• Advances in robotics research
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• v.2 no.1
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• pp.99-112
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• 2018

The main contribution of this work is the design of a field programmable gate array (FPGA) based ARX-Laguerre proportional-integral observation (PIO) system for fault detection and identification (FDI) in a multi-input, multi-output (MIMO) nonlinear uncertain dynamical robot manipulators. An ARX-Laguerre method was used in this study to dynamic modeling the robot manipulator in the presence of uncertainty and disturbance. To address the challenges of robustness, fault detection, isolation, and estimation the proposed FPGA-based PI observer was applied to the ARX-Laguerre robot model. The effectiveness and accuracy of FPGA based ARX-Laguerre PIO was tested by first three degrees of the freedom PUMA robot manipulator, yielding 6.3%, 10.73%, and 4.23%, average performance improvement for three types of faults (e.g., actuator fault, sensor faults, and composite fault), respectively.

• Earthquakes and Structures
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• v.7 no.6
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• pp.1093-1118
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• 2014

A sophisticated story-wise stiffness identification method for a shear building structure is applied to the case where the shear building is subjected to an actual micro-tremor. While the building responses to earthquake ground motions are necessary in the previous method, it is shown that micro-tremors can be used for identification within the same framework. This enhances the extended usability and practicality of the previously proposed identification method. The difficulty arising in the limit manipulation at zero frequency in the previous method is overcome by introducing an ARX model. The weakness of small SN ratios in the low frequency range is avoided by using the ARX model together with filtering and introducing new constraints on the ARX parameters.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.10
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• pp.827-832
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• 2002

We propose a prediction method of the pollutant and a synchronous classification of the current state of SOx emission in the power plant. We use the auto-regressive with exogeneous (ARX) model as a predictor of SOx emission and use a radial basis function network (RBFN) as a pattem classifier. The ARX modeling scheme is implemented using recursive least squares (RLS) method to update the model parameters adaptively. The capability of SOx emission monitoring is utilized with the application of the RBFN classifier. Experimental results show that the ARX model can predict the SOx emission concentration well and ARX modeling parameters can be a good feature for the state monitoring. in addition, its validity has been verified through the power spectrum analysis. Consequently, the RBFN classifier in combination with ARX model is shown to be quite adequate for monitoring the state of SOx emission.

• Korean Chemical Engineering Research
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• v.45 no.1
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• pp.67-72
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• 2007

An efficient method for identification of MIMO state space model has been developed by combining partial least squares (PLS) regression, balanced realization, and balanced truncation. In the developed method, a MIMO system is decomposed into multiple MISO systems each of which is represented by a high-order ARX model and the parameters of the ARX models are estimated by PLS. Then, MISO state space models for respective MISO ARX transfer function are found through realization and combined to a MIMO state space model. Finally, a minimal balanced MIMO state space model is obtained through balanced realization and truncation. The proposed method was applied to the design of model predictive control for temperature control of a high pressure $CO_2$ solubility measurement system.

• International Journal of Control, Automation, and Systems
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• v.1 no.1
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• pp.111-118
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• 2003

This paper proposes a two dimensional behavior analysis method for fish in a water tank based on the ARX method and the Kalman filter algorithm using image processing technology. In modeling the behavior of fish, the input is denoted as the environmental change and uses M-sequence. The output is expressed by the partnership between fish. The behavior model of individual fish is identified by the ARX method. It is then estimated by the Kalman filter algorithm. Finally, the fish behavior is analyzed by FFT. To prove the effectiveness of the pro-posed algorithm, it is applied to two tilapias in a water tank with dimensions of 100cm$\times$100cm$\times$50cm. The effectiveness of the proposed method is demonstrated through ARX identification, estimation of Kalman filter, and FFT analysis.

• Journal of the Earthquake Engineering Society of Korea
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• v.21 no.6
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• pp.287-293
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• 2017

Sometimes, it is impossible to install a sensor on a certain location of a structure due to the size of a structure or poor surrounding environments. Even if possible, sensors can be frequently malfunctioned or improperly operated due to lack of adequate maintenance. These kind of problems are solved by the virtual sensing methods in various engineering fields. Virtual sensing technology is a technology that can measure data even though there is no physical sensor. It is expected that this technology can be also applied to the construction field effectively. In this study, a virtual sensing technology based on ARX model is proposed. An ARX model is defined by using the simulated data through a structural analysis rather than by actually measured data. The ARX-based virtual sensing model can be applied to estimate unmeasured response using a transfer function that defines the relationship between two point data. In this study, a simulation and experimental study were carried out to examine the proposed virtual sensing method with a laboratory test on a cable-stayed model bridge. Acceleration measured at a girder is transformed to estimate a cable tension through the ARX model-based virtual sensing.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.7
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• pp.556-562
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• 2002

This paper studies the identification of a combustion model, which is used to design a linear controller of a steam generation quantity and harmful exhaust gases of a Refuse Incineration Plant(RIP). Even though the RIP has strong nonlinearities and complexities, it is identified as a MIMO parametric ARX model from experimental input-output data sets. Unknown model parameters are decided from experimental input-output data sets, using system identification algorithm based on Instrumental Variables(IV) method. It is shown that the identified model well approximates the input-output combustion characteristics.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.26 no.3
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• pp.623-630
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• 2016

Heterogeneous IoT devices must satisfy a certain level of security for mutual connections and communications. However, a performance degradation of cryptographic algorithms in resource constrained devices is inevitable and so an optimization or efficient implementation method is necessary. In this paper, we study an efficient implementation method for rotation operations regarding registers for running ARX lightweight block ciphers. In a practical sense, we investigate the performance of modified rotation operations through experiments using real experiment devices. We show the improved performance of modified rotation operations and discover the significant difference in measured performance between simulations and real experiments, particularly for 16-bit MSP microcontrollers.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.26 no.6
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• pp.1421-1430
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• 2016

In this paper, we suggest an advanced method searching for differential trails of block cipher with ARX structure. we use two techniques to optimize the automatic search algorithm of differential trails suggested by A. Biryukov et al, and obtain 2~3 times faster results than Biryukov's when implemented in block cipher SPECK. This results contribute to find better differential trails than previous results.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.27 no.3
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• pp.427-437
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• 2017

Impossible differential characteristics distinguish the corresponding block cipher from random substitution and can also be used for key recovery attack. Recently Cui et al. proposed an automatic method for searching impossible differential characteristics of several ARX - based block ciphers using Mixed Integer Linear Programming(MILP). By optimizing the method proposed by Cui et al., It was possible to find new impossible differential characteristics which could not be founded by the method by using less linear constraint expression than the existing method. It was applied to the SPECK family and LEA using the modified method. We found 7-rounds for SPECK32, SPECK48, SPECK64, SPECK96 and 8-rounds impossible differential characteristics of SPECK128. These impossible differential characteristics are all newly found. We also found existing 10-rounds of impossible differential characteristic and new 10-rounds of impossible differential characteristics of LEA.