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The purpose of this paper is to concern the design of a robust model predictive controller for distributed networked systems with transmission delays.

The overall system is composed of a number of interconnected nonlinear subsystems with time-varying transmission delays. A distributed networked system with transmission delays is modeled as a nonlinear system with a time-varying delay. Time delays appear in distributed systems due to the information transmission in the communication network or transport of material between the sub-plants. In real applications, the states may not be available directly and it could be a challenge to address the control problem in interconnected systems using a centralized architecture because of the constraints on the computational capabilities and the communication bandwidth. The controller design is characterized as an optimization problem of a “worst-case” objective function over an infinite moving horizon.

The aim is to propose control synthesis approach that depends on nonlinearity and time varying delay characteristics. The MPC problem is represented in a time varying delayed state feedback structure. Then the synthesis sufficient condition is provided in the form of a linear matrix inequality (LMI) optimization and is solved online at each time instant. In the rest, an LMI-based decentralized observer-based robust model predictive control strategy is proposed.

The authors develop RMPC strategies for a class of distributed networked systems with transmission delays using LMI-Based technique. To evaluate the applicability of the developed approach, the control design of a networked chemical reactor plant with two sub-plants is studied. The simulation results show the effectiveness of the proposed method.

This paper aims to study that for multi-agent systems, how to find proper control protocols to ensure synchronization when the input set of each agent is not the whole real axis but a discrete set, and how the coarseness of imprecise input sets affect the synchronization control of the multi-agent systems.

The paper uses a relative state feedback method and non-linear mapping functions to design a proper control protocol which matches the coarseness of the input set and ensures synchronization. For theoretical analysis, the paper uses an error analysis method and mathematic induction to prove the effectiveness of the designed control protocol. The paper also uses a numerical example to show the correctness of the theoretical results.

The paper provides a method for protocol design when the input set of each agent is imprecise. The paper establishes a bi-direction relationship which suffices for synchronization between the coarseness of the input set and the synchronization precision, and finds that this relationship describes how the coarseness of the input set affects the synchronization control of the multi-agent system.

This paper only studies the case with logarithmically distributed and uniformly distributed discrete input sets. The authors are encouraged to study the synchronization control of multi-agent systems under input sets with more general distributions.

The paper includes implications for coordination control of multi-agent networks when the actuator of each agent is with a limited capacity, which leads to the case of discrete input sets with limit precision.

This paper fulfils an identified need to study how the coarseness of the input set of each agent affects the synchronization control of the whole multi-agent system.

This paper aims to focus on distributed technologies with the aim of highlighting their economic-organizational dimensions. In particular, the contribution first presents a deeper understanding of the nature and the dynamics of the economies and diseconomies that arise from the adoption and diffusion of distributed technologies. Second, it aims to shed light on the increasing tension between the hierarchy-based model of production and peer-to-peer (p2p) production, which involves the pervasive diffusion of distributed technologies.

Adopting an economic-organizational perspective, which is deeply rooted in the related extant literature, an analytically consistent model is developed to simultaneously take into account the following variables: adoption density independent variable) and economies of knowledge integration and organizational diseconomies (the costs of a loss of control and the costs of organizational decoupling and recoupling) as dependent variables.

Distributed technologies allow access to a large quantity and a wide variety of cognitive slacks that have not been possible until now. In doing so, they are leading the transition towards p2p. This is an emerging production paradigm that is characterized – with respect to mass production – by a shift in the relative importance of cognitive slack in comparison with tangible slack. Nevertheless, the unrestrainable diffusion of distributed technologies is not neutral for organizations. On the one hand, these technologies allow for the integration of economies of knowledge, and on the other hand, they involve organizational diseconomies that should not be ignored by managers and researchers.

This paper fills a gap in the literature by developing a consistent analytical framework that simultaneously takes into account the economies of knowledge integration and potential organizational diseconomies (the costs of coordination and the loss of control) that arise from the adoption and diffusion of distributed technologies.

Discusses the movement away from hierarchical organizational structures towards flatter, heterarchical, structures which is reflected in the growing interest in distributed manufacturing control systems. Traditional hierarchical control systems are limited by the breadth, quantity and timeliness of information needed for their operation. Distributed, heterarchical, control systems overcome these hierarchical limitations but, concurrently, forfeit advantages of the hierarchy including analytically optimal loading patterns and centralized pristine data tracking. Classifies existing research into four categories and documents a progression of heterarchical control approaches to inject some of the advantages of the traditional hierarchy into new heterarchical frameworks. Concludes that neither hierarchical nor heterarchical control structures are ideal in their pure form and, hence, proposes a modified structure, called the quasi‐heterarchical control system, which is a combination of, and a compromise between, pure hierarchy and pure heterarchy.

This paper presents work on design and development of a software platform in terms of virtual distributed control system (DCS) for the design of machine control systems. A component‐based framework has been adopted within the design avenue, due to the fact that machines or mechatronic systems are built from components: objects as in software engineering. Since machine control systems are distributed conformant, the main focus is given on DCS‐based approach. DCS inherits local intelligence to be incorporated at the field level (sensor and actuator level), unlike its centralised counterpart. The developed platform has been validated through a case study. The virtual platform can be useful for many kinds of event driven target platforms such as assembly lines, conveyor‐based material handling systems, production cells, and so on.

Components‐based approach virtual design and validation method computer assisted design.

Specification requirements for virtual design of mechatronic systems.

Prototype tool/approach with a case study example.

Distributed systems usually contain objects with heterogeneous security requirements that pose important challenges for the underlying security mechanisms and especially in access control systems. Access control in distributed systems often relies on centralised security administration. Existing solutions for distributed access control do not provide the flexibility and manageability required. This paper presents the XML‐based secure content distribution (XSCD) infrastructure, which is based on the production of protected software objects that convey contents (software or data) and can be distributed without further security measures because they embed the access control enforcement mechanism. It also provides means for integrating privilege management infrastructures (PMIs). Semantic information is used in the dynamic instantiation and semantic validation of policies. XSCD is scalable, facilitates the administration of the access control system, guarantees the secure distribution of the contents, enables semantic integration and interoperability of heterogeneous sources, provides persistent protection and allows actions (such as payment) to be bound to the access to objects.

The aim of this paper is to enhance the control performance of dexterous hands, enabling them to handle the high data flow from multiple sensors and to meet the deployment requirements of deep learning methods on dexterous hands.

A distributed control architecture was designed, comprising embedded motion control subsystems and a host control subsystem built on ROS. The design of embedded controller state machines and clock synchronization algorithms ensured the stable operation of the entire distributed control system.

Experiments demonstrate that the entire system can operate stably at 1KHz. Additionally, the host can accomplish learning-based estimates of contact position and force.

This distributed architecture provides foundational support for the large-scale application of machine learning algorithms on dexterous hands. Dexterity hands utilizing this architecture can be easily integrated with robotic arms.

Distributed control is an effective method for controlling and suppressing excessive vibrations of continuous systems. Optimal distributed control for a plate problem is solved utilizing a maximum principle after the introduction of a quadratic index of performance in terms of displacement, velocity and a control force as well as an adjoint variable. The problem is reduced to solving a system of partial differential equations for the state variable and the adjoint variable subjected to boundary, initial and terminal conditions. A numerical algorithm is presented to solve the optimal distributed control problem in the space‐time domain which reduces the computational effort required to solve the initial‐terminal‐boundary value problem. Results obtained for a simply supported, rectangular, thin plate are also presented.

Presents numerical algorithms which easily solve both optimal distributed and optimal boundary control problems in a space‐time domain. Analyses two simple cases of continuous systems. These are the vibrating string and the axially vibrating rod. Using finite difference recurrence schemes, gives numerical results which compare the behaviour of the controlled and uncontrolled systems. Compares the results for special cases in which analytical solutions are obtainable are compared with the results using the general numerical schemes.

Cross-layer approach in media access control (MAC) layer will address interference and jamming problems. Hybrid distributed MAC can be used for simultaneous voice, data transmissions in wireless sensor network (WSN) and Internet of Things (IoT) applications. Choosing the correct objective function in Nash equilibrium for game theory will address fairness index and resource allocation to the nodes. Game theory optimization for distributed may increase the network performance. The purpose of this study is to survey the various operations that can be carried out using distributive and adaptive MAC protocol. Hill climbing distributed MAC does not need a central coordination system and location-based transmission with neighbor awareness reduces transmission power.

Distributed MAC in wireless networks is used to address the challenges like network lifetime, reduced energy consumption and for improving delay performance. In this paper, a survey is made on various cooperative communications in MAC protocols, optimization techniques used to improve MAC performance in various applications and mathematical approaches involved in game theory optimization for MAC protocol.

Spatial reuse of channel improved by 3%–29%, and multichannel improves throughput by 8% using distributed MAC protocol. Nash equilibrium is found to perform well, which focuses on energy utility in the network by individual players. Fuzzy logic improves channel selection by 17% and secondary users’ involvement by 8%. Cross-layer approach in MAC layer will address interference and jamming problems. Hybrid distributed MAC can be used for simultaneous voice, data transmissions in WSN and IoT applications. Cross-layer and cooperative communication give energy savings of 27% and reduces hop distance by 4.7%. Choosing the correct objective function in Nash equilibrium for game theory will address fairness index and resource allocation to the nodes.

Other optimization techniques can be applied for WSN to analyze the performance.

Game theory optimization for distributed may increase the network performance. Optimal cuckoo search improves throughput by 90% and reduces delay by 91%. Stochastic approaches detect 80% attacks even in 90% malicious nodes.

Channel allocations in centralized or static manner must be based on traffic demands whether dynamic traffic or fluctuated traffic. Usage of multimedia devices also increased which in turn increased the demand for high throughput. Cochannel interference keep on changing or mitigations occur which can be handled by proper resource allocations. Network survival is by efficient usage of valid patis in the network by avoiding transmission failures and time slots’ effective usage.

Literature survey is carried out to find the methods which give better performance.