Agent-based Control Architecture Research Articles

Planning the Future of Smart Cities With Swarms of Fully Autonomous Unmanned Aerial Vehicles Using a Novel Framework

The autonomy of unmanned aerial vehicles (UAVs) - self-governing in the aerospace discipline has been a remarkable research area with the development of the advanced bespoke microcontrollers embedded with advanced AI techniques for the last several decades. The road forward about the operational environment is certain about the swarms of fully automated UAVs (FAUAVs), that is, urban areas. FAUAVs with self-learning and self-decision-making abilities by executing non-trivial sequences of events with decimetre-level accuracy based on a set of rules, control loops and constraints using dynamic flight plans and trajectories are taking their indispensable parts within smart cities (SCs). Therefore, their integration with the SC components using real-time data analytics is urgent. This is mainly required to establish a better swarm intelligence along with a safer and optimised harmonious smart ecosystem that enables cooperative FAUAV-SC automation systems with collaborative automated intelligence engaging in the concepts of Internet of Everything (IoE) and Automation of Everything (AoE). Planning the future of cities with swarms of FAUAVs is explored in this paper to optimise the use of FAUAVs with a diverse range of applications and a contemporary methodology is proposed using a holistic framework - FAUAVinSCF equipped with various effective and efficient techniques along with a novel FAUAV routing technique customisable to the constraints of FAUAVs and urban areas. With the methodology, the components of SC and FAUAVs involving recent and impending technological advancements are moulded together to make this inevitable transformation a harmonious part of the inhabitants contributing to the cities' liveability and sustainability. The framework consists of a decentralized agent-based control architecture that monitors and controls the swarms of resource-constraint FAUAVs for their real-time requirements in optimising their urban uses. The outcomes of the methodology suggest that the constraints of FAUAVs can be mitigated significantly in urban areas and consequently, their efficacy can be increased in realising their diverse range of missions.

Comparing Agent-based Control Architectures For Next Generation Telecommunication Network Infrastructures

Multi-agent systems have been an effective choice for designing control systems that are flexible and agile. However, few attention has been given to the evaluation of the architectures of such systems. This becomes critical with the emerging requirements in complex domains such as digital network infrastructures. In this paper, we propose an approach for the evaluation of agent-based control architectures and introduce three multi-agent based architectures for the supervisory control of network service operations of the next generation of digital infrastructures. With the proposed approach, we evaluated the architectures and the implemented control systems prototypes under a realistic network infrastructure environment. Our approach has been effective to evaluate the candidate architectures. The results of communication overhead and reaction time, have shown that agent-based hierarchical and heterarchical-ring architectures have outperformed the heterarchical-complete network architecture.

Using distributed agents to optimize thermal energy storage

Abstract The Intelligent Building Agents Laboratory (IBAL) at the National Institute of Standards and Technology (NIST) will be used to develop and evaluate advanced control systems for commercial building heating, ventilation, and air conditioning (HVAC) applications. Advanced control techniques include model predictive control (MPC) and distributed optimization, both of which can utilize machine learning. This study is a first step in the development of more advanced techniques. MPC is used to generate an optimal schedule for the operation of a cooling plant consisting of ice-on-coil thermal energy storage and two chillers with different maximum capacities. The schedule is generated offline and then used in the IBAL. The performance of the actual system is used to validate the simulation. The simulation is then used to conduct studies relating to the effect of the time horizon and electrical tariff on the optimal schedule. The results demonstrate that an agent-based control architecture is effective in defining optimal control of thermal energy storage systems.

A Hybrid Methodology for Validation of Optimization Solutions Effects on Manufacturing Sustainability with Time Study and Simulation Approach for SMEs

The properties of small- and medium-sized enterprises (SMEs) make them one of the most important categories of enterprises for the economics of challenging world. SMEs, in most countries, are still enterprises with marketing and financial challenges. In addition, most of these challenges are related to their production and product characteristics. On the other hand, SMEs should fulfil the costumer’s demands. In order to reach these goals, SMEs must reach the highest level of production quality and quantity and successfully sustain them. Consequently, various manufacturing paradigms have been offered by an Industry 4.0 concept, which offers a variety of solutions to increase the productivity and enhance the performance of SMEs. It should be noted that implementation of these manufacturing paradigms for SMEs is quite difficult and sometimes risky for several reasons. Still, amidst all these difficulties and challenges, the benefits and idealism of the Industry 4.0 paradigms prevail. From productivity to market, it is difficult to deny that SMEs are frightened by the challenges they face and fleeing from the potential of overcoming them. This paper is an extended version of the research by Ghafoorpoor Yazdi et al. (2018) and conducts a hybrid methodology to satisfy the SMEs by validating and verifying any optimization idea before implementing the Industry 4.0 concept. To reach the study goals, an intelligent Material Handling System (MHS) with agent-based control architecture has been developed. The developed MHS has been utilized for auto parts distribution. The system performance has been evaluated, and some solutions have been provided to optimize the performance of system. To evaluate the target system’s performance, an analytical time study method has been utilized. The time study has an Overall Equipment Effectiveness (OEE) standard approach to identifying the matters that need to be resolved and optimized to increase system performance. The other part of the methodology is generating a simulation model of the real system by use of ARENA® software to evaluate the system’s performance before implementing the optimization idea and modifying the real system. Furthermore, as the sustainability strategies create many synergistic effects for SMEs, after evaluating the effects of the optimization ideas on OEE percentage, the influence of the OEE changes on manufacturing sustainability has been investigated. The results show that optimizing the OEE in SMEs with sustainability approaches can create competitive advantages, rather than simply focusing on reducing unsustainability.

Concept and implementation of an agent-based control architecture for a cyber-physical assembly system

Today’s production companies are challenged with: the assembly of different product variants with lot size of one on a single assembly line and the increase of product variants. The implementation of reconfigurable assembly systems with a modular design is a solution, which allows a flexible adaptation to different product variants. However, handling different assembly modules via specific communication protocols is limited by the current centralized control concepts. Therefore, this paper presents a concept for an agent-based control architecture. This concept uses coherent information starting from the planning process of the assembly system until the system is put into operation allowing a decentralized control. The decentralized agents in each station act as mediators between the modules and the assembly memory database enabling the product autonomous control throughout the assembly system. Moreover, the agent manages the data transfer for the modules with different specific syntaxes via respective communication protocols since a standardized communication protocol does not exist in industry. The concept is verified in a test assembly line for the production of small electronic components.

Multiagent Stochastic Simulation of Minute-to-Minute Grid Operations and Control to Integrate Wind Generation Under AC Power Flow Constraints

The variability and uncertainty inherent to wind generation, which is rapidly increasing, could significantly impact operations efficiency in the future, particularly frequency regulation reserves. This paper addresses these issues from both analytical and curative standpoints through operational impact studies which combine a transmission grid representation with a distributed agent-based control architecture that mimics industry organization charts and follows NERC reliability management rules. As simulating a control area over many years of recorded historical operating conditions is a massive computation problem, the new scheme uses distributed computing with 228 computing nodes to maintain a reasonable simulation time. The simulator-derived automatic generation control and load following generated with a data set characterizing 3000 MW of wind generation integrated in the Quebec interconnection were compared with statistical analysis-based results. The results of the simulation of a full year of minute-by-minute operations suggest that wind integration will increase the number of generating unit start-ups and shut-downs by approximately 5%. The simulator was also able to estimate import/export opportunity losses, as well as several impacts related to voltages and reactive power attributable to increased wind penetration.

Multi-agent Microgrid Power Management

AbstractMicrogrids are a promising means to broadly integrate distributed energy resource (DER) systems. Seen as an enabling technology within smart grid infrastructure, microgrids offer solutions for both customers and system operators of future power networks. However, the optimal management and control of many generation, load, and storage assets local to a microgrid presents as a daunting challenge. In this paper, an agent-based control architecture for microgrids, capable of coordinating and cooperatively achieving multiple user-defined objectives in real-time is presented. Herein, the authors present fundamental properties required by a decentralized microgrid multi-agent system (MAS), define agent capabilities that support resilient operations, and discuss aspects of the microgrid MAS necessary to smoothly transition between system states. The microgrid MAS developed allows control decision-making to be shifted to a lower hierarchical level, capitalizing on the ability of distributed agents to self-order and cooperate towards an optimal power management solution, given assigned goals. As smart grid technologies continue to evolve, the microgrid operational concepts discussed, along with robust power management and control issues, will play an increasingly significant role.

Agent-based interbay system control for a single-loop semiconductor manufacturing fab

This study investigates agent-based interbay control of a wafer fabrication facility with a single-loop track. Doing so will simultaneously resolve the production scheduling and vehicle dispatching problems for an interbay over-hoist-transportation system which is commonly employed in the semiconductor manufacturing industry. Two issues are focused on in this study: (i) To design appropriate agent-based control architecture for an interbay system and (ii) to develop a coordination mechanism for the autonomous agents in the interbay system, so that wafer manufacturing tasks can be accomplished efficiently. In this study, we construct a distributed interbay system architecture, in which wafer cassettes, vehicles, and manufacturing cells with stockers are modelled as independent and autonomous agents. This study develops an agent coordination mechanism that is based on a vehicle-initiated contract net protocol. Three types of bidding strategies are proposed and empirically examined via simulation. The performances of the proposed agent-based control mechanism, in terms of cassette sojourn time and throughput, are observed and our experiments have shown promising results.

Agile manufacturing system control based on cell re-configuration

The control of an agile manufacturing system (AMS) is expected to be flexible, open, scalable and re-configurable so as to tackle the more complex and uncertain information flows. To meet these requirements, we propose agent-based control architecture for AMS, under which the functions of task planning, scheduling and dynamic control are integrated seamlessly. First of all, this paper introduces the concept of RMC (re-configurable manufacturing cell), based on which, we construct the control architecture for AMS in compliance with multi-agent system (MAS). The whole control process under the architecture comprises two hierarchies, i.e. the upper one for order planning and RMC forming and the lower one for task scheduling within each RMC. For the upper hierarchy, we establish a linear integer programming (LIP)-based mathematical model and a MAS-based dynamic process model, and present a two-step approach to order planning and RMC forming. For the lower hierarchy, we develop the scheduling model, a method based on the bidding mechanism from contract net, and describe the rescheduling mechanism in the control system. To illustrate the methodology proposed in the paper, a simulation study is thoroughly discussed. Our studies demonstrate that the RMC-based control architecture provides an AMS with an optimal, dynamic and flexible mechanism of responding to an unpredictable manufacturing environment, which is crucial to achieve agility for the whole manufacturing system.

A DES-supported agent-based control architecture for flexible manufacturing systems

The paper presents a methodology for the synthesis of a supervisor based on a Petri Net model. This supervisor is used for the real-time control of a Flexible Manufacturing System by a two layer agent-based architecture. The structure and functioning of the architecture as well as the FMS modeling approach are also described in the paper. The synthesis methodology was implemented into a software application, which was used on a case study.

MANPro: mobile agent-based negotiation process for distributed intelligent manufacturing

This paper examines negotiation procedures in an agent-based distributed shop floor control system (SFCS). A distributed SFCS is under a heterogeneous environment, which is controlled through negotiations between autonomous agents. The negotiation-based control can be considered as the core of a distributed control paradigm. An efficient information exchanging mechanism and an information model with reasonable structure are indispensable for effective negotiations. This paper proposes a novel negotiation mechanism, called a mobile agent-based negotiation process (MANPro), which applies a mobile agent system to the process of information exchange. Since using mobile agents allows each component to execute asynchronously and autonomously and to adapt dynamically to the execution environment, MANPro may guarantee autonomy of agents. Moreover, it is possible to build a fully distributed and autonomous SFCS by using MANPro. MANPro is based on the agent-based control architecture, which includes a communication architecture and an information architecture. The communication architecture provides the exchanging mechanism of information, defining functional modules to support the mechanism while the information architecture provides the framework for information modelling on negotiation, proposing information models required for introducing the ontology concept.