404 research outputs found
Event-triggered control cannot improve the gain of optimal periodic control and transmit at a smaller average rate
We consider a standard discrete-time event-triggered control setting by which
a scheduler collocated with the plant's sensors decides when to transmit sensor
data to a remote controller collocated with the plant's actuators. When the
scheduler transmits periodically with period larger than or equal to one, the
optimal controller guarantees an optimal attenuation bound (
gain) from any square-summable disturbance input to a plant's output. We show
that, under mild assumptions, there does not exist a controller and scheduler
pair that strictly improves the optimal attenuation bound of periodic control
with a smaller average transmission rate. Equivalently, given any controller
and scheduler pair, there exists a square-summable disturbance such that either
the attenuation bound or the average transmission rate are larger than or equal
to those of optimal periodic control
Optimal sampling schedules for and state-feedback control
We consider a discrete-time linear system for which the control input is
updated at every sampling time, but the state is measured at a slower rate. We
allow the state to be sampled according to a periodic schedule, which dictates
when the state should be sampled along a period. Given a desired average
sampling interval, our goal is to determine sampling schedules that are optimal
in the sense that they minimize the or the closed-loop norm,
under an optimal state-feedback control law. Our results show that, when the
desired average sampling interval is an integer, the optimal state sampling
turns out to be evenly spaced. This result indicates that, for the and
performance metrics, there is relatively little benefit to go beyond
constant-period sampling
Estimation over Communication Networks: Performance Bounds and Achievability Results
This paper considers the problem of estimation over communication networks. Suppose a sensor is taking measurements of a dynamic process. However the process needs to be estimated at a remote location connected to the sensor through a network of communication links that drop packets stochastically. We provide a framework for computing the optimal performance in the sense of expected error covariance. Using this framework we characterize the dependency of the performance on the topology of the network and the packet dropping process. For independent and memoryless packet dropping processes we find the steady-state error for some classes of networks and obtain lower and upper bounds for the performance of a general network. Finally we find a necessary and sufficient condition for the stability of the estimate error covariance for general networks with spatially correlated and Markov type dropping process. This interesting condition has a max-cut interpretation
Group Chase and Escape
We describe here a new concept of one group chasing another, called "group
chase and escape", by presenting a simple model. We will show that even a
simple model can demonstrate rather rich and complex behavior. In particular,
there are cases in which an optimal number of chasers exists for a given number
of escapees (or targets) to minimize the cost of catching all targets. We have
also found an indication of self-organized spatial structures formed by both
groups.Comment: 13 pages, 12 figures, accepted and to appear in New Journal of
Physic
A non-uniform predictor-observer for a networked control system
The final publication is available at Springer via http://dx.doi.org/10.1007/s12555-011-0621-5This paper presents a Non-Uniform Predictor-Observer (NUPO) based control approach in order to deal with two of the main problems related to Networked Control Systems (NCS) or Sensor Networks (SN): time-varying delays and packet loss. In addition, if these delays are longer than the sampling period, the packet disordering phenomenon can appear. Due to these issues, a (scarce) nonuniform, delayed measurement signal could be received by the controller. But including the NUPO proposal in the control system, the delay will be compensated by the prediction stage, and the nonavailable data will be reconstructed by the observer stage. So, a delay-free, uniformly sampled controller design can be adopted. To ensure stability, the predictor must satisfy a feasibility problem based on a time-varying delay-dependent condition expressed in terms of Linear Matrix Inequalities (LMI). Some aspects like the relation between network delay and robustness/performance trade-off are empirically studied. A simulation example shows the benefits (robustness and control performance improvement) of the NUPO approach by comparison to another similar proposal. © ICROS, KIEE and Springer 2011.This work was supported by the Spanish Ministerio de Ciencia y Tecnologia Projects DPI2008-06737-C02-01 and DPI2009-14744-C03-03, by Generalitat Valenciana Project GV/2010/018, by Universidad Politecnica de Valencia Project PAID06-08.Cuenca Lacruz, ÁM.; García Gil, PJ.; Albertos Pérez, P.; Salt Llobregat, JJ. (2011). A non-uniform predictor-observer for a networked control system. International Journal of Control, Automation and Systems. 9(6):1194-1202. doi:10.1007/s12555-011-0621-5S1194120296K. Ogata, Discrete-time Control Systems, Prentice-Hall, Inc., Upper Saddle River, NJ, USA, 1987.Y. Tipsuwan and M. Chow, “Control methodologies in networked control systems,” Control Eng. 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