A SysML-based methodology for mechatronic systems architectural design

Mechatronic systems are characterized by the synergic interaction between their components from different technological domains. These interactions enable the system to achieve more functionalities than the sum of the functionalities of its components considered independently. Traditional design approaches are no longer adequate and there is a need for new synergic and multidisciplinary design approaches with close cooperation between specialists from different disciplines.SysML is a general purpose multi-view language for systems modeling and is identified as a support to this work.In this paper, a SysML-based methodology is proposed. This methodology consists of two phases: a black box analysis with an external point of view that provides a comprehensive and consistent set requirements, and a white box analysis that progressively leads to the internal architecture and behavior of the system.     

Tool support for the design of self-optimizing mechatronic multi-agent systems

Complex technical systems, such as mechatronic systems, can exploit networking as well as the computational power available today to achieve an automatic improvement of the technical system performance at run-time through self-optimization. To realize this vision, appropriate means for the design of such self-optimizing mechatronic systems are required. Well-established techniques and tools for the modeling of cognitive behavior, reflective behavior, and control behavior exist. However, to really enable self-optimization and its full potential, these different aspects have to be safely integrated in a manner that remains comprehensible to the designer. In this article, we present how this required integration has been realized at the semantic level by extending the unified modeling language (UML), and at the tool level by integrating the CAE tool CAMeL and the CASE tool Fujaba real-time tool suite. The presented Mechatronic UML approach supports the design of verifiable, complex, reconfigurable mechatronic systems using the multi-agent system metaphor. This work was developed in the course of the Special Research Initiative 614—self-optimizing concepts and structures in mechanical engineering—University of Paderborn, and was published on its behalf and funded by the Deutsche Forschungsgemeinschaft. Sven Burmester, Oliver Oberschelp, Florian Klein and Peter Scheideler are members of the respective research group which left after the paper was submitted.     

Perspectives on hierarchical modeling in mechatronic design

Hierarchical modeling helps to describe product models and data from different viewpoints that, representing the different disciplines involved in the design process of mechatronic systems. This paper gives an overview of hierarchical modeling techniques. This includes the investigation of systems, which requires handling different issues that address very specific views of the system (system aspects) and come from various disciplines. Also the model granularity which describes the extent to which an object or model is broken down into smaller elements it an important aspect. The different phases of the product life cycle require models with different objectives and levels of detail. Some models are needed mainly in specific phases of the product life cycle, which are discussed in detail in the paper. Especially in the conceptual design phase some design-characteristic aspects such as hierarchy of parameters, modularity of the design should be analyzed, because in this phase the largest part of the later resulting product costs is predetermined or even fixed. As a consequence, the scope for design is limited to merely small changes in the subsequent design phases. Therefore the interaction between the design phases and the related models plays an important role the development process of mechatronic systems.     

Flexible coordinator design for modeling resource sharing in multi-agent systems

One approach to modeling multi-agent systems (MASs) is to employ a method that defines components which describe the local behavior of individual agents, as well as a special component, called a coordinator. The coordinator component coordinates the resource sharing behavior among the agents. The agent models define a set of local plans, and the combination of local plans and a coordinator defines a system’s global plan. Although earlier work has provided the base functionality needed to synthesize inter-agent resource sharing behavior for a global, conflict-free MAS environment, the lack of coordination flexibility limits the modeling capability at both the local plan level and the global plan level. In this paper, we describe a flexible design method that supports a range of coordinator components. The method defines four levels of coordination and an associated four-step coordinator generation process, which allows for the design of coordinators with increasing capabilities for handling complexity associated with resource coordination. Colored Petri net based simulation is used to analyze various properties that derive from different coordinators and synthesis of a reduced coordinator component is discussed for cases that involve homogeneous agents.     

Applications and environments for multi-agent systems

This paper addresses multi agent system (MAS) environments from an application perspective. It presents a structured view on environment-centric MAS applications. This comprises three base configurations, which MAS applications may apply directly or combine into a composite configuration. For each configuration, the paper presents key issues, requirements and opportunities (e.g. time management issues, real-world augmentation opportunities and state snapshot requirements). Thus, the paper delineates what environment technology may implement to serve MAS applications. Sample applications illustrate the configurations. Next, electronic institutions provide an example of an environment technology, addressing norms and laws in an agent society, already achieving some maturity. In comparison, application-domain specific environment technologies still are in embryonic stages.     

AgentGateway: A communication tool for multi-agent systems

With the rapid growth of multi-agent systems (MAS), there is a pressing need to communicate between different MAS. Various MAS communication standards have been proposed. However, MAS is usually designed to meet special need, thus making it difficult to follow a standard. This paper presents a tool called AgentGateway trying to solve this problem using a simple, effective approach. The tool translates messages from one MAS to intermediate XML-based messages, which then are translated to messages for another MAS. AgentGateway is scalable, meaning that new MAS can easily join it. Furthermore, it provides transparent and reliable communication. A prototype is developed that shows communication between two MAS, namely, Java Agent Template Lite (JATLite) and OAA, can be done using this approach.     

MOBMAS: A methodology for ontology-based multi-agent systems development

Ontologies offer significant benefits to multi-agent systems: interoperability, reusability, support for multi-agent system (MAS) development activities (such as system analysis and agent knowledge modeling) and support for MAS operation (such as agent communication and reasoning). This paper presents an ontology-based methodology, MOBMAS, for the analysis and design of multi-agent systems. MOBMAS is the first methodology that explicitly identifies and implements the various ways in which ontologies can be used in the MAS development process and integrated into the MAS model definitions. In this paper, we present comprehensive documentation and validation of MOBMAS.     

Discrete-event modeling of multi-agent systems with broadcasting-based parallel composition

Multi-agent systems have been widely used in logistics and manufacturing. In this paper we develop an automaton-based modeling framework for a special type of multi-agent systems, where agents are instantiated from a finite number of finite-state automaton templates, and interactions among agents are characterized via cooperative synchronization and broadcasting. To describe the compositional behavior of all agents, we propose a novel broadcasting-based parallel composition rule and show that it is commutative and associative. The effectiveness of this modeling framework and the parallel composition rule is illustrated in a simple multi-agent system.     

A new framework of consensus protocol design for complex multi-agent systems

This paper aims to find a simple but efficient method for consensus protocol design. This paper presents two consensus protocols to solve the consensus problem of complex multi-agent systems that consist of inhomogeneous subsystems. The limitations of current studies are analyzed, and a novel model based on transfer functions is presented. This model can be used to describe both homogeneous and inhomogeneous multi-agent systems in a unified framework. Based on this model, two sufficient and necessary conditions for the consensus of complex multi-agent systems have been obtained. One is for the systems without any external input, and the other is for the systems with the same external input. Then, two corresponding distributed consensus protocols are presented. Considering that the complex multi-agent systems may require different outputs sometimes, the relationship between inputs and outputs is analyzed. Finally, some simulations are given to demonstrate the performance and effectiveness of the proposed approaches.     

A framework for meta-level control in multi-agent systems

Sophisticated agents operating in open environments must make decisions that efficiently trade off the use of their limited resources between dynamic deliberative actions and domain actions. This is the meta-level control problem for agents operating in resource-bounded multi-agent environments. Control activities involve decisions on when to invoke and the amount to effort to put into scheduling and coordination of domain activities. The focus of this paper is how to make effective meta-level control decisions. We show that meta-level control with bounded computational overhead allows complex agents to solve problems more efficiently than current approaches in dynamic open multi-agent environments. The meta-level control approach that we present is based on the decision-theoretic use of an abstract representation of the agent state. This abstraction concisely captures critical information necessary for decision making while bounding the cost of meta-level control and is appropriate for use in automatically learning the meta-level control policies.     

An integrated approach for simulation of mechatronic systems applied to a hexapod robot

Mechatronics is the integration of mechanism, electronics and computer control to produce a functional system. The design process involves application of many engineering areas and various approaches are possible. Computer programs are available in different engineering areas. Engineers define systems and inputs, and user-friendly programs establish mathematical models, solve them and give simulation outputs. In this study, SolidWorks is used for solid modeling and assembly, CosmosMotion is used for rigid body dynamics, CosmosWorks is used for finite element vibration and strength analyses, and Adlink module is used for actuator control. The integration of the design process is achieved with a main program developed in Visual Basic, which uses the application programming interface (API) capabilities. The procedure is applied to a hexapod robot. The robot has been produced to develop and test the procedure. CosmosMotion results are verified by the analytical results obtained from the dynamic equations of the hexapod. Besides known kinematic workspace definition of robots, kinetic and rigidity workspace concepts are introduced. Mechatronic systems can be designed and evaluated easily and effectively by using the design process developed in this work.     

Robust cooperative control for multi-agent systems via distributed output regulation

Robust cooperative control for multi-agent systems is considered in this paper, under the framework of the distributed output regulation problem. With some fundamental assumptions, two necessary and sufficient conditions are given for the distributed output regulation problem to be solvable. The algorithm of designing the robust distributed control law is provided, with the help of internal models. It is shown that this robust controller is effective in a neighborhood of the nominal system, which is tolerant of system uncertainties.     

A structured modeling based methodology to design decision support systems

Many Decision Support Systems (DSS) support the decision making process through the use of mathematical models and data. DSS design involves modeling data as well as mathematical relationships in a domain. The process of model formulation and subsequent integration of model with data in a DSS is a complex and ill-structured process. This paper proposes a methodology based on Structured Modeling (SM), originally introduced by Geoffrion together with the modeling language SML, to model and design the DSS. The methodology includes rigorous and step by step procedures to design and integrate data and modelbases. The main contribution of our approach lies in the integration of research in database design, and mathematical model formulation within the structured modeling framework. The resultant procedures can be easily automated and taught to students in DSS courses. The motivation for our research stemmed from our constant frustrations in teaching DSS courses over the last five years. In the last two years, when we used our methodology, the performance of the students improved significantly. The average score in the DSS project went up to 85 from 60. Our positive experience in using our methodology in classes over the past two years suggests that the methodology imposes structure into the analysis of decision problems, and as a result students produce better DSS designs for classroom cases.     

Broadcast stochastic receding horizon control of multi-agent systems

Optimal regulation of stochastically behaving agents is essential to achieve a robust aggregate behavior in a swarm of agents. How optimally these behaviors are controlled leads to the problem of designing optimal control architectures. In this paper, we propose a novel broadcast stochastic receding horizon control architecture as an optimal strategy for stabilizing a swarm of stochastically behaving agents. The goal is to design, at each time step, an optimal control law in the receding horizon control framework using collective system behavior as the only available feedback information and broadcast it to all agents to achieve the desired system behavior. Using probabilistic tools, a conditional expectation based predictive model is derived to represent the ensemble behavior of a swarm of independently behaving agents with multi-state transitions. A stochastic finite receding horizon control problem is formulated to stabilize the aggregate behavior of agents. Analytical and simulation results are presented for a two-state multi-agent system. Stability of the closed-loop system is guaranteed using the supermartingale theory. Almost sure (with probability 1) convergence of the closed-loop system to the desired target is ensured. Finally, conclusions are presented.     

Revealing bullying patterns in multi-agent systems

Multi-agent systems communication is arguably difficult to be designed. An equal balance of communication among agents is usually desirable. When this does not happen, it affects the quality of service, causing poor performances in terms of response times. The aim of this work is to detect undesirable patterns of communication in these types of systems, using the metaphor of bullying. Though observed in social environments, it can also be applied to a multi-agent system scenario: it consists of some agents’ continuous communications toward the same agents. This causes an unbalanced communication, overloading the receiver, which results in higher response times. Some metrics have been designed to measure the agents’ communication, and some rules classify agents accordingly into several patterns regarding the bullying metaphor. Furthermore, the experimental results prove that the metrics based on the bullying metaphor are strongly related with the quality of service of multi-agent systems. The experimental results also show that the causes of a bad quality of service can be figured out by means of this bullying metaphor and their metrics and classification rules.     

Game theoretical applications for multi-agent systems

We consider game-theoretic principles for design of cooperative and competitive (non-cooperative self-interested) multi-agent systems. Using economic concepts of tâtonnement and economic core, we show that cooperative multi-agent systems should be designed in games with dominant strategies that may lead to social dilemmas. Non-cooperative multi-agent systems, on the other hand, should be designed for games with no clear dominant strategies and high degree of problem complexity. Further, for non-cooperative multi-agent systems, the number of learning agents should be carefully managed so that solutions in the economic core can be obtained. We provide experimental results for the design of cooperative and non-cooperative MAS from telecommunication and manufacturing industries.     

Distributed tracking of a non-minimally rigid formation for multi-agent systems

The objective of this paper is to design distributed control algorithms for a multi-agent system such that a rigid formation can be achieved asymptotically and the agents can finally move with a desired velocity. In particular, it is assumed that the formation is not necessarily minimally rigid, and the desired velocity is available to only a subset of the agents. Estimators are constructed for the agents to estimate the desired velocity, which are further used to design the control inputs of the agents. The proposed control algorithms consist of a formation acquisition term which depends on a potential function and the rigidity matrix, and a velocity estimation term. To deal with non-minimal rigidity, the centre manifold theorem is exploited to prove the stability of the resulting system. Simulation results are also provided to show the effectiveness of the proposed control algorithms.     

A framework for simulating real-time multi-agent systems

In this paper, we describe an implementation of use in demonstrating the effectiveness of architectures for real-time multi-agent systems. The implementation provides a simulation of a simplified RoboCup Search and Rescue environment, with unexpected events, and includes a simulator for both a real-time operating system and a CPU. We present experimental evidence to demonstrate the benefit of the implementation in the context of a particular hybrid architecture for multi-agent systems that allows certain agents to remain fully autonomous, while others are fully controlled by a coordinating agent. In addition, we discuss the value of the implementation for testing any models for the construction of real-time multi-agent systems and include a comparison to related work.

Collective rotating motions of second-order multi-agent systems in three-dimensional space

This paper addresses collective rotating motions of second-order multi-agent systems in three-dimensional space (3D). Two distributed control protocols are proposed and sufficient conditions are derived under which all agents rotate around a common point with a specified formation structure. Simulation results are provided to illustrate the effectiveness of the theoretical results.