• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.05a
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• pp.144-147
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• 2001

This paper presents adaptive fuzzy controller which is uncertainty or unknown variation in different parameters with nonlinear system of helicopter. The proposed adaptive fuzzy controller applied TSK(Takagi-Sugeno-Kang) fuzzy system which is not only low number of fuzzy rule, and a linear input-output equation with a constant term, but also can represent a large class of nonlinear system with good accuracy. The adaptive law was designed by using Lyapunov stability theory. The adaptive fuzzy controller is a model reference adaptive controller which can adjust the parameter $\theta$ so that the plant output tracks the reference model output. First of all, system of helicopter was considered as stopping state, and design of controller was simulated from dynamics equation with stopping state. Results show that it is controlled more successfully with a model reference adaptive controller than with a non-adaptive fuzzy controller when there is a modelling error between system and model or a continuous added noise in such unstable system.

• Journal of Information Technology Services
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• v.10 no.2
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• pp.177-188
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• 2011

This paper proposes a DEA model for the performance evaluation of each brand of coking coals in an integrated steel mill. The performance is defined as the efficiency which is the ratio of two linear combinations of the output factors to the input factors. There is only one input factor considered in the model : unit price of each brand based on CIF. Five output factors are chosen in consideration of their impact to the quality of cokes such as Ash, VM, LMF, TD, and Rm. Some of the output factors are treated as undesirable in DEA model because the quality criteria are given by the range. The CCR and BCC efficiencies are derived by the DEA model, and the scale efficiency is calculated, too. Each brand of coking coal is classified into four categories according to the CCR and BCC efficiencies, and the most inferior brands are identified as a result. The impact of the input and output factors to the efficiency is analyzed using a multiple regression, then the unit price is revealed as the most critical among them. Also, ANOVA results show that there exist efficiency differences among the coal types and the countries imported, respectively. Finally, the quantitative projection for the inefficient brands is performed if they are to be efficient. The result could be utilized in selecting the good or bad brands of coking coal based on the efficiency in an integrated steel mill. Also, this model will be used to assess the relative efficiency of a new brand of coking coal if it is a candidate to be imported.

• Journal of Communications and Networks
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• v.14 no.4
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• pp.443-450
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• 2012

As for cluster-based wireless sensor networks (WSNs), cluster lifetime is one of the most important subjects in recent researches. Besides reducing the energy consumptions of the clusters, it is necessary to make the clusters achieve equal lifetimes so that the whole network can survive longer. In this paper, we focus on the cluster lifetimes in multi-hop WSNs with cooperative multi-input single-output scheme. With a simplified model of multi-hop WSNs, we change the transmission schemes, the sizes and transmission distances of clusters to investigate their effects on the cluster lifetimes. Furthermore, linear and uniform data aggregations are considered in our model. As a result, we analyze the cluster lifetimes in different situations and discuss the requirements on the sizes and transmission distances of clusters for equal lifetimes.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.10
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• pp.165-171
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• 1998

An axial electromagnetic levitation system using attractive force is a highly nonlinear system due to the nonlinearity of materials, variable air gap and flux density. To control the levitating system with large air gap, a conventional PID control based on the linear model is not satisfactory to obtain the desired performance and the position tracking control of the sinusoidal motion by simulation results. Thus, sliding mode control(SMC) based on the input-output linearization is suggested and evaluated by simulation and experimental approaches. Usefulness of the SMC to this system is conformed experimentally. If the expected variation of added mass can be included in the gain conditions and the model, the position control performance of the electromagnetic levitation system with large air gap will be improved with robustness.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.4
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• pp.534-540
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• 2014

In this paper, we propose a fuzzy combined Polynomial Neural Network(PNN) for pattern classification. The fuzzy combined PNN comes from the generic TSK fuzzy model with several linear polynomial as the consequent part and is the expanded version of the fuzzy model. The proposed pattern classifier has the polynomial neural networks as the consequent part, instead of the general linear polynomial. PNNs are implemented by stacking the simple polynomials dynamically. To implement one layer of PNNs, the various types of simple polynomials are used so that PNNs have flexibility and versatility. Although the structural complexity of the implemented PNNs is high, the PNNs become a high order-multi input polynomial finally. To estimate the coefficients of a polynomial neuron, The weighted linear discriminant analysis. The output of fuzzy rule system with PNNs as the consequent part is the linear combination of the output of several PNNs. To evaluate the classification ability of the proposed pattern classifier, we make some experiments with several machine learning data sets.

• Journal of the Earthquake Engineering Society of Korea
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• v.9 no.3 s.43
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• pp.33-42
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• 2005

Frequency domain Volterra model is applied to nonlinear parameter identification procedure for dynamic systems modeled by nonlinear function. The frequency domain Volterra kernels, which correspond io linear, quadratic, and cubic transfer functions in lime domain, are incorporated in nonlinear parametric identification procedure. The nonlinear transfer functions, which can be derived from the Volterra series representation of the nonlinear differential equation of the system by Schetzen's method(1980), are directly used for modeling input output relation. The error is defined by the difference between the observed output and the estimated output which is calculated by substituting the observed input to nonlinear frequency domain model. The system parameters are searched by minimizing the error. Volterra model guarantees enough accuracy and convergence and the estimated coefficients have a good agreement with their actual values not only in the linear frequency region but also in the legion where the $2^{nd}\;or\;3^{rd}$ order nonlinearity is dominant.

• Journal of Electrical Engineering and Technology
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• v.3 no.3
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• pp.401-407
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• 2008

The dynamic model and displacement control of piezoelectric actuators, which are commercially available materials for managing extremely small displacements in the range of sub-nanometers, are presented. Piezoceramics have electromechanical characteristics that transduce energy between the electrical and mechanical domains. However, they have hysteresis between the input voltage and output displacement, and this behavior is very demanding and complicated. In this paper, we propose a method of designing the control algorithm, and present the dynamic modeling equations that represent the hysteretic behavior between input voltage and output displacement. For this process, the piezoelectric actuator is treated as a second-order linear dynamic system and system constants are determined by the system identification method. Also, a classical PID controller is designed and used to regulate the output displacement of the actuator. To evaluate the performance of the proposed method, numerical simulation results are presented.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10b
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• pp.1-6
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• 1993

This report proposes a novel method of identification of continuous time-delay systems from sampled input-output data. By the aid of a digital pre-filter, an approximated discrete-time estimation model is first derived, in which the system parameters remain in their original form and the time delay need not be an integral multiple of th sampling period. Then an identification method combining the common linear least squares(LS) method or the instrumental variable(IV) method with the genetic algorithm(GA) is proposed. That is, the time-delay is selected by the GA, and the system parameters are estimated by the LS or IV method. Furthermore, the proposed method is extended to the case of multi-input multi-output systems where the time-delays in the individual input channels may differ each other. Simulation resutls show that our method yields consistent estimates even in the presence of high measurement noises.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.160-163
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• 1996

This paper deals with MCMBPC(Multivariable Constrained Model Based Predictive Controller) for nonlinear boiler system with noise and disturbance. MCMBPC is designed by linear state space model obtained from some operating point of nonlinear boiler system and Kalman filter is used to estimate the state with noise and disturbance. The solution of optimization of the cost function constrained on input and/or output variables is achieved using quadratic programming, viz. singular value decomposition (SVD). The controller designed is shown to have excellent tracking performance via simulation applied to nonlinear dynamic drum boiler turbine model for 16OMW unit.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10a
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• pp.332-337
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• 1988

A digital series-feedback compensator algorithm for tracking time-varying signal is presented. The series-feedback compensator is composed of one closed loop pole / zero cancellation compensator and one desired-input generator. This algorithm is applied to nonlinear hydraulic position control system. The hydraulic servo system is modelled as a second order linear model and cancellation compensator is modelled from it. The desired input generator is inserted to reduce modelling error. Digital computer simulation output using this control method is present and the usefulness of this control algorithm for nonlinear hydraulic system is verified.