Event-based data scheduling for a class of interconnected networked control systems

Abstract

Abstract-In this paper we address the problem of eventbased data scheduling for a class of physically interconnected networked control systems which compete for limited communication resources. The overall interconnected system consists of multiple heterogeneous LTI sub-systems with the physical interconnection being modeled by a directed acyclic graph (DAG). The sub-systems are controlled by a networked controller through a shared communication channel. In order to cope with the limited channel capacity, we introduce a bi-character deterministic-probabilistic scheduling mechanism which dynamically assigns access priorities to each sub-system at each time-step according to an error-dependent priority measure. The sub-systems which are granted channel access then transmit their state information through the communication network. Given an emulation-based control strategy, we prove stability of such networked systems under the proposed scheduling law in terms of f -ergodicity of overall network-induced error. Simulation results illustrate the proposed approach and show a reduction in the error variance compared to standard TDMA and uniform random-access scheduling policies.

Analysis of linear quadratic control loops with decentralized event-triggered sensing: Rate and performance guarantees

“…However, the need to manage communication via ETC is more arguable when several agents in one or more control loops transmit their information to the other agents. In this context, we can either consider settings with several control loops and where the control agents (sensors, actuators and sensors) are independent from the control agents of other loops (and must only share a communication network)see [9]- [11]-, or settings where the control agents pertain to the same (large but possibly sparse) system and are interconnected -see, e.g., [12]- [17]. In the present work we will be mostly interested in the latter setting.…”

“…Most of the works in this setting consider deterministic process models [14]- [17], and there are also a few works considering stochastic process models as we will be considering in this paper [12], [13]. In [12] a system consisting of several interconnected stochastic linear time invariant subsystems is considered.…”

“…Most of the works in this setting consider deterministic process models [14]- [17], and there are also a few works considering stochastic process models as we will be considering in this paper [12], [13]. In [12] a system consisting of several interconnected stochastic linear time invariant subsystems is considered. Assuming that the graph modeling the interconnections between the sub-systems is acyclic, [12] provides a distributed scheduling policy to prioritize the data to be transmitted over the network and establishes fergodicity of the overall error propagating in the network.…”

“…In [12] a system consisting of several interconnected stochastic linear time invariant subsystems is considered. Assuming that the graph modeling the interconnections between the sub-systems is acyclic, [12] provides a distributed scheduling policy to prioritize the data to be transmitted over the network and establishes fergodicity of the overall error propagating in the network. In [13] an upper bound on the average quadratic cost for a decentralized event-triggered output feedback system with wireless communication is provided.…”