STABILITY ANALYSIS AND COOPERATIVE CONTROL OF DISTRIBUTED MULTI-AGENT SYSTEM WITH SAMPLED COMMUNICATION

The cooperative control and stability analysis problems for the multi-agent system with sampled com- munication are investigated. Distributed state feedback controllers are adopted for the cooperation of networked agents. A theorem in the form of linear matrix inequalities（LMI） is derived to analyze the system stability. An- other theorem in the form of optimization problem subject to LMI constraints is proposed to design the controller, and then the algorithm is presented. The simulation results verify the validity and the effectiveness of the pro- posed approach.

Extend OWL: toward a clustering integration of collaborative ontologies and agents

In order to solve the problem of how to collaborate with foreign agents and ontologies, a restricted clustering integration approach is proposed. It differs from the traditional approaches in which web ontology language （OWL） is extended by adding some new collaborative interfaces （ i. e., agent-link and ontology-link） to it instead of owl： import. Syntaxes of the interface for foreign ontologies and foreign agents, respectively, and a meta-method of clustering integrated collaboration are discussed. The approach focuses on taking advantage of OWL itself to solve the collaborative problems, and it is feasible to track the contexts of newadded knowledge concerning ontological collaboration.

Completeness of bounded model checking temporal logic of knowledge

In order to find the completeness threshold which offers a practical method of making bounded model checking complete, the over-approximation for the complete threshold is presented. First, a linear logic of knowledge is introduced into the past tense operator, and then a new temporal epistemic logic LTLKP is obtained, so that LTLKP can naturally and precisely describe the system＇s reliability. Secondly, a set of prior algorithms are designed to calculate the maximal reachable depth and the length of the longest of loop free paths in the structure based on the graph structure theory. Finally, some theorems are proposed to show how to approximate the complete threshold with the diameter and recurrence diameter. The proposed work resolves the completeness threshold problem so that the completeness of bounded model checking can be guaranteed.

Approach for knowledge sharing based on ontology context immigration

In order to better achieve knowledge sharing based on distributed ontologies, an approach based on ontology context immigration （OCI）is proposed. Compared with traditional approaches such as ontology integration and mapping, the proposed approach can reduce the implementation complexity. This approach can be mainly divided into three phases： ontology context determination for a given term, ontology semantic similarity computation between ontology terms, and ontology context immigration. As for a local semantic term based on distributed ontologies, an appropriate ontology context of the term is determined and extracted from a local ontology most associated with the term by using semantic similarity computation. Then, the ontology context is dynamically immigrated to the source ontology for enriching semantic information related to the term. A system called distributed knowledge sharing system（DKSS） is developed to illustrate this approach. The system adopts multi-agent technology for better communication and coordination between different ontology information sources. The experimental results show that it is efficient for distributed ontology knowledge sharing. The proposed approach does not require the support of a global ontology or the maintenance of complex ontology mapping relations, and thus it has better maintainability and scalability.

A distributed algorithm for signal coordination of multiple agents with embedded platoon dispersion model

In order to reduce average arterial vehicle delay, a novel distributed and coordinated traffic control algorithm is developed using the multiple agent system and the reinforce learning （RL）. The RL is used to minimize average delay of arterial vehicles by training the interaction ability between agents and exterior environments. The Robertson platoon dispersion model is embedded in the RL algorithm to precisely predict platoon movements on arteries and then the reward function is developed based on the dispersion model and delay equations cited by HCM2000. The performance of the algorithm is evaluated in a Matlab environment and comparisons between the algorithm and the conventional coordination algorithm are conducted in three different traffic load scenarios. Results show that the proposed algorithm outperforms the conventional algorithm in all the scenarios. Moreover, with the increase in saturation degree, the performance is improved more significantly. The results verify the feasibility and efficiency of the established algorithm.

Integrated Monitor System of Water and Fertilizer of Greenhouse Intelligent Irrigatio

The integration of water and fertilizer is a comprehensive technology combined irrigation and fertilizer, which has outstanding advantages of saving fertilizer, saving water, saving labor, protecting environment, high yield and high efficiency. Currently, most of the water and fertilizer integrated irrigation and fertilization and irrigation operation in the production-based greenhouse is achieved relying on artificial experience, which is hard to achieve timely, scientific and intelligent irrigation. In this study, the application of STM32 embedded system realized the real-time collection of the data from the humidity sensors buried in top, middle and low depth of soil, and water and fertilizer integrated irrigation work was completed in the greenhouse through automatic control according to the predetermined fertilization and irrigation strategies for different crops. Moreover, the system had remote monitoring function, which used the global system for mobile （GSM） module to provide users with remote short message services, and therefore, the users could not only achieve the remote intelligent monitoring on the irrigation, light, ventilation of the greenhouse through short messages, but also could start and stop the remote control system operation, so as to realize the automatic management of the greenhouse environment, achieving the purpose of remote fertilization and water-saving irrigation.

A Blackboard-Based Multi-Agent Cooperative Expert System Tool

Aim To design and implement a multi-agent cooperative problem solving expert system tool. Methods A blackboard system was adopted in the system as a data sharing and information exchanging center, to coordinate the complex cooperative problem solving. The system was developed in UNIX and MSWindows 95 mixed TCP/IP network environment. Results and Conclusion A prototype system of a multi-agent cooperative expert systems tool is implemented.The experiment demonstrates that the fundamental functions of a cooperative expert systems is realized.

Necessary and Sufficient Conditions for Consensus in Third Order Multi-Agent Systems

We deal with a consensus control problem for a group of third order agents which are networked by digraphs.Assuming that the control input of each agent is constructed based on weighted difference between its states and those of its neighbor agents, we aim to propose an algorithm on computing the weighting coefficients in the control input. The problem is reduced to designing Hurwitz polynomials with real or complex coefficients. We show that by using Hurwitz polynomials with complex coefficients, a necessary and sufficient condition can be obtained for designing the consensus algorithm. Since the condition is both necessary and sufficient, we provide a kind of parametrization for all the weighting coefficients achieving consensus. Moreover, the condition is a natural extension to second order consensus, and is reasonable and practical due to its comparatively decreased computation burden. The result is also extended to the case where communication delay exists in the control input.

Multi-agent Coordinated Control and Collision Avoidance with Unknown Disturbances

The formation problem of multi-agent systems via coordinated control is investigated,where the multiple agents can achieve the common velocity with leader and avoid collision during the evolution.In the real-world situation,the communication is often disturbed and inaccurate.Hence,the unknown disturbances are considered in the velocity measurements,which is assumed to be bounded and does not need to be modelled.Moreover,a complicated nonlinear interaction among agents is presented in the design of control.Based on the existing work of multi-agent systems,a flocking control protocol is proposed to address the formation problem in the dynamic topology.The stability analysis is given to prove that the velocities of all agents can converge to the velocity of leader and the stable motion with collision avoidance can be achieved eventually.Finally,some simulations are presented to verify the effectiveness of the proposed algorithm.

Consensus control for multi-agents in a non-rectangular bounded space: algorithmand experiments

Aiming for the coordinated motion and cooperative control of multi-agents in a non-rectangular bounded space, a velocity consensus algorithm for the agents with double- integrator dynamics is presented. The traditional consensus algorithm for bounded space is only applicable to rectangular bouncing boundaries, not suitable for non-rectangular space. In order to extend the previous consensus algorithm to the non- rectangular space, the concept of mirrored velocity is introduced, which can convert the discontinuous real velocity to continuous mirrored velocity, and expand a bounded space into an infinite space. Using the consensus algorithm, it is found that the mirrored velocities of multi-agents asymptotically converge to the same values. Because each mirrored velocity points to a unique velocity in real space, it can be concluded that the real velocities of multi-agents also asymptotically converge. Finally, the effectiveness of the proposed consensus algorithm is examined by theoretical proof and numerical simulations. Moreover, an experiment is performed with the algorithm in a real multi-robot system successfully.

An enhanced artificial bee colony optimizer and its application to multi-level threshold image segmentation

A modified artificial bee colony optimizer(MABC)is proposed for image segmentation by using a pool of optimal foraging strategies to balance the exploration and exploitation tradeoff.The main idea of MABC is to enrichartificial bee foraging behaviors by combining local search and comprehensive learning using multi-dimensional PSO-based equation.With comprehensive learning,the bees incorporate the information of global best solution into the solution search equation to improve the exploration while the local search enables the bees deeply exploit around the promising area,which provides a proper balance between exploration and exploitation.The experimental results on comparing the MABC to several successful EA and SI algorithms on a set of benchmarks demonstrated the effectiveness of the proposed algorithm.Furthermore,we applied the MABC algorithm to image segmentation problem.Experimental results verify the effectiveness of the proposed algorithm.

Three-dimensional multi-constraint route planning of unmanned aerial vehicle low-altitude penetration based on coevolutionary multi-agent genetic algorithm

To address the issue of premature convergence and slow convergence rate in three-dimensional (3D) route planning of unmanned aerial vehicle (UAV) low-altitude penetration,a novel route planning method was proposed.First and foremost,a coevolutionary multi-agent genetic algorithm (CE-MAGA) was formed by introducing coevolutionary mechanism to multi-agent genetic algorithm (MAGA),an efficient global optimization algorithm.A dynamic route representation form was also adopted to improve the flight route accuracy.Moreover,an efficient constraint handling method was used to simplify the treatment of multi-constraint and reduce the time-cost of planning computation.Simulation and corresponding analysis show that the planning results of CE-MAGA have better performance on terrain following,terrain avoidance,threat avoidance (TF/TA2) and lower route costs than other existing algorithms.In addition,feasible flight routes can be acquired within 2 s,and the convergence rate of the whole evolutionary process is very fast.

Decentralized Multiagent Task Planning for Heterogeneous UAV Swarm

A decentralized task planning algorithm is proposed for heterogeneous unmanned aerial vehicle(UAV)swarm with different capabilities.The algorithm extends the consensus-based bundle algorithm(CBBA)to account for a more realistic and complex environment.The extension of the algorithm includes handling multi-agent task that requires multiple UAVs collaboratively completed in coordination,and consideration of avoiding obstacles in task scenarios.We propose a new consensus algorithm to solve the multi-agent task allocation problem and use the Dubins algorithm to design feasible paths for UAVs to avoid obstacles and consider motion constraints.Experimental results show that the CBBA extension algorithm can converge to a conflict-free and feasible solution for multi-agent task planning problems.

Enabling Technology of Multiagent Manufacturing System:A Novel Mode of Self-organizing IoT Manufacturing

As the manufacturing mode focuses more on network and community,the orders and production processes are becoming highly dynamic and unpredictable.The traditional manufacturing system cannot handle those exceptional events such as rush orders and machine breakdowns.Nevertheless,the multiagent manufacturing system(MAMS)becomes a critical pattern to deal with these disturbances in a real-time way.However,due to the lack of universality,MAMS is difficult to be applied to industrial sites.A new multiagent architecture and the relay cooperation model based on a positive process relation matrix are proposed to address this paper’s issue.An optimized contract net protocol(CNP)-based negotiation mechanism is developed to improve the efficiency of collaboration in the proposed architecture.Finally,a case study of self-organizing internet of things(Io T)manufacturing system is used to test the feasibility and effectiveness of the method.It is shown that the proposed self-organizing Io T manufacturing mode outperforms the traditional manufacturing system in terms of makespan and critical machine workload balancing under disturbances through comparison.

Application of Multi-agent Models to Urban Expansion in Medium and Small Cities: A Case Study in Fuyang City,Zhejiang Province,China

In this study, three-phase satellite images were used to define rules for the allocation of time and space in construction land resources based on a complex adaptive system and game theory. The decision behavior and rules of government agent, enterprise agent and resident agent in construction land growth were explored. A distinctive and dynamic simulation model of construction land growth was built, which integrated multi-agent, GIS technology and RS data and described the interaction among influencing agents, Taking Fuyang City in the Changjiang River Delta as an example, an assessment process for the remote sensing data in construction land and scenario planning was constructed. Repast and ArcGIS were used as simulation platforms. A simulation of the spatial pattern in land-use planning and the setting of scenario planning were conducted by using the incomplete active game, which was based on different natural, social and economic levels. Through this model, a simulation of urban planning space and decision-making for Fuyang City was created. Relevant non-structured problems arising from urban planning management could be identified, and the process and logic of urban planning spatial decision-making could thus be improved. Cell-by-cell comparison showed that the simulation accuracy was over 72%. This model has great potential for use by government and town planners in decision support and technique support in the policy-making process.

Multi-agent System Optimized Reconfiguration of Shipboard Power System

Reconfigurability of the electrical network in a shipboard power system （SPS） after its failure is central to the restoration of power supply and improves survivability of an SPS. The navigational process creates a sequence of different operating conditions. The priority of some loads differs in changing operating conditions. After analyzing characteristics of typical SPS, a model was developed used a grade III switchboard and an environmental prioritizing agent （EPA） algorithm. This algorithm was chosen as it is logically and physically decentralized as well as multi-agent oriented. The EPA algorithm was used to decide on the dynamic load priority, then it selected the means to best meet the maximum power supply load. The simulation results showed that higher priority loads were the first to be restored. The system satisfied all necessary constraints, demonstrating the effectiveness and validity of the proposed method.

Railway intelligent transportation system and its applications

With the development of artificial intelligence, communication, computer and other related technologies, it becomes feasible to rebuild traditional railway with such advanced technologies in order to establish a new generation railway transport system. The railway intelligent transportation system is the trend of railway transportation system in China, and it is also the research focus of international railway transport industry. This paper presents the definition, characters, architecture, key technologies and developing pattern of the RITS(railway intelligent transportation system). Then three typical applications are introduced. Finally, the prospect of the RITS is summarized.

Analysis of Do D inkjet printhead performance for printable electronics fabrication using dynamic lumped element modeling and swarm intelligence based optimal prediction

The major challenge in printable electronics fabrication is to effectively and accurately control a drop-on-demand(Do D) inkjet printhead for high printing quality. In this work, an optimal prediction model, constructed with the lumped element modeling(LEM) and the artificial bee colony(ABC) algorithm, was proposed to efficiently predict the combination of waveform parameters for obtaining the desired droplet properties. For acquiring higher simulation accuracy, a modified dynamic lumped element model(DLEM) was proposed with time-varying equivalent circuits, which can characterize the nonlinear behaviors of piezoelectric printhead. The proposed method was then applied to investigate the influences of various waveform parameters on droplet volume and velocity of nano-silver ink, and to predict the printing quality using nano-silver ink. Experimental results show that, compared with two-dimension manual search, the proposed optimal prediction model perform efficiently and accurately in searching the appropriate combination of waveform parameters for printable electronics fabrication.

Trajectory tracking and formation control based on consensus in high-dimensional multi-agent systems

This paper discusses consensus problems for high-dimensional networked multi-agent systems with fixed topology. The communication topology of multi-agent systems is represented by a digraph. A new consensus protocol is proposed, and consensus convergence of multigent systems is analyzed based on the Lyapunov stability theory. The consensus problem can be formulated into solving a feasible problem with bilinear matrix inequality （BMI） constrains. Furthermore, the consensus protocol is extended to achieving tracking and formation control. By introducing the formation structure set, each agent can gain its individual desired trajectory. Finally, numerical simulations are provided to show the effectiveness of our strategies. The results show that agents from arbitrary initial states can asymptotically reach a consensus. In addition, agents with high-dimensional can track any target trajectory, and maintain desired formation during movement by selecting appropriate structure set.