1,721,119 research outputs found
A soft computing approach for task contracting in multi-agent manufacturing control
This paper describes a new task-contracting schema for multi-agent manufacturing control based on soft computing. It aims to apply fuzzy techniques to implement a real-time multi-criteria task-contracting mechanism for part flow control in manufacturing floor. For comparison purposes, the paper also considers other recently proposed evolutionary strategies to adapt and optimize agents' decision parameters to the changing conditions of the manufacturing floor. All the considered approaches are compared on a detailed simulation model of a hypothetical manufacturing system that was recently proposed in literature as benchmark for multi-agent control systems
A genetic approach for adaptive multiagent control in heterarchical manufacturing systems
In this paper, we apply genetic algorithms to adapt the decision strategies of autonomous controllers in a part-driven heterarchical manufacturing system. The control agents use pre-assigned decision rules only for a limited amount of time, and obey a rule replacement policy propagating the most successful rules to the subsequent populations of concurrently operating agents. The twofold objective of this approach is to automatically optimize the performance of the control system during the steady-state unperturbed conditions of the manufacturing floor, and to improve the reactions of the agents to unforeseen disturbances (e.g., failures, shortages of materials) by adapting their decision strategies. Results on a detailed discrete event model of a multiagent heterarchical manufacturing system confirm the effectiveness of the approach
New control policies preventing deadlock in automated manufacturing systems
In this paper we propose a hybrid approach to prevent deadlock between parts flowing in manufacturing systems. The approach uses both Petri nets and digraphs to exploit the higher simplicity of digraphs to detect deadlock combined with theoretic results known for Petri nets. The new PN-based prevention policies translate the information obtained from properly defined digraphs into empty siphons of a corresponding PN modeling the same system
An improved projection algorithm for direct adaptive fuzzy control
An effective variant of the projection algorithm frequently used in adaptive fuzzy control is presented. The proposed algorithm preserves the formal guarantees that the adapted parameters and some related system variables remain within the prescribed bounds, and improves the speed of convergence of the adaptation. The effectiveness of our approach is shown both in simulation and experimental case studies
A discrete-event system model for multi-agent control of automated manufacturing systems
In the area of multi-agent systems, many efforts have been recently devoted to find appropriate tools to model, and specify in a formal way the dynamics and the mechanisms of interaction of the various autonomous agents. In this paper, an approach based on the discrete event system specification technique is used. Typical agents used in manufacturing control systems can be viewed as discrete event systems, and analyzed with the proposed modeling tool. The models lend themselves both for developing a simulation platform, and for realizing the control software of the actual plant
Multi-agent fuzzy control of operation dispatching in flexible manufacturing environments
This paper describes a negotiation algorithm for task contracting in multi-agent manufacturing systems based on fuzzy techniques. In the proposed approach, operations on raw parts are executed on the workstation with a processing priority resulting from a negotiation between the agents controlling the machine and the parts flowing in the systems. Pricing and decision criteria encompass a set of variables taking into account different aspects of the available alternatives, as processing and setup times, workload in queues, buffer saturation or starvation. The proposed approach is compared with analogous strategies derived from literature on a simulation model of a hypothetical manufacturing system that was recently proposed as benchmark for multi-agent control systems
Recent developments in the application of computational intelligence to multi-agent manufacturing control
This paper surveys some recent approaches using Computational Intelligence (namely Fuzzy Logic and Evolutionary Algorithms) for manufacturing system control. In particular, the paper focuses on approaches oriented toward the Multi-Agent System design paradigms. Furthermore, this paper summarizes the results of a simulation comparison between-two fuzzy multi-agent architectures for job flow control, differing for the degree of interactions between agents, on a detailed case study that was recently proposed in literature to benchmark distributed multi-agent control approaches
Fuzzy multi-criteria algorithm for dynamic routing in FMS
Deals with real-time part routing in flexible manufacturing systems. At each production step, each part can autonomously choose its next server according to a fuzzy multiple criteria evaluation of each available destination. The influence of each criterion is graded to improve the effects of part decisions. A simulation study confirms the effectiveness of the approach
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