In this work, Periodic Event-Triggered Sampling (PETS) and dual-rate control techniques are integrated in a Wireless Networked Control System (WNCS), where time-varying network-induced delays and packet disorder are present. Compared to the conventional Time- Triggered Sampling (TTS) paradigm, the control solution is able to considerably reduce network utilization (number of transmissions), while retaining a satisfactory control performance. Stability for the proposed WNCS is assured using Linear Matrix Inequalities (LMIs). Simulation results show the main benefits of the control approach, which are experimentally validated by means of an Unmanned Aerial Vehicle (UAV) based test-bed platform.

A consistent event-triggered control (ETC) policy is defined as a policy that outperforms the performance of periodic control for the same average transmission rate and does not generate transmissions in the absence of disturbances. In this paper, we propose a threshold-based policy for periodic event-triggered control that is consistent. Simulation results illustrate the strengths of the proposed method.

This paper addresses networked control systems that can be modelled by Markov jump linear systems, including linear control systems with correlated random delays and correlated random packet drops. Our analysis focusses on the statistical moments (mean and variance) of the modelled system. We start by establishing that the map between the deterministic input of the system and the statistical moments of the state and output can be described by a time-invariant system. Then, we use this fact to provide a frequency domain analysis framework that allows for computing the mean and bounding the variance of the time response of the system to any deterministic input based on a graphical method. For the special case of networked control systems with independent and identically distributed delays and drops we formally establish that our variance bounds are tighter than the ones provided in previous work. We apply the results to the remote control of a linear process. We obtain the delays experimentally by having two remote processors communicate through two XBee modules. Based on this experimental data, we conclude that the delays between two consecutive transmissions are correlated and us

Consider a network of multiple independent stochastic linear systems where, for each system, a scheduler collocated with the sensors arbitrates data transmissions to a corresponding remote controller through a shared contention-based communication network. While the systems are physically independent, their optimal controller design problems may, in general, become coupled, due to network contention, if the schedulers trigger transmissions based on state-dependent events. In this article, we propose a class of probabilistic admissible schedulers for which the optimal controllers, with respect to local standard linear-quardatic Gaussian (LQG) costs, have the certainty equivalence property and can still be determined decentrally. Then, two subclasses of scheduling policies within this class are introduced; a nonevent-based subclass, so called purely stochastic transmission (PST) policy, and an event-based subclass, both with easily adjustable triggering probabilities at every time step. We then prove that, given a PST policy with given triggering probabilities and an associated closed-loop performance with optimal control law, we can find an event-based scheduler from the proposed subclass and with the same triggering probabilities for which the associated closed-loop performance with optimal control law is strictly superior. Moreover, we show that, for each closed-loop system, the optimal state estimators for both scheduling policies follows a linear iteration. Finally, we provide a method to regulate the triggering probabilities of the schedulers by maximizing a network utility function.