ETFA'09 Proceedings of the 14th IEEE international conference on Emerging technologies & factory automation
Network-based robust H∞ control of systems with uncertainty
Automatica (Journal of IFAC)
Exponential stabilisability of finite-dimensional linear systems with limited data rates
Automatica (Journal of IFAC)
Brief Networked control design for linear systems
Automatica (Journal of IFAC)
Control over unreliable networks affected by packet erasures and variable transmission delays
IEEE Journal on Selected Areas in Communications
| Hi-index | 22.14 |
This paper addresses the problem of stabilizing uncertain nonlinear plants over a shared limited-bandwidth packet-switching network. While conventional control loops are designed to work with circuit-switching networks, where dedicated communication channels provide almost constant bit rate and delay, many networks, such as Ethernet, organize data transmission in packets, carrying larger amounts of information at less predictable rates. We adopt a model-based approach to remotely compute a predictive control signal on a suitable time horizon. By exploiting the inherent packets payload, this technique effectively reduces the bandwidth required to guarantee stability. Communications are assumed to be ruled by a rather general protocol model, which encompasses many protocols used in practice. An explicit bound on the combined effects of the maximum time between consecutive accesses to each node (MATI) and the transmission and processing delays (MAD), for both measurements and control packets, is provided as a function of the basin of attraction and the model accuracy. Our control strategy is shown to be robust with respect to sector-bounded uncertainties in the plant model. Sampling of the control signal is also explicitly taken into account. A case study is presented which enlightens the great improvements induced by the packet-based control strategy over methods that send a single control value in each packet.