3 research outputs found
Sparsely-Packetized Predictive Control by Orthogonal Matching Pursuit
We study packetized predictive control, known to be robust against packet
dropouts in networked systems. To obtain sparse packets for rate-limited
networks, we design control packets via an L0 optimization, which can be
effectively solved by orthogonal matching pursuit. Our formulation ensures
asymptotic stability of the control loop in the presence of bounded packet
dropouts.Comment: 3-page extended abstract for MTNS 2012 with 3 figure
Sparse Packetized Predictive Control for Networked Control over Erasure Channels
We study feedback control over erasure channels with packet-dropouts. To
achieve robustness with respect to packet-dropouts, the controller transmits
data packets containing plant input predictions, which minimize a finite
horizon cost function. To reduce the data size of packets, we propose to adopt
sparsity-promoting optimizations, namely, ell-1-ell-2 and ell-2-constrained
ell-0 optimizations, for which efficient algorithms exist. We derive sufficient
conditions on design parameters, which guarantee (practical) stability of the
resulting feedback control systems when the number of consecutive
packet-dropouts is bounded.Comment: IEEE Transactions on Automatic Control, Volume 59 (2014), Issue 7
(July) (to appear