• Proceedings of the KIEE Conference
• /
• 1993.07a
• /
• pp.313-315
• /
• 1993

This paper presents the control of input/output automata. The input/output automata provides an appropriate model for discrete event systems consisting of concurrently-operating components. Ramadge and Wonham's supervisor controller can be transformed into the controllter of input/output automata. Using input/output automata, the modelling can be more realistic and concurrent discrete event systems can be controlled easily.

• 제어로봇시스템학회:학술대회논문집
• /
• 1993.10a
• /
• pp.460-465
• /
• 1993

The instrumentation system is the most important aspect of a flight test program. It is the means by which the objective of a flight test, the production of accurate, useful data, is achieved. An instrumentation system consists of everything required to sense, condition, and record all parameters of interest The task of a flight test engineer is to select a system that is adequate to obtain all needed data, but not complex, expensive, and heavy than the situation demands. In this paper, the primary factors that determine the design of an instrumentation system are discussed.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2003.09a
• /
• pp.496-499
• /
• 2003

Support Vector Machines (SVMs) is applied to a practical problem as one of standard tools for machine learning. The application of Reinforcement Learning (RL) and SVMs in action of mobile robot is investigated. A technique to decide the action of autonomous mobile robot in practice is explained in the paper, The proposed method is to find n basis for good action of the system under unknown environment. In multi-dimensional sensor input, the most reasonable action can be automatically decided in each state by RL. Using SVMs, not only optimal decision policy but also generalized state in unknown environment is obtained.

• Proceedings of the KIEE Conference
• /
• 2000.11d
• /
• pp.679-681
• /
• 2000

This thesis presents a analysis method of hybrid synthesis petri net for automated manufacturing systems in discrete event dynamic system. There are many errors that can happen to petri net modeling of complex systems because petri net modeling process has so many steps. A new matrix analysis method presented in this thesis can confirm the property of petri net such as boundedness, liveness and reversibility, modify errors which can be occurred in modeling.

• Proceedings of the KIEE Conference
• /
• 1999.07b
• /
• pp.838-840
• /
• 1999

In this paper, modeling and analysis of discrete event systems by temporal logic frame works and petri net is considered. The reachability tree of the petri net can be used to solve the safeness, boundedness, conservation and coverability problems of discrete event systems. But the reachability tree of the petri net do not solve reachability and liveness problems in general. We proposed a method that synthesised the petri net and the temporal logic frameworks. This method slove some problems of petri net by logical representation of temporal logic frameworks.

• 제어로봇시스템학회:학술대회논문집
• /
• 1990.10b
• /
• pp.1355-1360
• /
• 1990

This paper describes the application of the recently developed feedback linearization technique to the design of a new command to line-of-sight (CLOS) guidance law for skid-to-turn (STT) missiles. The key idea lies in converting the three dimensional CLOS guidance problem to the tracking problem of a time-varying nonlinear system. Then, using a feeedback linearizing approach to tracking in nonlinear systems, we design a three dimensional CLOS guidance law that can ensure zero miss distance for a randomly maneuvering target. Our result may shed new light on the role of the feedforward acceleration terms used in the earlier CLOS guidance laws. Furthermore, we show that the new CLOS guidance law can be computationally simplified without performance degradation. This is made possible by dropping out the terms in the new CLOS guidance law, which obey the well-known matching condition.

• Proceedings of the KIEE Conference
• /
• 1997.07b
• /
• pp.590-592
• /
• 1997

A Discrete Event Dynamic System is a system whose states change in response to the occurrence of events from a predefined event set. A major difficulty in developing analytical results for the systems is the lack of appropriate modeling techniques. This paper proposes the use of Real-time Temporal Logic as a modeling tool for the analysis and control of DEDS. The Real-time Temporal Logic Frameworks is extended with a suitable structure of modeling hard real-time constraints. Modeling rules are developed for several specific situations. It is shown how the graphical model can be translated to a system of linear equations and constraints.

• Proceedings of the KIEE Conference
• /
• 2000.07d
• /
• pp.3001-3003
• /
• 2000

In this paper. we propose Fuzzy Self-Organizing Networks (FSON) using both Polynomial Neural Networks(PNN) and Fuzzy Neural Networks(FNN) for model identification of complex and nonlinear systems. The proposed FSON is generated from the mutually combined structure of both FNN and PNN. Accordingly it is possible to consider the nonlinearity characteristics of process and to get the better output performance with superb predictive ability. In order to evaluate the performance of proposed models. we use the nonlinear data sets. The results show that the proposed FSON can produce the model with higher accuracy and more robustness than previous any other method.

• Proceedings of the KIEE Conference
• /
• 2001.07d
• /
• pp.2283-2285
• /
• 2001

This paper proposed to a neural network based fuzzy control (neuro-fuzzy control) technique for attitude control of helicopter with strongly dynamic nonlinearities and derived a helicopter aerodynamic torque equation of helicopter and the force balance equation. A neuro-fuzzy system is a feedforward network that employs a back-propagation algorithm for learning purpose. A neuro-fuzzy system is used to identify nonlinear dynamic systems. Hence, this paper presents methods for the design of a neural network(NN) based fuzzy controller(that is, neuro-fuzzy control) for a helicopter of nonlinear MIMO systems. The proposed neuro-fuzzy control determined to a input-output membership function in fuzzy control and neural networks constructed to improve through learning of input-output membership functions determined in fuzzy control.

• Nuclear Engineering and Technology
• /
• v.48 no.5
• /
• pp.1192-1205
• /
• 2016

Field programmable gate array (FPGA)-based systems are thought to be a practical option to replace certain obsolete instrumentation and control systems in nuclear power plants. An FPGA is a type of integrated circuit, which is programmed after being manufactured. FPGAs have some advantages over other electronic technologies, such as analog circuits, microprocessors, and Programmable Logic Controllers (PLCs), for nuclear instrumentation and control, and safety system applications. However, safety-related issues for FPGA-based systems remain to be verified. Owing to this, modeling FPGA-based systems for safety assessment has now become an important point of research. One potential methodology is the dynamic flowgraph methodology (DFM). It has been used for modeling software/hardware interactions in modern control systems. In this paper, FPGA logic was analyzed using DFM. Four aspects of FPGAs are investigated: the "IEEE 1164 standard," registers (D flip-flops), configurable logic blocks, and an FPGA-based signal compensator. The ModelSim simulations confirmed that DFM was able to accurately model those four FPGA properties, proving that DFM has the potential to be used in the modeling of FPGA-based systems. Furthermore, advantages of DFM over traditional reliability analysis methods and FPGA simulators are presented, along with a discussion of potential issues with using DFM for FPGA-based system modeling.