Communication-Control Codesign for Large-Scale Wireless Networked Control Systems

Stability analysis of large-scale distributed networked control systems with random communication delays: A switched system approach

Tradeoffs between quality-of-control and quality-of-service in large-scale nonlinear networked control systems

Using a multi-purpose communication network in large-scale control systems raises new opportunities and challenges. Among others, the challenges result mostly from variable communication delays, medium access constraints, and resource constraints. A design strategy which considers all of these challenges in one framework is of special importance. For this purpose, an event-based control and scheduling (EBCS) codesign strategy for large-scale networked control systems with all aforementioned challenges is proposed in this paper. The communication delay is represented as an uncertain variable belonging to a finite set of different bounded intervals where the transition between them is according to a stochastic process. The proposed EBCS strategy is formulated as an LMI optimization problem and evaluated for a simultaneous guidance of three mobile robots.

In this tutorial presentation we focus on the construction of Lyapunov or storage functions for large-scale networked control systems (NCSs) in which sensors, controllers and actuators are connected via multiple (local) communication networks which operate asynchronously and independently of each other. Within each packet-based communication network only one node can communicate at a given transmission time (requiring communication protocols) and the transmission intervals and delays may vary over time. These artefacts cause network-induced communication errors in the overal closed-loop system and can be detrimental for stability and performance. For these NCSs we provide explicit constructions of Lyapunov functions by modelling the large-scale NCS as an interconnection of a finite or even an infinite number of hybrid subsystems, and combining ‘local’ Lyapunov functions for the controlled dynamics (including network-induced errors) and the protocols in a systematic manner. These constructions lead to the numerical computation of maximum allowable transmission intervals (MATIs) and maximum allowable delays (MADs) for each of the individual networks. The availability of the Lyapunov or storage functions guarantee properties such as global asymptotic or exponential stability, input-to-state stability (ISS) and L p -stability for the large-scale NCS. Interestingly, the control performance expressed in terms of ISS and L p -gains can be traded with the network parameters (MATIs and MADs). Hence, tradeoffs can be made between the quality-of-control of the overal hybrid system and the required quality-of-service of the underlying communication infrastructure. Also event-triggered communication schemes will be shortly discussed. The results are illustrated with an example of vehicle platooning.

In this paper we consider large-scale networked control systems (NCSs) with multiple communication networks connecting sensors, controllers and actuators. Using a recently developed small-gain theorem for general interconnections of hybrid systems, we are able to find to find a maximum allowable transmission interval (MATI) and a maximum allowable delay (MAD) for each individual network, such that input-to-state stability of the complete NCS is guaranteed.

This paper investigates the problem of sensor-network-based distributed control for large-scale networked control systems, in which the communication constraint and topology switching problems are addressed. In the considered system, a discrete-time interconnected process is controlled by a network of sensors, controllers, and actuators that collect information about the plant, and apply control actions to manage the plant dynamics. The motivation for this paper is that the communication between the plant network and the controller network can be exploited for the system-wide purpose. To deal with the communication constraint problem, strategies such as the event-based communication and logarithmic quantization are applied. Furthermore, in a networked environment, the real-time information of the topology switching is not always available at the controller network side, hence a bunch of synchronous/asynchronous controllers are designed such that the closed-loop system is exponentially stable and achieves a prescribed ${H_\infty }$ disturbance attenuation level. Finally, an illustrative example on a benchmark continuous stirred-tank reactor system is presented to demonstrate the effectiveness of the proposed new control technique.

In large-scale networked control systems (NCSs), an important issue is how to guarantee the systems performance under the limited network bandwidth and stochastic cyber attacks. Centralized event-triggering mechanisms (ETMs) are now regarded as a desirable solution to ease the bandwidth pressure, but the application in large-scale NCSs is constrained by overall management complexity. In this paper, we will firstly propose a software defined centralized ETM to cost-efficiently conduct event-triggering decision based on global system states so as to assure the system transmission performance. Then, by taking deception attacks, which can hardly be detected and pose serious threats to NCSs, into account, we study secure control problem over a large-scale NCS with the presented centralized ETM. The considered deception attacks compromise controller-to-actuator channels, and the specific behaviors of the attacks on different channels are depicted by different Bernoulli processes. To solve the problem, a formal model of the envisioned large-scale system is established, the sufficient conditions that achieving the uniformly ultimately bounded (UUB) stability of the formulated system are analyzed, and then the controller gains are designed accordingly. The effectiveness of the proposed approach is finally validated by an illustrative example.

This paper proposes a new multi-agent platform for Fault Tolerant Control (FTC) Systems. Several multi-agent platforms exist to deal with different problems but none of them to deal with control systems tolerant to faults using the Matlab/Simulinkreg environment, which is in our days the scientific bench to this kind of research. When dealing with large-scale complex networked control systems (NCS), designing FTC systems is a very difficult task due to the large number of sensors and actuators spatially distributed and network connected. To solve this issue, the FTC platform presented in this paper uses simple and verifiable principles coming mainly from a decentralized design based on causal modelling partitioning of the NCS and distributed computing using multi- agent systems paradigm, allowing the use of agents with well established FTC methodologies or new ones developed taking into account the NCS specificities.

Recently, the incorporation of telecommunication technology with control systems provides the usability of remote measurement signals for the designing of networked controllers for geographically distributed large-scale systems. However, communication network introduces new difficulties such as time delays and packet dropouts to the design of networked controllers. This paper presents a new Distributed Networked Control Scheme (DNCS) and its stability analysis for stabilizing of large-scale systems with interconnected subsystems featuring both random delays and random packet dropouts in their communication links. Firstly, a general model for large scale distributed networked system consisting of subsystems is used in which the state of each subsystem has its own time varying delay and there are also delays and packet dropouts in their interconnection communication links. To compensate the influence of subsystems on each other and enhance performance and stability margin of the closed-loop system, a suitable distributed control scheme is proposed. The stability criteria are provided based on Lyapunov-Krasovskii and Linear Matrix Inequality (LMI) techniques. For this, a new type of Lyapunov-Krasovskii functional and certain slack matrices are developed to conclude some LMI-based delay-dependent theorems for designing the control law, as well as the stabilizing of the DNCS. To evaluate the proposed method, three illustrative examples are provided. To indicate the efficiency of the suggested approach, a small-gain-based approach and an observer-based consensus method are applied for comparison. Simulation results show the effectiveness of the proposed approach to enhance the performance of large-scale networked systems among a non-ideal communication network.

In recent years, a variety of wired and wireless network communication protocols in the field of industrial control have become increasingly mature. The purpose of this paper is to provide a Shared network communication bandwidth optimization management algorithm for large-scale industrial networked control systems in Internet of things applications. This algorithm is based on the generalized geometric convex optimization method and can realize the optimal allocation of Shared network communication bandwidth resources. L2 networked control systems is used in this paper for the establishment of various numerical relations between the control performance and the communication network parameters. Based on the generalized geometric convex optimization method for the numerical relationship between convex analysis and fitting, convexity, and with the convex analysis and the numerical relationship between convexity fitting as constraint conditions, the results of integrity for networked control systems with large-scale resource allocation target will share the optimal management of network resources as a generalized geometric convex optimization problem. Using convex optimization software package for optimizing the optimal global solution of management problem, i. e. the optimal allocation of resources, the algorithm realizes the stability of each networked control system and achieve optimal L2 control performance. It is concluded that the predetermined transmission rate between the network node one and network node two, the data flow information sent by the network node two to the network node one is read, the delay time and packet loss rate between the two nodes are determined, the delay time is reduced by about 8 seconds, and the packet loss rate is greatly reduced by 78%.

This paper examines a passivity-based I/O approach for stabilization of large scale networked control systems (NCSs) with event-driven communication. We use a cellular model to model the large scale NCSs and assume that each subsystem is an output feedback passive (OFP) system. We propose a distributed event-driven communication strategy, where each subsystem broadcasts its output information to its neighbors only when the subsystem's local output novelty error exceeds a specified threshold. Based on the proposed event-driven communication strategy, the studied large scale NCSs is finite-gain ℒ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> stable in the presence of bounded external disturbances. The triggering condition is related to the topology of the underlying communication graph. We also provide a way to analyze the time interval between two consecutive communication broadcasts(the inter-event time). Simulation results are shown at the end.

Deep reinforcement learning for scheduling in large-scale networked control systems

A Matlab/Simulink Multi-agent Toolkit for Distributed Networked Fault Tolerant Control System

The robust control problem has been investigated for a class of large-scale nonlinear networked control systems with nonlinear sector input. The time delays have been inherent for the systems because of the information transmission through the communication networks. By T-S fuzzyfication for each subsystem, the interconnected T-S fuzzy subsystems are obtained. When the bound parameters are known, the decentralized memoryless state feedback controller is constructed. When the parameters of bound functions are not available, the adaptive method is used, and the memoryless decentralized adaptive state feedback controller is developed. By the construction of the proper Lyapunov–Krasovskii functional, the exponential stabilization of the resultant closed-loop system is proved for the both cases. Finally, the theoretic results are applied to the decentralized controller design of networked interconnected chemical reactor systems.

Design of Distributed Fault Tolerant Control Systems