• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.244-249
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• 1998

In this paper, the hybrid state space self-tuning control technique Is studied within the framework of fuzzy systems and dual-rate sampling control theory. We show that fuzzy modeling techniques can be used to formulate chaotic dynamical systems. Then, we develop the hybrid state space self-tuning fuzzy control techniques with dual-rate sampling for digital control of chaotic systems. An equivalent fast-rate discrete-time state-space model of the continuous-time system is constructed by using fuzzy inference systems. To obtain the continuous-time optimal state feedback gains, the constructed discrete-time fuzzy system is converted into a continuous-time system. The developed optimal continuous-time control law is then convened into an equivalent slow-rate digital control law using the proposed digital redesign method. The proposed technique enables us to systematically and effective]y carry out framework for modeling and control of chaotic systems. The proposed method has been successfully applied for controlling the chaotic trajectories of Chua's circuit.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.37 no.2
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• pp.85-93
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• 2024

In this paper, we propose a method for establishing a state-space equation model for the motion analysis of floating structures subjected to wave loads, by applying system-identification techniques. Traditionally, the motion of floating structures has been analyzed in the time domain by integrating the Cummins equation over time, which utilizes a convolution integral term to account for the effects of the retardation function. State-space equation models have been studied as a way to efficiently solve floating-motion equations in the time domain. The proposed approach outlines a procedure to derive the target transfer function for the load-displacement input/output relationship in the frequency domain and subsequently determine the state-space equation that closely approximates it. To obtain the state-space equation, the method employs the N4SID system-identification method and an optimization approach that treats the coefficients of the numerator and denominator polynomials as design variables. To illustrate the effectiveness of the proposed method, we applied it to the analysis of a single-degree-of-freedom model and the motion of a six-degree-of-freedom barge. Our findings demonstrate that the presented state-space equation model aligns well with the existing analysis results in both the frequency and time domains. Notably, the method ensures computational accuracy in the time-domain analysis while significantly reducing the calculation time.

• Communications of the Korean Mathematical Society
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• v.10 no.3
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• pp.715-733
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• 1995

We present a transient queue size distribution for $M/G/m/N$ queue with state dependent arrival rates, using the diffusion process with piecewise constant diffusion parameters, with state space [0, N] and elementary return boundaries at x = 0 and x = N. The model considered here contains not only many basic model but the practical models such as as two-node cyclic queue, repairmen model and overload control in communication system with finite storage buffer. For the accuracy check, we compare the approximation results with the exact and simulation results.

• Journal of Electrical Engineering and Technology
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• v.12 no.3
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• pp.1146-1155
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• 2017

Normally, the artificial intelligence algorithms are widely applied to the optimal controller design. Then, it is expected that the best output performance is achieved. Unfortunately, when resulting controller parameters are implemented by using the practical devices, the output performance cannot be the best as expected. Therefore, the paper presents the optimal controller design using the combination between the state-space averaging model and the adaptive Tabu search algorithm with the new criteria as two penalty conditions to handle the mentioned problem. The buck-boost converter regulated by the cascade PI controllers is used as the example power system. The results show that the output performance is better than those from the conventional design method for both input and load variations. Moreover, it is confirmed that the reported controllers can be implemented using the realistic devices without the limitation and the stable operation is also guaranteed. The results are also validated by the simulation using the topology model of MATLAB and also experimentally verified by the testing rig.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.8 no.4
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• pp.264-269
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• 2008

In this paper, two neural networks as a material model, which are based on the state-space method, have been proposed. One outputs the rates of inelastic strain and material internal variables whereas the outputs of the other are the next state of the inelastic strain and material internal variables. Both the neural networks were trained using input-output data generated from Chaboche's model and successfully converged. The former neural network could reproduce the original stress-strain curve. The neural network also demonstrated its ability of interpolation by generating untrained curve. It was also found that the neural network can extrapolate in close proximity to the training data.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2606-2611
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• 2003

Comprehensive study on the control system design for a RTP process has been conducted. The purpose of the control system is to maintain maximum temperature uniformity across the silicon wafer achieving precise tracking for various reference trajectories. The study has been carried out in two stages: thermal balance modeling on the basis of a semi-empirical radiation model, and optimal iterative learning controller design on the basis of a linear state space model. First, we found through steady state radiation modeling that the fourth power of wafer temperatures, lamp powers, and the fourth power of chamber wall temperature are related by an emissivity-independent linear equation. Next, for control of the MIMO system, a state space modeland LQG-based two-stage batch control technique was derived and employed to reduce the heavy computational demand in the original two-stage batch control technique. By accommodating the first result, a linear state space model for the controller design was identified between the lamp powers and the fourth power of wafer temperatures as inputs and outputs, respectively. The control system was applied to an experimental RTP equipment. As a consequence, great uniformity improvement could be attained over the entire time horizon compared to the original multi-loop PID control. In addition, controller implementation was standardized and facilitated by completely eliminating the tedious and lengthy control tuning trial.

• Journal of Korea Game Society
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• v.4 no.1
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• pp.58-66
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• 2004

This paper uses counterexamples for solving reachability games. An objective. of the game we consider here is to find out a minimal path from an initial state to the goal state. We represent initial states and game rules as finite state model and the goal state as temporal logic formula. Then, model checking is used to determine whether the model satisfies the formula. In case the model does not satisfy the formula, model checking generates a counterexample that shows how to reach the goal state from an initial state. In this way, we solve many of small-sized Push Push games. However, we cannot handle larger-sized games due to the state explosion problem. To mitigate the problem, abstraction is used to reduce the state space to be che cked. As a result, unsolved games are solved with the abstraction technique we propose inthis paper.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.36 no.4
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• pp.301-304
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• 1987

The Optimal Control Problems for the singular system with the Generalized state space model are considered. It is shown that when the system is singular, the dimension can be reduced by coordinate transformation and the equivalent nonsingular system is got. After we have nonsingular system, the solution for the optimal control problem can be got by Riccati equation.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.33 no.12
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• pp.491-496
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• 1984

The optimal control and filtering problems for the systems with the generalized state space model are considered and the generalized Riccati equation is derived. Also the algorithm for the solution of the generalized algebraic Riccati equation is developed and it is shown that the algotithm can be applied to the case where the matrix R is singular or near singular.

• Proceedings of the KIPE Conference
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• 2019.07a
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• pp.483-484
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• 2019

This paper proposes a harmonic state space (HSS) modeling of DC microgrid. In the HSS model, nonlinear equations for the switched circuit model are transformed into multiple linear equations. The simulation results have shown the HSS modeling is comparable with PSIM simulation.