• 전기학회논문지
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• 제67권8호
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• pp.1062-1070
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• 2018

This paper presents a simple identification method for discrete-time low-order model of unknown delay process from pulse response. The key idea is to find the parameters of the model such that the first N moments of the unknown process and the model are equal. We first show that the k-th moment of a process can be determined by the moments of the input and output. The parameters and delay are estimated separately. It is shown that for a given delay, the parameters of the low-order model can be determined by solving linear equations in a matrix form. Delay of the model is estimated such that the integral of the absolute errors (IAE) of the candidate models with possible delays minimizes. The illustrative example shows that the proposed method can directly identify low-order models without order reduction process from a single pulse response.

• 제어로봇시스템학회논문지
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• 제3권6호
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• pp.555-562
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• 1997

With only the classical PID controller applied to control of a DC motor, good (target) performance characteristic of the controller can be obtained if all the model parameters of DC motor and operating conditions such as external load torque, disturbance, etc. are known exactly. However, in case when some of system parameters or operating conditions are uncertain or unknown, the fixed PID controller does not guarantee good performance, which is assumed with precisely known system parameters and operating conditions. In view of this and the robustness enhancement of DC motor control system, we propose a PID learning controller which consists of a set of learning rules for PID gain tuning and learning of an auxiliary input. The proposed PID learning controller is shown to drive the state of uncertain DC motor system with unknown system parameters and external load torque to the desired one world wide asymptotically. Computer simulation and experimental results are given to demonstrate the effectiveness of the proposed PID learning controller, thereby showing its superiority to the conventional fixed PID controller.

• 산업경영시스템학회지
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• 제28권3호
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• pp.26-35
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• 2005

This paper is intended to compare the hazard rate estimations from Bayesian approach and maximum likelihood estimate(MLE) method. Hazard rate frequently involves unknown parameters and it is common that those parameters are estimated from observed data by using MLE method. Such estimated parameters are appropriate as long as there are sufficient data. Due to various reasons, however, we frequently cannot obtain sufficient data so that the result of MLE method may be unreliable. In order to resolve such a problem we need to rely on the judgement about the unknown parameters. We do this by adopting the Bayesian approach. The first one is to use a predictive distribution and the second one is a method called Bayesian estimate. In addition, in the Bayesian approach, the prior distribution has a critical effect on the result of analysis, so we introduce the method using computerized-simulation to elicit an effective prior distribution. For the simplicity, we use exponential and gamma distributions as a likelihood distribution and its natural conjugate prior distribution, respectively. Finally, numerical examples are given to illustrate the potential benefits of the Bayesian approach.

• 조명전기설비학회논문지
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• 제23권11호
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• pp.9-21
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• 2009

This paper proposes the alternative observer and controller design scheme based on T-S fuzzy model. Nonlinear systems are represented by fuzzy models since fuzzy logic systems are universal approximators. In order to estimate the unmeasurable states of a given unknown nonlinear system, T-S fuzzy modeling method is applied to get the dynamics of an observation system. T-S fuzzy system uses the linear combination of the input state variables and the modeling applications of them to various kinds of nonlinear systems can be found. The proposed indirect adaptive fuzzy observer based on T-S fuzzy model can cope with not only unknown states but also unknown parameters. The proposed controller is based on a simple output feedback method. Therefore, it solves the singularity problem, without any additional algorithm, which occurs in the inverse dynamics based on the feedback linearization method. The adaptive fuzzy scheme estimates the parameters and the feedback gain comprising the fuzzy model representing the observation system. In the process of deriving adaptive law, the Lyapunov theory and Lipchitz condition are used. To show the performance of the proposed observer and controller, they are applied to an inverted pendulum on a cart.

• 전자공학회논문지B
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• 제31B권7호
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• pp.58-65
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• 1994

A recursive on-line algorithm for orthogonal ARMA identification is proposed for linear MIMO systems with unknown parameters time delay and order. This algorithm is based on the Gram-Schmidt orthogonalization of basis functions, and extended to a recursiveform by using new functions of two dimensional autocorrelations and crosscorrelations of inputs and outputs. This proposed algorithm can also cope with slowly time-varying or order-varying systems. Various simulations reveal the performance of the algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1993년도 한국자동제어학술회의논문집(국내학술편); Seoul National University, Seoul; 20-22 Oct. 1993
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• pp.58-63
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• 1993

A recursive on-line algorithm with orthogonal ARMA identification is proposed for linear MIMO systems with unknown parameters, time delay, and order. This algorithm is based on the Gram-Schmidt orthogonalization of basis functions, and extended to a recursive form by using new functions of two dimensional autocorrelations and cross-correlations of inputs and outputs. The proposed algorithm can also cope with slowly time-varying or order-varying systems. Various simulations reveal the performance of the algorithm.

• 대한수학회보
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• 제51권5호
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• pp.1347-1356
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• 2014

In this paper, we analyze the security of the KMOV public key cryptosystem. KMOV is based on elliptic curves over the ring $\mathbb{Z}_n$ where n = pq is the product of two large unknown primes of equal bit-size. We consider KMOV with a public key (n, e) where the exponent e satisfies an equation ex-(p+1)(q+1)y = z, with unknown parameters x, y, z. Using Diophantine approximations and lattice reduction techniques, we show that KMOV is insecure when x, y, z are suitably small.

• Journal of Electrical Engineering and information Science
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• 제2권3호
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• pp.61-65
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• 1997

This paper proposes an intelligent controller for brushless DC motor and load with unknown nonlinear dynamics. The proposed intelligent control system consists of a plant identifier and PID controller with varying gains. The identifier is constructed using an Auto Regressive Moving Average (ARMA) model. In order to tune the parameters of the identifier and the gains of the PID controller efficiently, e also propose a modified Evolution Strategy. Experimental results show that the proposed intelligent controller for brushless DC motor has good control performance under unknown disturbance.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1994년도 추계학술대회 논문집 학회본부
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• pp.345-348
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• 1994

A real-time collision avoidance algorithm for an AMR (Autonomous Mobile Robot) using the Distance Transform and Vector Field Histogram is studied. This approach enables AMR to find a collision-free path with the unknown obstacles. All system parameters including positions of the obstacles can be accepted using a mouse icon and all the obtained trajectories can be displayed on a computer monitor in graphics.

• Smart Structures and Systems
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• 제12권6호
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• pp.619-640
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• 2013

It is highly desirable to explore efficient algorithms for detecting structural damage of large size structural systems with limited input and output measurements. In this paper, a new structural damage detection algorithm based on substructure approach is proposed for large size structural systems with limited input and output measurements. Inter-connection effect between adjacent substructures is treated as 'additional unknown inputs' to substructures. Extended state vector of each substructure and its unknown excitations are estimated by sequential extended Kalman estimator and least-squares estimation, respectively. It is shown that the 'additional unknown inputs' can be estimated by the algorithm without the measurements on the substructure interface DOFs, which is superior to previous substructural identification approaches. Also, structural parameters and unknown excitation are estimated in a sequential manner, which simplifies the identification problem compared with other existing work. Structural damage can be detected from the degradation of the identified substructural element stiffness values. The performances of the proposed algorithm are demonstrated by several numerical examples and a lab experiment. Measurement noise effect is considered. Both the simulation results and experimental data validate that the proposed algorithm is viable for structural damage detection of large size structural systems with limited input and output measurements.