Velocity synchronization of multi-agent systems with mismatched parameters via sampled position data

This paper presents a preliminary and tentative formulation of a novel empirical generalization governing the relationship between grammar and cognition across a variety of independent domains. Its point of departure is an abstract distinction between two kinds of cognitive structures: symmetric and asymmetric. While in principle any feature whatsoever has the potential for introducing asymmetry, this paper focuses on one specific feature, namely thematic-role assignment. Our main empirical finding concerns the role of language, or, more specifically, grammar, in effecting and maintaining the distinction between symmetric and asymmetric cognitive structures. Specifically, whereas symmetric structures devoid of thematic-role assignment more commonly occur in a non-grammatical and usually also non-verbal medium, asymmetric structures involving thematic-role assignment are more likely to be associated with a grammatical medium. Our work draws together three independent strands of empirical research associated with three diverse phenomenological domains: compositional semantics, metaphors and schematological hybrids. These three domains instantiate conceptual combinations, bringing together two or more subordinate entities into a single superordinate entity. For compositional semantics this consists of a juxtaposition of constituent signs to form a single more complex sign; for metaphors this entails the bringing together of two different concepts in order to produce a comparison; while for schematological hybrids this involves the combination of different entities to form a single new hybrid entity. Our empirical results reveal a remarkable parallelism between the above three domains. Within each domain, symmetric structures tend to be associated with a non-verbal or otherwise non-grammatical medium, while asymmetric structures are more frequently associated with a grammatical medium. Thus, within each domain, grammar introduces asymmetry. More specifically, we find that in all three domains, the asymmetry in question is one that involves the assignment of thematic roles. To capture this effect, we posit two distinct levels, or tiers, of cognition: non-grammatical cognition, more commonly associated with symmetric structures, and grammatical cognition more conducive to asymmetric structures. Within each of the three phenomenological domains, we find the distinction between non-grammatical and grammatical cognition to be manifest in three independent realms, phylogeny, ontogeny, and the architecture of human cognition. Thus, grammar constitutes the driving force behind the transition from symmetric to asymmetric cognitive structures.

This paper considers the identification problem of network structures for networked dynamical systems. We define the network structure as a coupling function describing the network connectivity and the nonlinear data exchange functions in the network, and attempt to identify the coupling function from potentially noisy measurement data. We develop an identification method of network structures applicable even to network systems consisting of nonlinear systems and nonlinear coupling functions by using the Koopman operator theory. First, we design observable functions as basis functions of a functional space, and determine the Koopman operators associated with the dynamics of the network. Then, the coupling function is identified as a projection on the span of the observables. Also, we make use of the sparse identification techniques to reduce requirements on data amounts and improve robustness with respect to measurement noise. Numerical examples show that the proposed method is applicable to a wide range of nonlinear systems, including chaotic systems with nonlinear coupling functions, and yields better performance than some existing methods. Identification results for two different nonlinear network systems with nonlinear coupling functions show the usefulness of the proposed method.

In this article, we investigate the distributed resilient control problem for a class of cyber-physical systems with communication delays under denial-of-service (DoS) attacks. In contrast to the previous DoS attacks results based on multiagent systems (MASs), a new distributed resilient control approach is proposed for more general heterogeneous linear MASs with nonuniform communication delays. Two types of sampled-based observers are, respectively, proposed. Namely, adaptive distributed observers are designed by introducing a buffer mechanism to eliminate the heterogeneous behavior caused by communication delays while adaptive distributed resilient observers are designed by introducing resilient mechanisms to resist the DoS attacks. Furthermore, a time-varying sampling period sequence is provided to prevent the attacker from identifying the sampling period of the system. Based on the developed resilient observers, a controller is developed. It is proved that the considered problem can be solved by the developed method. Finally, a numerical example is given to illustrate the effectiveness of the obtained result.

Wideband directional couplers are among the microwave components extensively used in electronic warfare, electronic countermeasures, and instrumentation. In this paper, a simple straight line coupling function is used to design a high-pass directional coupler. The ripple performance of a coupler using the linear coupling function is shown to be superior to couplers designed using the cosine type coupling function as reported in (5). In addition, the straight line coupling function is easier to visualize and implement in the design of directional couplers. Other coupling functions such as the Cos type (6) coupling variation provide further reductions in ripple level, but with added mathematical and process complexities.

In evaluating the seismic performance of existing multi-story buildings, strain-based static pushover and time-history nonlinear analyses are traditionally used, as stated in the regulations. In addition, by evaluating the performance levels of symmetrical and asymmetrical structures, it will also be possible to design the mechanism with damping energy capacity that will completely absorb the earthquake energy in case of an inadequate situation in absorbing the earthquake energy. In this study, using real earthquake data, the usability of the energy-based performance analysis approach in the structure was investigated on a 20-story steel structure with rigid connections for symmetric and asymmetric structures. This study was conducted to demonstrate the usability of the energy-based method in evaluating the performance level of buildings under the effect of several earthquakes. In addition, the energy-based method was preferred to determine how much earthquake energy generated in the buildings could be distributed in symmetrical and asymmetrical structures. The selected 11 earthquake data were scaled and the input energies to the structure and the energies distributed by the structure (dissipated hysteretic energy, modal energy, dumping energy, and kinetic energy) were analyzed. Additionally, moment-rotation and axial force-strain behaviors were evaluated for the performance levels of the inspected symmetric and asymmetric structures. At the end of the study, the energy-based concept was confirmed by comparing it with the static pushover analysis results in determining the seismic performances of high-rise structures with very low dynamic mass participation rates. Energy-based analyses have shown that the symmetrical structure absorbs earthquake energies more than the asymmetrical structure and remains at the immediate occupancy (IO) level, as expected. It was concluded that the asymmetric structure remained at a controllable damage (LS) level. Energy-based evaluation has been used as a performance analysis method in the literature. In addition to performance analysis, this study aimed to calculate how much energy is required for the damping mechanism to be added to the structure so that an asymmetric structure behaves like a symmetric structure. This constitutes the original value of the article. So, it has been determined that in order for the asymmetric model to be at the immediate use level, a damper with an energy capacity of 0.062 m2/sec2 is needed, which can absorb earthquake energy from the outside, depending on the building mass.

Notice of Violation of IEEE Publication Principles<br><br>"Agents and Multi-agents Systems and Application to Condition Monitoring" by Christina B. Vilakazi, Tshilidzi Marwala<br>in the Proceedings of the 2007 International Conference on Systems, Man and Cybernetics 2007, pp. 644-649<br><br>After careful and considered review of the content and authorship of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE's Publication Principles.<br><br>This paper contains significant methodology and text from the paper cited below. The content was used with insufficient attribution (including appropriate references to the original author(s) and/or paper title) and without permission.<br><br>"The Design of a Multi-Agent Transformer Condition Monitoring System"<br> by Stephen D.J. McArthur, Scott M. Strachan, and Gordon Jahn<br>in the IEEE Transactions on Power Systems, Vol 19, No 4, November 2004, pp. 1845-1852<br><br> <br/> In recent years the need for improved monitoring systems has necessitated the application of intelligent systems. In this study, a multi-agent system (MAS) is used for vibration condition monitoring. The system consists of functional agents such as feature extraction agent, interpretation agent, diagnosis agent, engineering assistant agent and registry agent. Support Vector Machine (SVM), Multi-layer perceptron (MLP) and Extension Neural Network (ENN) are used as interpretation agent. The rationale behind using multi-agent system for condition monitoring is explained. Experimental results show that multi-agent system is an effective artificial intelligence techniques for condition monitoring.

In this study, a particle swarm optimization (PSO) based Multi-Agent Reinforcement Learning (MARL) approach for load frequency control (LFC) of multi-area power system over communication network considering communication delay and packet loss is presented. A networked control system (NCS) is framed to model a constant delay and packet loss using Markovian approach. The controller using PSO based MARL technique having two levels of controlled action in each area of power system act as an estimator agent and controller agent respectively. The proposed method for frequency regulation of multi-area power system is studied in detail and verified for different types of load disturbances. In addition, to check the system dynamic performance of electric power system a mean square errors (MSEs) of states with different value of communication delay are computed. The simulation results of this study is validated and compared with some pre-design methods available from literatures, along with capacity of multi agent system (MAS) for application of LFC in power system over communication network.

Cluster consensus problem of the multi-agent systems with communication delay is studied in this paper. We consider the multi-agent systems with a special Laplacian matrix as its system matrix. For two types of protocols with time-delay, our work shows that the multi-agent systems with communication delays can reach cluster consensus. Some numerical simulations are given to verify the effectiveness of the theoretical results.

In this dissertation, new algorithms for formation control of multi agent systems (MAS) based on continuum mechanics principles will be suggested. For this purpose, agents of the MAS are considered as particles in a continuum, evolving in R^n, whose desired configuration is required to satisfy an admissible deformation function. Considered is a specific class of mappings that are called homogenous where the Jacobian of the mapping is only a function of time and is not spatially varying. The primary objectives of this dissertation are to develop the necessary theory and its validation on a mobile-agent based swarm test bed that includes two primary tasks: 1) homogenous transformation of MAS and 2) deployment of a random distribution of agents on a desired configuration. Developed will be a framework based on homogenous transformations for the evolution of an MAS in an n-dimensional space (n=1,2, and 3), under1) no inter-agent communication (predefined motion plan), 2) local inter-agent communication, and 3) intelligent perception by agents. In this dissertation, different communication protocols for MAS evolution that are based on certain special features of a homogenous transformation will be developed. It is also aimed to deal with the robustness of tracking of a desired motion by an MAS evolving in R^n. Furthermore, the effect of communication delays in an MAS evolving under consensus algorithms or homogenous maps is investigated. In this regard, the maximum allowable communication delay for MAS evolution is formulated on the basis of eigen-analysis.

The paper presents a novel approximation method for discrete-time Multi-Agent System (MAS)s with communication delay. The applied approximation method was initially developed for a class of infinite-dimensional homogeneous or-dinary linear Volterra difference systems. First, we extend this approximation to non-homogeneous systems. Second, based on this approximation, we have shown that discrete-time MAS with communication delay and small gains is asymptotically equivalent to a MAS without communication delay. We give an algorithm to compute the delay-free MAS model and we have analysed its properties. Simulations are presented to show the applicability of the proposed approximation approach.

Control of time-delay systems represents one important class of control problems. A lot of work has been done in recent years. Much of the research work has been focused on the stability analysis and stabilization of time-delay systems based on the Lyapunov functional and linear matrix inequality (LMI) approaches. While the LMI approach does provide an e±cient tool, the results are mostly only su±cient and only numerical solutions are available. Our research aims to present analytical solutions by some algebraic approaches, which can provide an insightful understanding of control problem of time-delay systems. On the other hand, there has also been significant recent interest in networked multi-agent system (MAS) where unavoidably there exist delays in information acquisition as well as information exchange between agents in addition to possible input/state delays in each agent. This motivates the study of MASs with input and communication delays. The thesis is divided into two parts: Part I is focused on optimal control of single agent systems with multiple input delays; Part II is on distributed consensus control of MAS with communication and input delays. More specifically, in Part I, we shall study the linear quadratic regulation (LQR) and tracking for a single agent with linear dynamics. We first focus on LQR for linear discrete-time systems with multiple delays in a single input channel. By introducing a backward stochastic system, we establish a relationship between the LQR problem for the original system and optimal estimation for a backward stochastic system which can be solved by using projection approach. The explicit optimal controllers are developed for both finite time and infinite time horizon cases. A parallel result for linear continuous-time systems is also established, where the optimal feedback gain is given in terms of the solution of Riccati-type partial differential equations (PDEs).

The promotion of recent self-healing power system research has been directed towards centralized commands and control functions. This paper presents a self-healing power system using multi agent system (MAS) with superconducting fault current limiter. For a complex power system comprised of numerous micro grids, it is potentially unrealistic to expect that centralising total system control function is feasible. Therefore, in this paper particularly interested in making online decision by utilizing smart micro-grid control agents that cooperate during normal and fault situations. Control decision is being taken mutually by agents as these agents exchange circuit information between each other. Day by day increase in power generation capacity of electrical power systems has leads to increase in fault current level which can exceed the maximum designed short-circuit rating of the switch gear. The conventional devices used for the fault current have a responds time delay that can pass initial two to three fault current cycles through it before getting activated. Super Conducting Fault Current Limiter (SFCL) is innovative electric equipment which has the capability to limit fault current within first cycle of the fault current. However, a shortage of research concerning the implementation of SFCL with Multi-agent system in micro grid is felt. The centralized multi-agent system with SFCL explored in this paper help to support an enabling technology of future self-healing power system.

Determinants and performance impact of asymmetric governance structures in international joint ventures: an empirical investigation

This paper addresses the distributed consensus protocol design problem for multi-agent systems with general linear dynamics and directed communication graphs. Existing works usually design consensus protocols using the smallest real part of the nonzero eigenvalues of the Laplacian matrix associated with the communication graph, which however is global information. In this paper, based on only the agent dynamics and the relative states of neighboring agents, a distributed adaptive consensus protocol is designed to achieve leader-follower consensus for any communication graph containing a directed spanning tree with the leader as the root node. The proposed adaptive protocol is independent of any global information of the communication graph and thereby is fully distributed. Extensions to the case with multiple leaders are further studied.

Due to the rising use of renewable energy sources and the use of contemporary power electronic equipment, power system stability has become a major challenge in current power systems. Controlling the power system characteristics can increase the stability of the power system. The traditional techniques for improving power system stability, such as the use of FACTS devices, are costly and may not be effective in handling the dynamic changes of the power system. As a result, by optimizing the power system parameters, an optimization-based multi-agent system can improve the stability of the power system. The Grey Wolf Optimizer based Multi Agent System (GWO-MAS) is proposed in this paper to improve power system stability. The control agents of Distributed Generations (DGs) are optimized using GWO algorithm based on the deviations in frequencies of DGs. Particle Swarm Optimization based Multi Agent System (PSO-MAS) and Conventional Multi Agent System performance are compared with the suggested technique's implementation on IEEE 30 bus system and testing in MATLAB/Simulink environment. The outcomes showed that the suggested approach is successfully improving the stability of an interconnected power system.