• 한국통신학회논문지
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• 제18권5호
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• pp.695-707
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• 1993

Marked Petri Net(MPN) 모델은 최대 병행 활성화 랑데부 수에 따른 통신 복잡도를 분석할 수 있게 해준다. 그러나 이 모델은 시간과 확률 속성(Time and Probability characteristics)을 명시할 수 없음으로 통신 복잡도의 새로운 개념인 실행 시간 복잡도를 분석할 수 없다. 본 논문에서는 이러한 실행 시간 복잡도를 효율적으로 분석하기 위해 MPN에 새로운 제약 조건인 net 절감 법칙, 실행 시간, 그리고 확률 조건을 도입한 Ada Tasking Structure Nets(ATSN)을 제안한다. 끝으로 ATSN 모델을 이용하여 통신 복잡도의 분석 효과를 보인다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2001년도 합동 추계학술대회 논문집 정보 및 제어부문
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• pp.212-214
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• 2001

Siphons and traps are special structures of Petri nets with closely related to liveness for the deadlock analysis of Discrete Event Dynamic Systems. It can analysis the liveness of Petri nets using the siphon and trap without to check reachability.[1] Deadlock analysis approach we proposed is based on the notion of potential deadlock which are siphons that eventually become empty. And in this paper, we proposed a initial marking method by siphon to avoid and to prevent deadlock. It is shown that our approach is more efficient than classical state enumeration approach.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 하계학술대회 논문집 C
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• pp.1136-1138
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• 1999

This paper describes a new method of the modeling of protection system and fault diagnosis in power systems using Petri nets. The Petri net models of protection system are compose of the operating process of protective devices and the fault diagnosis process. Fault diagnosis model which makes use of the nature of Petri net is developed to overcome the drawbacks of methods that depend on operator knowledge. The proposed method can reduce processing time and increase accuracy when compared with the traditional methods. And also this method covers online processing of real-time data from SCADA.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1993년도 정기총회 및 추계학술대회 논문집 학회본부
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• pp.314-316
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• 1993

In this paper, a method to detect and diagnose faults in Automated Manufacturing Systems(AMS) is proposed. In AMS, it is necessary to monitor the process-status. The detection and diagnosis of faults are often difficult in monitoring level with given passive data. We propose the model-based monitoring system for faults detection and diagnosis using Petri Nets to model AMS efficiently and easily. Simulation results show the validity of proposed method with example of Reverse Mill Process in Automated Mill Lines.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.137.5-137
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• 2001

This paper proposes a method that combines diverse evidence relevant to the reliability to evaluate the reliability of complicated systems such as robots. In practice, reliability experts combine diverse evidences relevant to the reliability and infer the answers by using their own way that are mostly informal. The proposed method also combines diverse evidence and performs inferences but informal and quantitative way by using the benefits of Bayesian Belief Nets (BBN). Diverse evidences could be those from dassical analysis techniques, test results, quality assurance about the process of manufacturing, and the quality of the company or development team, etc. Some of these evidences are qualitative and others are quantitative. Both are ...

• 대한기계학회논문집A
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• 제21권5호
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• pp.769-779
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• 1997

This paper presents an approach to multiple objective scheduling of flexible manufacturing systems(FMS). The approach is an extension of the scheduling method that formulates scheduling problems using Petrinets, and applies heuristic search to find optimal or near-optimal schedules with a single objective. New evaluation functions are developed to optimize simultaneously the makespan and the total operating cost. A scheduling example is used to demonstrate the effectiveness of the proposed approach.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2001년도 춘계학술대회 논문집(한국공작기계학회)
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• pp.255-260
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• 2001

This paper presents a new approach to the design of neural control system using digital signal processors in order to improve the precision and robustness. Robotic manipulators have become increasingly important in the field of flexible automation. High speed and high-precision trajectory tracking are indispensable capabilities for their versatile application. The need to meet demanding control requirement in increasingly complex dynamical control systems under significant uncertainties, leads toward design of intelligent manipulation robots. The TMS320C31 is used in implementing real time neural control to provide an enhanced motion control for robotic manipulators. In this control scheme, the networks introduced are neural nets with dynamic neurons, whose dynamics are distributed over all the network nodes. The nets are trained by the distributed dynamic back propagation algorithm. The proposed neural network control scheme is simple in structure, fast in computation, and suitable for implementation of real-time control. Performance of the neural controller is illustrated by simulation and experimental results for a SCARA robot.

• Asia pacific journal of information systems
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• 제6권1호
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• pp.223-240
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• 1996

The paper proposes an approach, called OPNets, for modeling and validating manufacturing systems that is based on object-oriented high-level Petri nets. In OPNets, modeling components of Petri net are constructed into hierarchical objects that communicate with each other by passing messages. To enhance the reusability and maintainability, OPNets organizes a system into hierarchical objects that inherit attributes and behavioral properties from the object of super class and object-interaction relations are separated from the internal structure of object. The modeling scheme of OPNets tries to resolve the complexity problems of Petri net. To illustrate the modeling schemes of OPNets, a storage/retrieval example has been proposed.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 1999년도 추계학술대회 논문집 - 한국공작기계학회
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• pp.113-118
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• 1999

This paper presents a new approach to the design of neural control system using digital signal processors in order to improve the precision and robustness. Robotic manipulators have become increasingly important n the field of flexible automation. High speed and high-precision trajectory tracking are indispensable capabilities for their versatile application. The need to meet demanding control requirement in increasingly complex dynamical control systems under significant uncertainties, leads toward design of intelligent manipulation robots. The TMS320C31 is used in implementing real time neural control to provide an enhanced motion control for robotic manipulators. In this control scheme, the networks introduced are neural nets with dynamic neurons, whose dynamics are distributed over all the network nodes. The nets are trained by the distributed dynamic back propagation algorithm. The proposed neural network control scheme is simple in structure, fast in computation, and suitable for implementation of real-time control. Performance of the neural controller is illustrated by simulation and experimental results for a SCARA robot.

• Journal of Computing Science and Engineering
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• 제5권1호
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• pp.85-110
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• 2011

Achieving situation awareness is especially challenging for real-time data stream applications because they i) operate on continuous unbounded streams of data, and ii) have inherent realtime requirements. In this paper we showed how formal data stream modeling and analysis can be used to better understand stream behavior, evaluate query costs, and improve application performance. We used MEDAL, a formal specification language based on Petri nets, to model the data stream queries and the quality-of-service management mechanisms of RT-STREAM, a prototype system for data stream management. MEDAL's ability to combine query logic and data admission control in one model allows us to design a single comprehensive model of the system. This model can be used to perform a large set of analyses to help improve the application's performance and quality of service.