This paper addresses the problem of network modelling and its application in consensus control of Networked Multi Agent Systems (NMASs). These NMASs experience network imperfections such as variable time delays and packet dropouts, where some researchers sought a model that predicts the same behaviour of these imperfections. Earlier studies had two models predicting the behaviour of each network imperfection independently in a scheme called the Two Independent Model Scheme (TIMS). A new approach of modelling the behaviour of the network, based on the Semi-Continuous Hidden Markov Model (SCHMM), is introduced in this paper. This was achieved through introducing a Dirac-delta function alongside the Gaussian distributions in the SCHMM. The new model predicts time delays and packet dropouts, in a homogeneous manner, in a Single Model Scheme (SMS). A Smith Predictor (SP) scheme was implemented for the consensus control of NMASs to mitigate the effects of network limitations. The numerical analysis shows that the new model is more accurate in representing the network limitations, and shows that its performance is better at mitigating the effects of network imperfections in the consensus control problem.

In this paper, the output-based event-triggered predictive control problem for Networked Control Systems (NCSs) is investigated. This problem entails the tackling of bandwidth limitations imposed on the network, time delays and packet dropouts. The bandwidth conservation is normally overlooked in the literature. And thus, a new scheme is developed to tackle this issue. An event triggered mechanism is used to reduce the traffic on the feedback and forward channels. The system states are then estimated from the output received from the feedback channel by means of an observer. A Semi-Continuous Hidden Markov Model (SCHMM) is developed to predict the forward channel’s effective delay and upon that prediction, input commands are computed. Sufficient conditions for stabilization are derived by solving Linear Matrix Inequalities (LMIs) to obtain the gains of the controller and the observer. Finally, a simulation example is given to demonstrate the effectiveness of the proposed method.

This paper addresses the challenges associated with formation control of quadrotors. The collaboration between quadrotors necessitates communication, introducing additional complexities related to the network, specifically time delays and network switching. Although several algorithms have been proposed in prior research to handle these challenges separately, none have tackled both time delays and network switching concurrently. Our objective is to design a control law that handles both time delays and network switching concurrently. Initially, we use a control strategy consisting of three parts: 1) formation controller, 2) reference-angle generator and 3) attitude controller, for the simple case with no network imperfections. Subsequently, we adapt this strategy to accommodate both time delays and network switching, thereby providing a solution to the formation control problem for quadrotors under network imperfections.

This paper studies formation control problem for linear heterogenous multi-agent systems operating in the presence of network imperfections, specifically arbitrary switching and arbitrary time delay. Currently, there exists various control structures for handling this problem. One class of control structure that stands out, is a control law that uses only neighbours’ output information instead of the full state to reduce communication burden. However, existing methods, such as those employing Linear Matrix Inequalities (LMIs), overlook network switching. Another approach involves pole placement for individual agents. However, the proof of stability neglects arbitrary time delays, and the placement of poles is often constrained. The main contribution of this work is to present a novel proof for the stability of heterogeneous systems of linear agents, even in the presence of arbitrary switching and arbitrary time delays, using the concept of positive impulse systems.

This paper demonstrates a software framework and a model based design approach to flexible industrial system architectures. The paper primarily focusses on testing and verification of systems with CANopen network. As an example, the design of passenger elevators is demonstrated. Testing and verification of the system, consisting of simulated components, real components and components available off the shelf, can be performed in an early development phase long before in-situ integration. This approach also helps maintaining safety and integrity of the system while matching development schedules. Simulation is performed with Matlab/Simulink while CANopen communication with real components and/or neighboring networks is realized via stubs written in JAVA. Finally, applications of the new framework are shown which are beyond the sole component and system verification.

The software architecture AUTOSAR has become a standard in the automotive domain in recent years. It supports the development of reusable standardized software components that can be easily assigned to electronic control units (ECUs) at design time. At the end of the development process the AUTOSAR middleware is configured and compiled into a static configuration. However, future automotive systems will be based on components that are spread over more than one vehicle. Examples therefore are car-to-x applications as well as assistance systems for truck and trailer combinations. This kind of systems is characterized by changes on the architectural level at runtime since components may join and leave the network dynamically. Research has shown that Service-oriented computing can be used to introduce runtime adaptation to automotive systems. In order to support such systems in AUTOSAR architectures three different approaches to add runtime adaptation are described and discussed.

Unlike state-of-the-art Driver Assistance Systems(DAS) upcoming technologies may not base on a static software and system architecture. This is especially true for DAS for truck and trailer combinations were the components needed are distributed over both parts of the articulated vehicle. As a truck might be connected to different trailers changes are very common. In order to handle these changes at runtime the usage of Service oriented Architecture (SOA) is a promising approach. Using this principle the functionalities are encapsulated into Services which are Re-Orchestrated whenever the system architecture changes. Since the Services in such a system run on small embedded units and are connected through specialized network systems existing SOA frameworks cannot be used here. This paper introduces SODA, a tailored SOA middleware and development process to design runtime adaptive DAS for truck and trailer combinations using Services.

The increased use and interconnection of electronic components in automobiles has made communication behavior in automotive networks drastically more complex. Both communication designs at application level and complex communication scenarios are often under-specified or out of scope of existing analysis techniques. We extend traditional protocol analyzers in order to capture communication at the level of abstraction that reflects application design and show that the same technique can be used to specify, monitor and test complex scenarios. We present CFR (Channel Filter Rule) models, a novel approach for the specification of analyzers and a domain-specific language that implements this approach. From CFR models, we can fully generate powerful analyzers that extract design intentions, abstract protocol layers and even complex scenarios from low level communication data. We show that three basic concepts (channels, filters and rules) are sufficient to build such powerful analyzers and identify possible areas of application.