• Proceedings of the KIEE Conference
• /
• 2005.10b
• /
• pp.146-148
• /
• 2005

In this paper, we propose a genetically optimized identification of information granulation(IG)-based fuzzy model. To optimally design the IG-based fuzzy model we exploit a hybrid identification through genetic alrogithms(GAs) and Hard C-Means (HCM) clustering. An initial structure of fuzzy model is identified by determining the number of input, the seleced input variables, the number of membership function, and the conclusion inference type by means of GAs. Granulation of information data with the aid of Hard C-Means(HCM) clustering algorithm help determine the initial paramters of fuzzy model such as the initial apexes of the membership functions and the initial values of polyminial functions being used in the premise and consequence part of the fuzzy rules. And the inital parameters are tuned effectively with the aid of the genetic algorithms and the least square method. And also, we exploite consecutive identification of fuzzy model in case of identification of structure and parameters. Numerical example is included to evaluate the performance of the proposed model.

• 제어로봇시스템학회:학술대회논문집
• /
• 1993.10b
• /
• pp.372-377
• /
• 1993

In this paper, we investigate a set-membership identification approach to the quantification of an upper bound of model uncertainty in frequency domain, which is required in the H$_{\infty}$ robust control system design. First we formulate this problem as a set-membership identification of a nominal model error in the presence f unknown noise input with unknown bound, while the ordinary set-membership approaches assume that an upper bound of the uncertain input is known. For this purpose, the proposed algorithm includes the estimation of the bound of the uncertain input. thus the proposed method can obtain the hard bound of the model error in frequency domain as well as a parametric lower-order nominal model. Finally numerical simulation results are shown to confirm the validity of the presented algorithm..

• Transactions of the Korean Society of Mechanical Engineers B
• /
• v.24 no.3
• /
• pp.354-362
• /
• 2000

This paper identifies a discrete-time linear combustion model of Refuse Incineration Plant(RIP) which characterizes steam generation quantity, where the RIP is considered as a MIMO system with thirteen-inputs and one-output. The structure of RIP model is described as an ARX model which are analytically obtained from the combustion dynamics. Furthermore, using the Instrumental Variable(IV) identification algorithm, model structure and unknown parameters are identified from experimental input-output data sets, In result, it is shown that the identified ARX model well approximates the input-output combustion characteristics given by experimental data sets.

• Smart Structures and Systems
• /
• v.31 no.3
• /
• pp.229-245
• /
• 2023

The absence of excitation measurements may pose a big challenge in the application of structural damage identification owing to the fact that substantial effort is needed to reconstruct or identify unknown input force. To address this issue, in this paper, an iterative strategy, a synergy of Tikhonov regularization method for force identification and modified Jaya algorithm (M-Jaya) for stiffness parameter identification, is developed for damage identification with partial output-only responses. On the one hand, the probabilistic clustering learning technique and nonlinear updating equation are introduced to improve the performance of standard Jaya algorithm. On the other hand, to deal with the difficulty of selection the appropriate regularization parameters in traditional Tikhonov regularization, an improved L-curve method based on B-spline interpolation function is presented. The applicability and effectiveness of the iterative strategy for simultaneous identification of structural damages and unknown input excitation is validated by numerical simulation on a 21-bar truss structure subjected to ambient excitation under noise free and contaminated measurements cases, as well as a series of experimental tests on a five-floor steel frame structure excited by sinusoidal force. The results from these numerical and experimental studies demonstrate that the proposed identification strategy can accurately and effectively identify damage locations and extents without the requirement of force measurements. The proposed M-Jaya algorithm provides more satisfactory performance than genetic algorithm, Gaussian bare-bones artificial bee colony and Jaya algorithm.

• Transactions of the Korean Society for Noise and Vibration Engineering
• /
• v.17 no.8
• /
• pp.741-746
• /
• 2007

In this study, transfer path identification and output estimation are simulated by multi-dimension spectral analysis method (MDSA). Multi -input/single-output system give expression the vehicle suspension which each inputs are correlated reciprocally. In case of correlating with inputs, the system needs separating the each input signal by MDSA. Main simulations are about finding effective input by coherent output spectrum and selecting optimal input's number by multiple coherence function. Also, by shielding transfer path of each input, transfer path characteristic is identified in terms of overall integrated contribution level.

• Journal of Institute of Control, Robotics and Systems
• /
• v.10 no.12
• /
• pp.1280-1286
• /
• 2004

A lot of industrial chemical processes contain certain input nonlinearities even though they are controlled by several linear controllers. Here we investigate a sequential loop closing identification method for MIMO Hammerstein nonlinear processes with diagonal nonlinearities. The proposed method separates the identification of the nonlinear static function from that of the linear subsystem by using a relay feedback test and a triangular type signal test. From 2 n activations for n n MIMO nonlinear processes, we sequentially identify the whole range of the nonlinear static function as well as the transfer function matrix of the linear subsystem.

• Journal of Biosystems Engineering
• /
• v.15 no.4
• /
• pp.281-289
• /
• 1990

A frequency-domain, system-identification method using a binary multifrequency signal was developed to find the transfer function between smoke intensity and throttle position in a diesel engine. This paper describes the simulation study performed to test the identification method developed. With an assumption of a diesel operation in a limited region about the normal operating state, the linear theory was adopted. Because that air fuel ratio is one of the most important operating variables causing smoke production in diesel combustion, single-input and single-output model was adopted.

• Journal of the Korean Institute of Telematics and Electronics
• /
• v.25 no.4
• /
• pp.386-392
• /
• 1988

In this paper, we suggest a modified Gradient method for the identification of plant parameter. And also, through this new identification method, a direct adaptive control theory is proposed for a single-input single-output discrete system. Direct adaptive control theory proposed in this papar ensures global stability and the results of compute simulation show that the proposed algorithm can be applied to both stable and unstable plant.

• 제어로봇시스템학회:학술대회논문집
• /
• 1990.10a
• /
• pp.821-824
• /
• 1990

This paper presents a method for Identification of a continuous time linear system parameters. We take the plant driven by percitently exciting input. To express the integral functions in terms of measured periodic output data. We use the Walsh function based on cal-sal functions. The linear algebraic equations for parameter identification is obtained. The present method Is simple and computationally advantageous.

• Journal of Advanced Marine Engineering and Technology
• /
• v.22 no.5
• /
• pp.652-659
• /
• 1998

The present study is aimed to develop a new PIV operating software through optimization of vector tracking identification including versatile pre-processings and post-processing techniques. And the result exhibits an improved version corresponding various input and output multimedia compared to previous commercial software developed by other makers. An upgraded identification method called grey-level cross correlation coefficient method by direct calculation is suggested and related user-friendly pop-up menu are also represented. Post-processings comprising turbulence statistics are also introduced with graphic output functions.