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

Jump state estimation with multiple sensors with packet dropping and delaying channels

This work addresses the design of a state observer for systems whose outputs are measured through a communication network. The measurements from each sensor node are assumed to arrive randomly, scarcely and with a time-varying delay. The proposed model of the plant and the network measurement scenarios cover the cases of multiple sensors, out-of-sequence measurements, buffered measurements on a single packet and multirate sensor measurements. A jump observer is proposed that selects a different gain depending on the number of periods elapsed between successfully received measurements and on the available data. A finite set of gains is pre-calculated offline with a tractable optimisation problem, where the complexity of the observer implementation is a design parameter. The computational cost of the observer implementation is much lower than in the Kalman filter, whilst the performance is similar. Several examples illustrate the observer design for different measurement scenarios and observer complexity and show the achievable performance

Robust stabilization of a class of nonlinear systems controlled over communication networks

The paper deals with the stabilization of nonlin-ear systems in which the loop is closed over a lossy non-acknowledged communication network. Given a Regional Input-to-State (ISS) stabilizing state-feedback control law, designedwithout accounting for the network-induced delays, we proposea non-acknowledged communication policy that allows to deploythe above controller over the network without any modification,while preserving the Regional ISS property. The time-varyingdelays and packet dropouts occurring on both the up-link andthe down-link are compensated through a model-based predictionscheme and a packet-management policy based on time-stamping.The consistency of the prediction, which is a major issue inthe context of nonlinear systems with an embedded networkedcontroller, is guaranteed through the exploitation of a novel move-blocking strategy for computing the command sequence to beforwarded to the actuators

Engineering Emergence: A Survey on Control in the World of Complex Networks

Complex networks make an enticing research topic that has been increasingly attracting researchers from control systems and various other domains over the last two decades. The aim of this paper was to survey the interest in control related to complex networks research over time since 2000 and to identify recent trends that may generate new research directions. The survey was performed for Web of Science, Scopus, and IEEEXplore publications related to complex networks. Based on our findings, we raised several questions and highlighted ongoing interests in the control of complex networks.publishedVersio