• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2000.04a
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• pp.453-458
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• 2000

Design of an in-process feedback control system has been studied for precision grinding. A grinding system consists of a grinding tool, a turn table and a disk-shaped workpiece on the table is taken as an object. A grinding process model has been deduced which gives some reasoning about the process errors. In the control system the tool position is actively controlled by an electro-magnetic actuator in-process. The ground error is feedback to compose a closed-loop control system and an optimal PID controller is applied. Some control performances such as transient response and disturbance such as transient response and disturbance attenuation have been examined, which convinces the effectiveness of the control. Some methods for implementation of the control. Some methods for implementation of the control have been suggested from a standpoint of practical application.

• International Journal of Aeronautical and Space Sciences
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• v.15 no.3
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• pp.281-292
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• 2014

We propose a novel cooperative guidance law design method based on the finite time disturbance observer (FTDO) for multiple near space interceptors (NSIs) with impact time control. Initially, we construct a cooperative guidance model with head pursuit, and employ the FTDO to estimate the system disturbance caused by target maneuvering. We subsequently separate the cooperative guidance process into two stages, and develop the normal acceleration command based on the super-twisting algorithm (STA) and disturbance estimated value, to ensure the convergence of the relative distance. Then, we also design the acceleration command along the line-of-sight (LOS), based on the nonsingular fast terminal sliding mode (NFTSM) control, to ensure that all the NSIs simultaneously hit the target. Furthermore, we prove the stability of the closed-loop guidance system, based on the Lyapunov theory. Finally, our simulation results of a three-to-one interception scenario show that the proposed cooperative guidance scheme makes all the NSIs hit the target at the same time.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.8
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• pp.898-906
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• 1999

A control structure is introduced for the purpose of rejecting periodic (or repetitive) disturbances on a tracking system. The objective of the proposed structure is to drive the output of the system to the reference input that will result in perfect following without any changing the inner configuration of the system. The structure includes an adaptation block which learns the dynamics of the periodic disturbance and forces the interferences, caused by disturbances, on the output of the system to be reduced. Since the control structure acquires the dynamics of the disturbance by on-line adaptation, it is possible to generate control signals that reject any slowly varying time-periodic disturbance provided that its amplitude is bounded. The artificial neural network is adopted as the adaptation block. The adaptation is done at an on-line process. For this , the real-time recurrent learning (RTRL) algoritnm is applied to the training of the artificial neural network.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.41 no.8
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• pp.783-789
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• 2017

In terms of 3D orientation estimation based on nine-axis IMMU(inertial and magnetic measurement unit), there are two disturbance components decreasing estimation accuracy: one is external acceleration disturbing accelerometer's signals and the other is magnetic disturbance related to magnetometer's signals. In order to minimize effects by these two disturbances, two approaches including switching approach and model-based approach have been suggested and further research comparing these two has also been conducted. Nevertheless, effect of disturbance modeling differences on orientation estimation accuracy in model-based approach has not been studied before. This paper compares the recently reported two orientation estimation algorithms that have difference in disturbance models, in order to investigate the effect of disturbance models on accuracy of IMMU-based orientation estimation under various operating conditions. This research shows that the difference in disturbance models leads to difference in process noise covariance matrix. Consequently, this affected the orientation estimation, i.e., the estimation differences between the algorithms were root mean square errors of $1.35^{\circ}$ in average and $3.63^{\circ}$ in yaw estimation.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.4C
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• pp.149-157
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• 2012

In order to investigate the soil disturbance induced by anchor-shoe for PVD installation and the anchoring mechanism, a new two dimensional testing system was developed. By using the developed testing system, 1g and centrifuge model tests were performed, simulating the driving-retrieval process of both conventional symmetric anchor shoe and new asymmetric anchor shoe. Various size anchor-shoes were simulated and the results were compared. The images recorded during the installation were analyzed by image processing technique. The results of the image analysis presented the clay disturbance depending on the size and type of anchor shoe. In addition, from the retrieval process, the anchoring mechanism was revealed and the holding capacity was measured. As results, the size of anchor shoe influences the soil disturbance and holding capacity. The new asymmetric anchor shoe reduces the soil disturbance and improves anchoring performance.

• Journal of Electrical Engineering and Technology
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• v.11 no.2
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• pp.309-319
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• 2016

This paper presents a new recognition and classification method for power quality (PQ) disturbances on the basis of pattern linguistic values. This method solves the difficulty of recognizing disturbances rapidly and accurately by using fuzzy logic. This method uses classification disturbance patterns to define the linguistic values of fuzzy input variables and used the input variables of corresponding disturbance pattern to set membership functions. This method also sets the fuzzy rules by analyzing the distribution regularities of the input variable values. One characteristic of this method is that the linguistic values of fuzzy input variables and the setting of membership functions are not only related to the input variables but also to the character of classification disturbance and the classification results. Furthermore, the number of fuzzy rules is equal to the number of disturbance patterns. By using this method for disturbance classification, the membership function and design of fuzzy rules are directly related to the objective of classification, thus effectively reducing the complexity of the design process and yielding accurate classification results. The classification results of the simulation and measured data verify the feasibility and effectiveness of this method.

• Transactions of Materials Processing
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• v.8 no.4
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• pp.393-398
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• 1999

The plastic instable flow phenomenon happens in practical forming process, I. e. upsetting, backward extrusion, piercing, indentation. And also, it is difficult to control precisely the shape and dimensions of forming process. It is found that instabilities of the process are mainly connected with imperfections in the lubrication, billet eccentricity, inclined punch alignment. In view of the direct relationship between instable material flow and quality defects of the products and for better control of forming operation, we should necessarily find out their phenomena. In this study, we introduced the friction disturbance due to inclined punch angle. Analysis of upset forging is carried out using the rigid plastic FEM and slab method with eccentricity. Also, we considered the buckling parameters of billet with the large aspect ratio in upset forging.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.8 no.1
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• pp.24-30
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• 2008

A simulation of hot strip finishing mill automatic gauge control (AGC) system is built, which is divided into four modules such as rolling mill system, AGC module, looper system and strip model. The rolling mill system is built by mechanism modeling, the looper system and strip model are built by function modeling, and the AGC model is tried to use intelligent control of a multi-function AGC system. The target is attempted to use this simulation object to minimize finisher exit strip thickness deviation resulting from strip entry thickness disturbance and rolling force deviation. Simulation results show that the result of this AGC/LPC synthetical system module simulation is quite close to the actual result. The simulation system can also analyze most kinds of disturbance which affect the rolling process. It is proved that the system can represent practical situation of hot strip finishing mill process control, and be used as a basic platform of research and development for researcher and engineer.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 1999.03b
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• pp.98-101
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• 1999

The plastic instable flow phenomenon happens in practical forming process I. e. upsetting backward extrusion piercing indentation. And also it is difficult to control precisely the shape and dimensions of forming process. It is found that instabilities of the process are mainly connected with imperfection in the lubrication billet eccentricity inclined punch alignment. In view of the direct relationship between instable material flow and quality defects of the products and it is for better control of forming operation we should necessarily find out their phenomena. In this study we used the friction disturbance due to inclined punch angle and introduced the method considering kinematic hardening effect Analysis of upset forging is carried out using the rigid plastic FEM and slab method with eccentricity.

• Nuclear Engineering and Technology
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• v.32 no.3
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• pp.261-273
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• 2000

During an extensive review made as part of the Integrated Diagnosis System project of the Maiden Reactor Project, MOAS (Maryland Operator Advisory System) was identified as one of the most thorough systems developed thus far. MOAS is an integrated on-line diagnosis system that encompasses diverse functional aspects that are required for an effective process disturbance management: (1) intelligent process monitoring and alarming, (2) on-line sensor data validation and sensor failure diagnosis, (3) on-line hardware (besides sensors) failure diagnosis, and (4) real-time corrective measure synthesis. The MOAS methodology was used at the Maiden Man-Machine Laboratory HAMMLAB of the OECD Maiden Reactor Project. The performance of MOAS, developed in G2 real-time expert system shell for the high-pressure preheaters of the NORS process in the HAMMLAB, was tested against a variety of transient scenarios, including failures of the control valves and sensors, and tube leakage of the preheaters. These tests showed that MOAS successfully carried out its intended functions, i.e., quickly recognizing an occurring disturbance, correctly diagnosing its cause, and presenting advice on its control to the operator. The lessons learned and insights gained during the implementation and performance tests also are discussed.