Interconnection Topology Research Articles

Distributed Synthesis of Local Controllers for Networked Systems With Arbitrary Interconnection Topologies

We consider the problem of designing distributed controllers to guarantee dissipativity of a networked system comprised of dynamically coupled subsystems. We require that the control synthesis is carried out locally at the subsystem-level, without explicit knowledge of the dynamics of other subsystems in the network. We solve this problem in two steps. First, we provide distributed subsystem-level dissipativity analysis conditions whose feasibility is sufficient to guarantee dissipativity of the networked system. We then use these conditions to synthesize controllers locally at the subsystem-level, using only the knowledge of the dynamics of that subsystem, and limited information about the dissipativity of the subsystems to which it is dynamically coupled. We show that the subsystem-level controllers synthesized in this manner are sufficient to guarantee dissipativity of the networked dynamical system. We also provide an approach to make this synthesis compositional, that is, when a new subsystem is added to an existing network, only the dynamics of the new subsystem, and information about the dissipativity of the subsystems in the existing network to which it is coupled are used to design a controller for the new subsystem, while guaranteeing dissipativity of the networked system including the new subsystem. Finally, we demonstrate the application of this synthesis in enabling plug-and-play operations of generators in a microgrid by extending our results to networked switched systems.

Distributed containment control of multi-agent systems with velocity and acceleration saturations

This paper studies the problem of distributed containment control for multi-agent systems modeled by double integrators. A new class of rotation-free distributed containment controllers with successive saturated loops is proposed for the challenging situation where the velocity and acceleration of each agent are required to stay within their desired ranges. It is proved that the objective of containment control is achievable if the parameters of the controllers satisfy a mild condition. Moreover, the desired ranges of the accelerations and the velocities are allowed to be very small, and the interconnection topology is allowed to be directed and switched.

AUTHOR’S APPROACH TO TOPOLOGICAL MODELING OF PARALLEL COMPUTATION SYSTEMS

The author's research of topologies of parallel computing systems and the tasks solved with them, including the corresponding tools of their modeling, is summarized in the present paper. The original topological model of such systems is presented based on the modified Amdahl law. It allowed formalizing the dependence of the necessary number of processors and the maximal distance between information-adjacent vertices in a graph on the directive values of acceleration or efficiency. The dependences of these values on the system interconnection topology and on the information graph of the parallel task are also formalized. The tools for a comparative evaluation of these dependences, topological criteria and the functions of scaling and fault-tolerant operation of parallel systems are based on the author|s technique of projective description of graphs and the algorithms used in it.

Distributed model predictive control with guaranteed performance for reconfigurable power flow systems based on passivity

AbstractThis paper presents a passivity‐based distributed model predictive control algorithm that can provide minimum performance bound on power flow systems. The dynamics of large‐scale power flow systems can be described by the transportation, conversion, and storage of energy among and across subsystems. By strategically choosing a passive output for each subsystem and augmenting each local model predictive controller with a special passivity constraint, the passivity property of each closed‐loop subsystem can be guaranteed; in addition, the corresponding passivity index can be characterized by the designed parameters of the local controller. The passivity‐preserving coupling between subsystems can be utilized to maintain passivity and the stability properties of the overall system. Moreover, the passivity index of the overall system can be characterized by the transition of passivity indices of subsystems based on interconnection topology. Based on the passivity index, the minimum performance bound of the overall power flow system can be characterized. Even if the structure of the power flow system changes, the entire system can remain stable and achieve a certain performance level. Simulation results of a fluid tank system show the effectiveness of the proposed algorithm.

Distributed Collision-Free Motion Coordination on a Sphere: A Conic Control Barrier Function Approach

This letter studies a distributed collision avoidance control problem for a group of rigid bodies on a sphere. A rigid body network, consisting of multiple rigid bodies constrained to a spherical surface and an interconnection topology, is first formulated. In this formulation, it is shown that motion coordination on a sphere is equivalent to attitude coordination on the 3-dimensional Special Orthogonal group. Then, an angle-based control barrier function that can handle a geodesic distance constraint on a spherical surface is presented. The proposed control barrier function is then extended to a relative motion case and applied to a collision avoidance problem for a rigid body network operating on a sphere. Each rigid body chooses its control input by solving a distributed optimization problem to achieve a nominal distributed motion coordination strategy while satisfying constraints for collision avoidance. The proposed collision-free motion coordination law is validated via simulation.

A Novel Low Cost Interconnection Architecture Based on the Generalized Hypercube

The generalized hypercube (GH) is one key interconnection network with excellent topological properties. It contains many other interconnection topologies, such as the hypercube network, the complete graph, the mesh network, and the $k$ k -ary $n$ n -cube network. It can also be used to construct some data center networks, such as HyperX, BCube, FBFLY, and SWCube. However, the construction cost of GH is high since it contains too many links. In this paper, we propose a novel low cost interconnection architecture called the exchanged generalized hypercube (EGH). We study the properties of EGH, such as the number of edges, the degree of vertices, connectivity, diameter, and diagnosability. Then, we give a routing algorithm to find the shortest path between any two distinct vertices of EGH. Furthermore, we design an algorithm to give disjoint paths between any two distinct vertices of EGH. In addition, we propose two local diagnosis algorithms: LDT $_{EGH}$ E G H and LDWB $_{EGH}$ E G H in EGH under PMC model and MM model, respectively. Simulation results demonstrate that even if the proportion of faulty vertices in EGH is up to 25 percent, the probability that these two diagnosis algorithms can successfully determine the status of vertices is more than 90 percent. As far as the number of edges is concerned, the analysis shows that the construction cost of EGH is much less than that of GH. We could regard this work as the basis for proposing future new high performance topologies.

The 1-good-neighbor diagnosability of unidirectional hypercubes under the PMC model

The hypercubes are a famous class of networks for multiprocessor systems and the unidirectional hypercubes are hypercube interconnection topologies with simplex unidirectional links. Under the classic PMC model, each processor in a multiprocessor system tests a subset of its neighbors. The collection of tests in this system can be modeled by a directed graph. The diagnosability of a system is the maximum number of faulty processors that the system may identify according to the outcomes of the tests, and the g-good-neighbor diagnosability is a more accurate indicator than the diagnosability. In this paper, we first determine the 1-good-neighbor connectivity of unidirectional hypercubes and then determine the diagnosability and 1-good-neighbor diagnosability of hypercube networks when unidirectional hypercubes are used as the collection of tests under the PMC model.

A one-to-many traffic-oriented mm-wave wireless network-in-package interconnection architecture for multichip computing systems

High Performance Computing (HPC) platforms like blade servers consist of multiple processor chips, which may be multicore CPUs, GPUs, memory modules and other subsystems. In such memory and computation intensive systems one-to-many traffic patterns originate from cache coherency, system-level synchronization mechanisms and other control signals. However, small portions of such traffic can introduce huge local and global congestion, which significantly reduce overall performance and cause energy bottleneck unless low latency transmission is ensured by a one-to-many traffic-aware interconnection architecture. Therefore, these high performance and memory intensive multichip systems require efficient support for one-to-may traffic. Traditional metal-based Network-on-Chip (NoC) interconnection architecture is mostly designed for unicast traffic and therefore not suitable for such one-to-many traffic as it provides high-latency, power-hungry multi-hop paths. To address this issue, we propose the design of a one-to-many traffic-aware Wireless Network-in-Package (WiNiP) architecture by integrating a novel asymmetric wireless interconnection topology, a novel hybrid two-state Medium Access Control (MAC) and flow control. The proposed asymmetric topology, MAC and flow control collaborate with each other to form a low latency, one-to-many traffic-aware WiNiP interconnection architecture and increase system bandwidth with lower energy consumption. Through cycle-accurate simulator we show that the proposed topology reduces average packet latency by 47.92 % and outperforms other interconnection architectures for on and off-chip data transfer for synthetic as well as application-specific traffic patterns.

Compositional abstraction of large-scale stochastic systems: A relaxed dissipativity approach

In this paper, we propose a compositional approach for the construction of finite abstractions (a.k.a. finite Markov decision processes (MDPs)) for networks of discrete-time stochastic control subsystems that are not necessarily stabilizable. The proposed approach leverages the interconnection topology and a notion of finite-step stochastic storage functions, that describes joint dissipativity-type properties of subsystems and their abstractions, and establishes a finite-step stochastic simulation function as a relation between the network and its abstraction. To this end, we first develop a new type of compositionality conditions which is less conservative than the existing ones. In particular, using a relaxation via a finite-step stochastic simulation function, it is possible to construct finite abstractions such that stabilizability of each subsystem is not necessarily required. We then propose an approach to construct finite MDPs together with their corresponding finite-step storage functions for general discrete-time stochastic control systems satisfying an incremental passivability property. We also construct finite MDPs for a particular class of nonlinear stochastic control systems. To demonstrate the effectiveness of the proposed results, we first apply our approach to an interconnected system composed of 4 subsystems such that 2 of them are not stabilizable. We then consider a road traffic network in a circular cascade ring composed of 50 cells, and construct compositionally a finite MDP of the network. We employ the constructed finite abstractions as substitutes to compositionally synthesize policies keeping the density of the traffic lower than 20 vehicles per cell. Finally, we apply our proposed technique to a fully interconnected network of 500 nonlinear subsystems and construct their finite MDPs with guaranteed error bounds on the probabilistic distance between their output trajectories.

A Survey on Emerging Issues in Interconnection Networks

Nowadays, the interconnection network is considered as an important architectural choice for the future parallel system in many processors owing to the scalable nature of the interconnection network. The basic idea of interconnection is to reach efficient network communication and overcome scalability problems. Since an interconnection network plays a critical role in such computers, with millions of processors providing an efficient data transferring in the possible shortest time without congestion, designing various topologies for these networks is of high significance. This survey paper focuses on the issues emerged during the design of enhanced interconnected topologies to provide efficient inter-processor communication considering a maximum number of transferred packets in the shortest path.

Planning Framework for Optimal Resource Utilization Strategy in Microgrid

The incorporation of distributed energy resources and technical innovations has restructured the electrical power system network from conventional grid to microgrid. Consequently, significant impacts on both distribution and utilization of power have been observed triggered by diverse operating condition and enhanced power demand. In planning of microgrid, energy management is a critical issue which is related to efficient utilization of available resources at minimum operating cost. Distributed and intermittent nature of generations in microgrid demands efficient and optimal allocation of existing resources. An allocation technique is necessary to attain optimal utilization of assets and to accomplish decision making for optimal power flow route through shortest path. This paper proposes a multi-objective optimization-based resource allocation technique to efficiently control available generation at any load condition to achieve minimum operating cost while maintaining all system constraints. In proposed framework, line flows are maximized to its load-carrying capability and by controlling power flow through shortest possible path. Proposed methodology suggests proper controller position to sustain desired power flow through the shortest path between each generator and load pair. An interconnected microgrid network topology is considered to demonstrate the proposed methodology.

Demand Tracking Control in Manufacturing Systems

The purpose of this research is to design optimal boundary control to solve demand tracking problems for manufacturing systems represented at the factory level in terms of conservation laws coupled with ordinary differential equations. The factory level is modeled as a network with arcs describing specific production policies, e.g., velocity, processing rate, number of machines, and each vertex represents the buffer zone. Different interconnection topologies that correspond to dispersing and merging networks are considered. Numerical solutions are performed using direct and indirect methods.

Compositional Construction of Finite MDPs for Continuous-Time Stochastic Systems: A Dissipativity Approach

Abstract This paper provides a compositional scheme based on dissipativity approaches for constructing finite abstractions of continuous-time continuous-space stochastic control systems. The proposed framework enjoys the structure of the interconnection topology and employs a notion of stochastic storage functions, that describe joint dissipativity-type properties of subsystems and their abstractions. By utilizing those stochastic storage functions, one can establish a relation between continuous-time continuous-space stochastic systems and their finite counterparts while quantifying probabilistic distances between their output trajectories. Consequently, one can employ the finite system as a suitable substitution of the continuous-time one in the controller design process with a guaranteed error bound. In this respect, we first leverage dissipativity-type compositional conditions for the compositional quantification of the distance between the interconnection of continuous-time continuous-space stochastic systems and that of their discrete-time (finite or infinite) abstractions. We then consider a specific class of stochastic affine systems and construct their finite abstractions together with their corresponding stochastic storage functions. We illustrate the effectiveness of the proposed techniques by applying them to a physical case study.

Impedance Network Model of D-PMSG Based Wind Power Generation System Considering Wind Speed Variation for Sub-Synchronous Oscillation Analysis

Recently, sub-synchronous oscillation (SSO) issues were observed in direct-drive permanent magnet synchronous generator (D-PMSG) based wind power generation systems (WPGS) comprising multiple wind farms. Impedance model (IM) analysis has become an important method to study such problems. In this paper, an IM of a D-PMSG grid-connected system (GCS) is established considering the relationship between wind speed and wind turbine output power and the effect of voltage outer loop control. An impedance network model (INM) for a multi-wind-farm grid-connected system (MWFGS) is constructed with IMs of each wind turbine/farm and transmission lines according to the interconnection topology of them. Then, based on the IM of the D-PMSG-GCS, the influence of wind speed on the SSO characteristics is quantitatively analyzed, and the accuracy of the model is verified by comparing with the eigenvalue analysis results. Finally, the influencing factors such as distributed wind speed and network topology of MWFGS on SSO characteristics are quantitatively analyzed based on the INM, and the time-domain simulation verifications are performed in PSCAD/EMTDC. The results prove the effectiveness of INM in analyzing SSO problems of a large-scale WPGS. This is of great significance for the planning of large-scale D-PMSG-based WPGSs and the suppression of SSO.

A consistency-guaranteed approach for Internet of Things software refactoring

The software architecture of Internet of Things defines the component model and interconnection topology of Internet of Things systems. Refactoring is a systematic practice of improving a software structure without altering its external behaviors. When the Internet of Things software is refactored, it is necessary to detect the correctness of Internet of Things software to ensure its security. To this end, this article proposes a novel refactoring correction detection approach to ensure software security. Control flow analysis and data flow analysis are used to detect code changes before and after refactoring, and synchronization dependency analysis is used to detect changes in synchronization dependency. Three detection algorithms are designed to detect refactoring correctness. Four real-world benchmark applications are used to evaluate our approach. The experimental results show that our proposed approach can ensure correctness of Internet of Things software refactoring.

Event-Triggered Resilient Consensus for Multi-Agent Networks Under Deception Attacks

In this paper, a novel distributed algorithm derived from the event-triggered strategy is proposed for achieving resilient consensus of multi-agent networks (MANs) under deception attacks. These malicious deception attacks are intended to interfere with the communication channel causing periods in time at which the sending information among nodes is modified. In particular, we develop an event-triggered update rule which can mitigate the influence of the attackers and at the same time reduce the computing and communication consumption. Each node chooses the instances to update its state information by checking whether its neighbor set meets a given cardinality-dependent function or not. With specified prerequisite on the coupling weights and the sampling period, the consensus achievement of the MANs is independent of the deception attacks, but strictly depends on the robustness of the interconnection topology. Simulation examples are finally given to illustrate the efficacy of the theoretical results.

Structural Controllability of an NDS With LFT Parameterized Subsystems

This paper studies structural controllability for a networked dynamic system (NDS), in which each subsystem may have different dynamics, and unknown parameters may exist both in subsystem dynamics and in subsystem interconnections. In addition, subsystem parameters are parameterized by a linear fractional transformation (LFT). It is proven that controllability keeps to be a generic property for this kind of NDSs. Some necessary and sufficient conditions are then established respectively for them to be structurally controllable, to have a fixed uncontrollable mode, and to have a parameter dependent uncontrollable mode, under the condition that each subsystem interconnection link can take a weight independently. These conditions are scalable, and in their verifications, all arithmetic calculations are performed separately on each subsystem. In addition, these conditions also reveal influences on NDS controllability from subsystem input-output relations, subsystem uncontrollable modes and subsystem interconnection topology. Based on these observations, the problem of selecting the minimal number of subsystem interconnection links is studied under the requirement of constructing a structurally controllable NDS. A heuristic method is derived with some provable approximation bounds and a low computational complexity.

Conceptual Insightful Synthesis of Spatial Compliant Mechanisms Using the Load Flow Formulation

Abstract Conceptual design of spatial compliant mechanisms with distinct input and output ports may be hard because of its complex interconnected topology and is currently accomplished by computationally intensive automated techniques. This paper proposes a user insightful method for generating conceptual compliant topology solutions. The method builds on recent advances where the compliant mechanism deformation is represented as load flow in its constituent members. The nature of load flow enables functional decomposition of compliant mechanisms into maximally decoupled building blocks, namely, a transmitter member and a constraint member. The proposed design methodology seeks to synthesize spatial compliant designs by systematically combining transmitter-constraint members first, identifying kinematically feasible transmitter load paths between input(s) and output(s), and then selecting appropriate constraints that enforce the load path. The paper proposes four design steps to generate feasible solutions and four additional guidelines to optimize load paths and constraint orientations. The method is applied with equal ease to three spatial complaint mechanism examples that belong to single-input single-output, multiple-input single output, and single-input multiple-output mechanisms.

Leader-following Exponential Consensus of Discrete-time Multi-agent Systems with Time-varying Delay and Intermittent Communication

In this paper, the leader-following exponential consensus problem of discrete-time multi-agent systems with time-varying delay is investigated. For systems with interconnected topology being directed and mobile agents being able to communicate with each other at some disjoint time intervals, a new distributed consensus protocol is proposed. By model transforming, it is shown that the consensus problem can be cast into the stability problem for discrete-time multi-agent systems. In light of the multiple Lyapunov stability analysis and the linear matrix inequality method, some new sufficient conditions are derived for guaranteeing the exponential consensus of discrete-time multi-agent systems under fixed topology and switching topology. Moreover, the corresponding gain matrices are also obtained. Finally, simulation results are provided to illustrate the effectiveness of the theoretical results.

Data-sampling controllability of multi-agent systems

Abstract In this paper, we consider data-sampling controllability of multi-agent systems (MASs), where the interconnection topology is directed and weighted and the nodes have generic linear kinetic dynamics. First, the asynchronous data sampling protocols and synchronous data sampling protocols are proposed, respectively. Then the discussions focus on deriving the necessary and sufficient conditions for data-sampling controllability of MASs with a single leader and multiple leaders. The criteria for data-sampling controllability are derived in terms of recursions of matrix multiplication. For the single-leader situation, the asynchronous data-sampling controllability is equivalently transformed to be the output controllability of a discrete linear system. For the multiple-leader situation, the asynchronous data-sampling controllability is equivalently transformed to be the output controllability of a discrete time-delayed linear system. Finally, the synchronous data-sampling controllability is discussed as a special case of asynchronous data-sampling controllability. Two numerical examples are given to illustrate the effectiveness of the theoretical results.