• Transactions on Control, Automation and Systems Engineering
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• v.4 no.4
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• pp.277-282
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• 2002

This paper proposes a nonlinear adaptive controller based on back-stepping method for tracking reference substrate concentration by manipulating dilution rate in a continuous baker's yeast cultivating process in stirred tank bioreactor. Control law is obtained from Lyapunov control function to ensure asymptotical stability of the system. The Haldane model for the specific growth rate depending on only substrate concentration is used in this paper. Due to the uncertainty of specific growth rate, it has been modified as a function including the unknown parameter with known bounded values. The substrate concentration in the bioreactor and feed line are measured. The deviation from the reference is observed when the external disturbance such as the change of the feed is introduced to the system. The effectiveness of the proposed controller is shown through simulation results in continuous system.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1877-1880
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• 2005

This paper proposed the new current feed-back amplifier for low supply voltage application. The input stage was designed to be a class-AB circuit and achieve the low supply-voltage operation down to $2V_{TH}+2V_{DS(SAT)}$. With the self-adjust bias current, the high performance can be adopted with high stability. The circuit was successfully proven by the simulation with MOSIS 0.5 ${\mu}$m MOS technology.

• Journal of Advanced Marine Engineering and Technology
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• v.33 no.5
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• pp.729-737
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• 2009

This paper introduces the machine tools feed system, which can be optimized the control's performance through simulation and the adjustment of the mechanical components. One method simulates the frequency response of the speed-loop with the design value using the MATLAB application, so that all of the interpolation axis can be equal to the response bandwidth, resulting in a high accuracy rate. The other method sees the mechanical component being adjusted by analyzing the results of various experiments. Lastly, this client's program is able to change the parameters that are related to the FFD, as well as the parameters in the friction compensation of the OPEN-CNC.

• Journal of Power Electronics
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• v.4 no.4
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• pp.217-227
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• 2004

A robust controller that combines the merits of the feed-back, feed-forward and model-following control for induction motor drives utilizing field orientation control is designed in this paper. The proposed controller is a two-degrees-of­freedom (2DOF) integral plus proportional & rate feedback (I-PD) speed controller combined with a model-following (2DOF I-PD MFC) speed controller. A systematic mathematical procedure is derived to find the parameters of the 2DOF I-PD MFC speed controller according to certain specifications for the drive system. Initially, we start with the I-PD feed­back controller design, then we add the feed-forward controller. These two controllers combine to form the 2DOF I-PD speed controller. To realize high dynamic performance for disturbance rejection and set point tracking characterisitics, a MFC controller is designed and added to the 2DOF I-PD controller. This combination is called a 2DOF I-PD MFC speed controller. We then study the effect of the 2DOF I-PD MFC speed controller on the performance of the drive system under different operating conditions. A computer simulation is also run to demonstrate the effectiveness of the proposed controller. The results verify that the proposed 2DOF I-PD MFC controller is more accurate and more reliable in the presence of load disturbance and motor parameter variations than a 2DOF I-PD controller without a MFC. Also, the proposed controller grants rapid and accurate responses to the reference model, regardless of whether a load disturbance is imposed or the induction machine parameters vary.

• Journal of the Korea Society of Computer and Information
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• v.5 no.4
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• pp.112-119
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• 2000

In this paper, it aims at two different situation such that a preventive control which means, it never has network information in case of occurring congestion in network, and a reactive control which means, after the congestion simply happens. it is not effective to recover with congestion just because of extensive delay for an electric wave. To solve the problems, threshold is set up with buffer in multiplex system, and executes a congestion control by FBLB which is FeedBack Leaky Bucket Algorithm. As suggested by FBLB Algorithm. the outcome of performance could be compared with Buffered Leaky Bucket Algorithm.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2000.10a
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• pp.79-83
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• 2000

A sliding mode fuzzy control (SMFC) with disturbance estimator is applied to design a controller for the third generation benchmark problem on an wind-excited building. A distinctive feature in vibration control of large civil infrastructure is the existence of large disturbances, such as wind, earthquake, and sea wave forces. Those disturbances govern the behavior of the structure, however, they cannot be precisely measured, especially for the case of wind-induced vibration control. Since the structural accelerations are measured only at a limited number of locations without the measurement of the wind forces, the structure of the conventional control may have the feed-back loop only. General structure of the SMFC is composed of a compensation part and a convergent part. The compensation part prevents the system diverge, and the convergent part makes the system converge to the sliding surface. The compensation part uses not only the structural response measurement but also the disturbance measurement, so the SMFC has a feed-back loop and a feed-forward loop. To realize the virtual feed-forward loop for the wind-induced vibration control, disturbance estimation filter is introduced. the structure of the filter is constructed based on an auto regressive model for the stochastic wind force. This filter estimates the wind force at each time instance based on the measured structural responses and the stochastic information of the wind force. For the verification of the proposed algorithm, a numerical simulation is carried out on the benchmark problem of a wind-excited building. The results indicate that the present control algorithm is very efficient for reducing the wind-induced vibration and that the performance indices improve as the filter for wind force estimation is employed.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.05a
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• pp.991-995
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• 2002

The engine booming noise heard inside a vehicle's cabin is due to the engine vibration that's transferred to the chassis in the form of structural vibration and it often causes discomfort to the passenger. In an effort to seek out the possible relation between the engine booming noise and the engine vibration of a vehicle, a position on the engine mount was selected and the vibration transmission through the position was attenuated to observe the corresponding change in the noise level inside the cabin. A system consisting of an actuator and a hybrid controller that has both the feed-forward and feed-back capabilities was developed in order to carry out the experiment.

• International Journal of Naval Architecture and Ocean Engineering
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• v.12 no.1
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• pp.768-783
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• 2020

Typically, a Dynamic Positioning System (DPS) uses a PID feed-back system, and it often adopts a wind feed-forward system because of its easier implementation than a feed-forward system based on current or wave. But, because a ship's drifting motion is caused by wind, current, and wave drift loads, all three environmental loads should be considered. In this study, a motion predictive control for the PID feedback system of the DPS is proposed, which considers the three environmental loads by utilizing predicted drifted ship positions in the future since it contains information about the three environmental loads from the moment to the future. The prediction accuracy for the future drifted ship position is ensured by adopting deep learning algorithms and a replay buffer. Finally, it is shown that the proposed motion predictive system results in better station-keeping performance than the wind feed-forward system.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.14 no.2
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• pp.136-144
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• 2014

The existing conventional motion controller does not perform well in the presence of nonlinear properties, uncertain factors, and servo lag phenomena of industrial actuators. Hence, a feasible and effective fuzzy self-tuning proportional integral derivative (PID) and feed-forward control scheme is introduced to overcome these problems. In this design, a fuzzy tuner is used to tune the PID parameters resulting in the rejection of the disturbance, which achieves better performance. Then, both velocity and acceleration feed-forward units are added to considerably reduce the tracking error due to servo lag. To verify the capability and effectiveness of the proposed control scheme, the hardware configuration includes digital signal processing (DSP) which plays the main role, dual-port RAM (DPRAM) to guarantee rapid and reliable communication with the host, field-programmable gate array (FPGA) to handle the task of the address decoder and receive the feed-back encoder signal, and several peripheral logic circuits. The results from the experiments show that the proposed motion controller has a smooth profile, with high tracking precision and real-time performance, which are applicable in various manufacturing fields.

• Asian-Australasian Journal of Animal Sciences
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• v.21 no.12
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• pp.1785-1793
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• 2008

Fifty-four PIC barrows were used to evaluate the effects of lower dietary lysine content and energy level on carcass characteristics and meat quality in slaughter pigs. Pigs were allotted to one of three treatments by body weight with six replicate pens in each treatment. The dietary treatments for body weights of 20-50 kg, 50-80 kg and 80-90 kg were as follows, respectively: control diet (digestible energy 14.22 MJ/kg, lysine/DE 0.67 g/MJ, 0.53 g/MJ and 0.42 g/MJ); a low lysine group (digestible energy 14.22 MJ/kg, lysine/DE 0.49, 0.38 and 0.30 g/MJ); and a low lysine-low energy group or low nutrient group (digestible energy 13.11 MJ/kg, lysine/DE 0.49, 0.38 and 0.30 g/MJ). The daily weight gain, daily feed intake and feed efficiency were calculated in the overall growth period (nearly 12 weeks). Meanwhile, carcass characteristics and meat quality were evaluated at 60 and 90 kg body weight respectively. During the overall growth trial, lowering dietary lysine and nutrient level both decreased weight gain (p<0.05) and feed efficiency (p<0.01). At 60 kg body weight, decreasing dietary lysine and nutrient level noticeably decreased dressing percentage (p<0.01) and back fat depth at last rib of PIC pigs (p<0.01), but enhanced marbling scores (p<0.10), intramuscular fat content (p<0.10) and water loss rate (p<0.01) of the longissimus dorsi muscle. At 90 kg body weight, lean percentage (p<0.01) was evidently reduced by both lowering lysine content and nutrient level in the diet. However, the shoulder back fat depth (p<0.05) and marbling scores of the loin eye muscle (p<0.05) were increased; Lowering dietary nutrient level could improve back fat depth of 10th rib (p<0.01) and last rib (p<0.01), intramuscular fat content (p<0.10), redness (p<0.01) and water loss rate of the loin eye muscle (p<0.05), but decrease loin area (p<0.05). Finally, when comparing the 60 kg and 90 kg slaughter weights, it was found that the shoulder back fat depth (p<0.01, p<0.10), 6th-7th rib (p<0.01, p<0.01), 10th-rib (p<0.01, p<0.01) and last rib back fat depth (p<0.01, p<0.01) of the low lysine and low nutrient group were all obviously increased comparing with the control group. Taken together, the results showed that decreasing dietary lysine content and nutrient level increased intramuscular fat content and water loss rate of longissimus dorsi muscle; On the other hand, both lowering dietary lysine and nutrient level markedly compensated to increase back fat deposition in the later finishing period (body weight from 60 to 90 kg) in contrast to the control group.