• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.120-123
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• 1997

This paper presents models of fuzzy inference systems that can be built from a set of input-output training data pairs through hybrid structure-parameter learning. Fuzzy inference systems has the difficulty of parameter learning. Here we develop a coding format to determine a fuzzy neural network(FNN) model by chromosome in a genetic algorithm(GA) and present systematic approach to identify the parameters and structure of FNN. The proposed FNN can automatically identify the fuzzy rules and tune the membership functions by modifying the connection weights of the networks using the GA and the back-propagation learning algorithm. In order to show effectiveness of it we simulate and compare with conventional methods.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.41 no.9
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• pp.1071-1084
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• 1992

In this paper, the method for navigation and obstacle avoidance of the autonomous mobile robot is proposed. The proposed algorithms are based on the fuzzy inference system which is able to deal with imprecise and uncertain information. The self-tuning algorithm, which adopts the simplex method, modifies the parameters of membership functions of the input-output linguistic variables by changing the support of these fuzzy sets according to the integral of absolute error(IAE) of the system response. The wall-follwing navigation and obstacle avoidance of the mobile robot are based on range data measured from the internal sensors(encoder) and the outer sensors(sonar sensor). In addition, the algorithm for the obstacle detection proposed in this paper is based on the expert's experience. Finally, the effectiveness of navigation and obstacle avoidance algorithm is demonstrated through simulation and experiment.

• Proceedings of the KIPE Conference
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• 2003.07a
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• pp.162-167
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• 2003

In this paper, systematization design method by analogical Interpretation which is profitable in the compatability and standardization of developed products and is useful of reducing construction time and price was introduced. Systematization design based on analogical interpretation is a method which systematizes each characteristic with mathematical description in order to make variable design parameters correspond with the terms desired. In this paper, after choosing a differential transformer as the sample for design components each characteristic was expressed mathematically by analogical interpretation and miniaturized ones were manufactured by similarity factors. The relationship between input voltages of an actual differential transformer and the model and output voltages occurred by the change of the displacements in operational axis was shown.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.659-661
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• 1999

In this paper, we proposed a simple neural network-based parameter tuning algorithm, which could find the gradients of a certain performance index in the PID parameter spaces. In this process, we had to know the dynamics between input and output of the plant, and we used the Back Propagation Neural network to identify them. To make the parameter updating fast and smooth, we constructed the performance index as the sum of past N-squared plant errors, and applied a batch mode algorithm to update parameters. We performed several experiments with a DC Motor to show the validity of the proposed algorithm.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.2
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• pp.131-138
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• 1999

In discrete-time controlled system, sampling time is one of the critical parameters for control performance. It is useful to employ different sampling rates into the system considering the feasibility of measuring system or actuating system. The systems with the different sampling rates in their input and output channels are named multirate system. Even though the original continuous-time system is time-invariant, it is realized as time-varying state equation depending on multirate sampling mechanism. By means of the augmentation of the inputs and the outputs over one Period, the time-varying system equation can be constructed into the time-invariant equation. In this paper, an alternative time-invariant model is proposed, the design method and the stability of the LQG (Linear Quadratic Gaussian) control scheme for the realization are presented. The realization is flexible to construct to the sampling rate variations, the closed-loop system is shown to be asymptotically stable even in the inter-sampling intervals and it has smaller computation in on-line control loop than the previous time-invariant realizations.

• Journal of Advanced Marine Engineering and Technology
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• v.30 no.6
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• pp.746-752
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• 2006

This paper presents a scheme for the parameter estimation and stabilization of unstable systems, such as inverted pendulum systems. First a stable feedback loop is constructed for an inverted pendulum system and then its parameters are estimated based on input-output data, a real-coded genetic algorithm(RCGA) and the model adjustment technique. Then, a PI-type LQ control scheme is designed based on the estimated model. The performance of the proposed algorithm is demonstrated through a set of simulation and experiment.

• Structural Engineering and Mechanics
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• v.46 no.6
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• pp.853-868
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• 2013

The comparison of the effectiveness of artificial neural network (ANN) and linear regression (LR) in the prediction of strain in tie section using experimental data from eight high-strength-self-compact-concrete (HSSCC) deep beams are presented here. Prior to the aforementioned, a suitable ANN architecture was identified. The format of the network architecture was ten input parameters, two hidden layers, and one output. The feed forward back propagation neural network of eleven and ten neurons in first and second TRAINLM training function was highly accurate and generated more precise tie strain diagrams compared to classical LR. The ANN's MSE values are 90 times smaller than the LR's. The correlation coefficient value from ANN is 0.9995 which is indicative of a high level of confidence.

• Proceedings of the KIPE Conference
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• 2010.07a
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• pp.248-249
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• 2010

This paper deals with the design and experiment of 85kW(17kV, 5A) high voltage power supply for 60kW industrial magnetron. The power supply was designed based on the series resonant converter discontinuous conduction mode(DCM) which has the current source characteristic and high efficiency. In addition, inevitable leakage inductance of high voltage transformer can be used as resonant inductance. The basic analysis of full-bridge series resonant converter with transformer is given and the relationships between resonant tank parameters and input, output specification was derived. Simulation and experiment was done with variable switching frequency and their results verify the theoretical analysis.

• Proceedings of the KIPE Conference
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• 2005.07a
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• pp.697-700
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• 2005

An adaptive fuzzy sliding-mode controller (SMC) for uncertain or ill-defined single-input single-output (SISO) nonaffine nonlinear systems is proposed. By using the universal approximation property of the fuzzy logic system (FLS), it is tuned on-line to cancel the unknown system nonlinearity. We adopt a self-structuring FLS to guarantee global stability of the closed-loop system rather than semi=global boundedness. The control and adaptive laws are derived so that the estimated fuzzy parameters are bounded and the sliding condition is satisfied.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2651-2654
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• 2000

In this paper, we re-analyzed the fuzzy controller as conventional PID controller structure, and proposed a self tuning fuzzy PID controller whose input output scaling factors were tuned automatically. At first stage, the tuning parameters of fuzzy controller were determined by Ziegler-Nichols tuning method and then they were adjusted as the delay time and process environment were changed. Proposed controller was simple in its structrue and computational burden was small so that on line adaptation was easy to apply to. The result of computer simulation and practical experiment showed the proposed controller's excellent performance