Event-Triggered Variable Structure Control

This paper presents a novel Variable Structure Control (VSC) algorithm of Event- Triggered (ET) type, capable of dealing with a class of nonlinear uncertain systems. By virtue of its ET nature, the algorithm can be used as the kernel of a robust networked control system. The design objective is indeed to reduce the number of transmissions over the network. This has to be done while guaranteeing that the proposed ET-VSC is a stabilizing law with appropriate robustness property in front of matched uncertainties, even in presence of delayed transmissions. The proposed algorithm is theoretically analyzed in the paper, proving that the sliding variable associated with the controlled system results in being ultimately confined into a boundary layer of prescribed amplitude. As a consequence, it is proved that the state of the considered uncertain nonlinear system is ultimately bounded as well. Moreover, a lower bound for the time elapsed between consecutive triggering events is provided, which excludes the notorious Zeno behavior. Finally, the designed event- triggered variable structure control scheme is satisfactorily assessed in simulation

EVENT-TRIGGERED SLIDING MODE CONTROL FOR CONSTRAINED NETWORKED CONTROL SYSTEMS

The paper describes a Non-linear Control (ETNC) approach for constrained Networked Feedback Control Systems (NFCS). The real-time controller execution is implemented based on the Event-triggering paradigm. A  nonlinear variable structure is used for the controller design. The nonlinear approach is based on the predefined sliding variable defined by the system states with a nonlinear switching function. The system's stability is analyzed regarding the evolution of the sliding variable. The Event-Triggered operation of the nonlinear controller is based on the prescribed triggering rule. The stability boundary of the sliding variable is subject to the preselected triggering condition, whose selection is a tradeoff of system performance, networks constraints and transmission capabilities. The main focus of the Event triggering approach is lowering network resources utilization in the steady-state behavior of the NFCS. The presented approach ensures a non-zero inter-event time of controller execution, which enables scheduling and optimization of the network operation regarding the network constraints and real-time system performance. The efficiency of the presented method is presented with a comparison of the classical time triggering approach.  The real measurement supports the results

Overcoming Bandwidth Limitations in Wireless Sensor Networks by Exploitation of Cyclic Signal Patterns: An Event-triggered Learning Approach

Wireless sensor networks are used in a wide range of applications, many of which require real-time transmission of the measurements. Bandwidth limitations result in limitations on the sampling frequency and number of sensors. This problem can be addressed by reducing the communication load via data compression and event-based communication approaches. The present paper focuses on the class of applications in which the signals exhibit unknown and potentially time-varying cyclic patterns. We review recently proposed event-triggered learning (ETL) methods that identify and exploit these cyclic patterns, we show how these methods can be applied to the nonlinear multivariable dynamics of three-dimensional orientation data, and we propose a novel approach that uses Gaussian process models. In contrast to other approaches, all three ETL methods work in real time and assure a small upper bound on the reconstruction error. The proposed methods are compared to several conventional approaches in experimental data from human subjects walking with a wearable inertial sensor network. They are found to reduce the communication load by 60–70%, which implies that two to three times more sensor nodes could be used at the same bandwidth

Event-triggered distributed H∞ state estimation with packet dropouts through sensor networks

This study is concerned with the event-triggered distributed H∞ state estimation problem for a class of discrete-time stochastic non-linear systems with packet dropouts in a sensor network. An event-triggered communication mechanism is adopted over the sensor network with hope to reduce the communication burden and the energy consumption, where the measurements on each sensor are transmitted only when a certain triggering condition is violated. Furthermore, a novel distributed state estimator is designed where the available innovations are not only from the individual sensor, but also from its neighbouring ones according to the given topology. The purpose of the problem under consideration is to design a set of distributed state estimators such that the dynamics of estimation errors is exponentially mean-square stable and also the prespecified H∞ disturbance rejection attenuation level is guaranteed. By utilising the property of the Kronecker product and the stochastic analysis approaches, sufficient conditions are established under which the addressed state estimation problem is recast as a convex optimisation one that can be easily solved via available software packages. Finally, a simulation example is utilised to illustrate the usefulness of the proposed design scheme of event-triggered distributed state estimators.This work was supported in part by Royal Society of the UK, the National Natural Science Foundation of China under Grants 61329301, 61203139, 61473076, 61374127 and 61422301, the Shanghai Rising-Star Program of China under Grant 13QA1400100, the ShuGuang project of Shanghai Municipal Education Commission and Shanghai Education Development Foundation under Grant 13SG34, the Fundamental Research Funds for the Central Universities, DHU Distinguished Young Professor Program, and the Alexander von Humboldt Foundation of Germany

Value of Information in Feedback Control

In this article, we investigate the impact of information on networked control systems, and illustrate how to quantify a fundamental property of stochastic processes that can enrich our understanding about such systems. To that end, we develop a theoretical framework for the joint design of an event trigger and a controller in optimal event-triggered control. We cover two distinct information patterns: perfect information and imperfect information. In both cases, observations are available at the event trigger instantly, but are transmitted to the controller sporadically with one-step delay. For each information pattern, we characterize the optimal triggering policy and optimal control policy such that the corresponding policy profile represents a Nash equilibrium. Accordingly, we quantify the value of information $\operatorname{VoI}_k$ as the variation in the cost-to-go of the system given an observation at time $k$. Finally, we provide an algorithm for approximation of the value of information, and synthesize a closed-form suboptimal triggering policy with a performance guarantee that can readily be implemented