• Journal of Institute of Control, Robotics and Systems
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• v.7 no.7
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• pp.574-581
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• 2001

In this paper we design and evaluate the longitudinal nonlinear N(aub)z-CSAS(Command and Stability Augmentation System) flight control law in \"DMI(Dynamic Model Inversion)-method\" and classical \"Gain Scheduling-method\", respectively, to meet the handling quality requirements associated with push-over pull-up maneuver. It is told that the flight control law designed in \"DM-method\" is adequate to the full flight regime without gain scheduling and is efficient to produce the time response shape desired to the handling quality requirements. On the contrary, the flight control law designed in \"Gain Scheduling-method\" is easy to be implemented in flight control computer and insensitive to variation of the actuator model characteristics.n of the actuator model characteristics.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.10a
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• pp.744-747
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• 2005

This research studied 6-Axes Articulated Robot Manipulator's gain Tuning in consideration of dynamic. First of all, search fur proportional gain of velocity control loop by dynamic signal analyzer. Proportional gain of velocity control loop is connected to dynamic signal analyzer. Next Select free Proportional Gain value. And Select amplitude X of sinusoidal properly so that enough Velocity Feedback Signal may be paid as there is no group to utensil department. Next step, We can get Bode Diagram of Closed loop transfer function response examination in interested frequency. Integral calculus for gain of velocity loop is depended on integral calculus correction's number. We can obtain open loop transfer function by integrator. And we can know bode diagram's special quality from calculated open loop transfer function. With this, Velocity Control Loop's Parameter as inner loop is controlled. Next In moving, when vibration occurs, it controls notch filter. And finally, we have to control fred-forward filter parameter for elevation of control performance.

• Journal of the Korean Institute of Telematics and Electronics D
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• v.34D no.2
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• pp.10-20
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• 1997

This paper describes the design, the manufacture and the development of th eautomatic gain control unit which ajdusts the gain of IF processor in the high sensitive & multifunctional receiver unit (HMR) for pulse doppler radar system. Accodording to the effective distnce of target, radar cross section, and a lot of external environments (such as clutter), the receiving stage of RADAR system often deviates from dynamic range. To solve this kind o fproblem, continuous/pulse wave AGC are realized, make it possible to control the gain characteristics of receiver stably, and can increase dynamic range linearly by adjusting the gain slope of receiver which is limited by 1-dB gain compression point. In this study, AGC unit is designed to regulate the total gain of receiver by using te analog feedback theory. It also has rapid enough response to process pulse signal. This study presents the gain control method of IF, the real manufacture technique (the package-type components) and the measurement performance of AGC.

• Journal of the Ergonomics Society of Korea
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• v.26 no.4
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• pp.9-16
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• 2007

Input devices of wearable computer are difficult to use, so a lot of alternative pointing devices have been considered in recent years. In order to resolve this problem, this paper proposed a dynamic gain control method which is able to improve the performance of wearable pointing device and showed an experimental result comparing this method with conventional method. Also the effects of methods were compared in terms of device (wearable and desktop). The result of calculating throughputs(index of performance) by Fitts' law showed that the pointing performance in dynamic gain condition was improved 1.4 times more than normal gain.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.280-285
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• 1991

Neural network control has many innovative potentials for fast, accurate and intelligent adaptive control. In this paper, a learning control architecture for the dynamic control of a robot manipulator is developed using inverse dynamic neurocontroller and linear neurocontroher. The inverse dynamic neurocontrouer consists of a MLP (multi-layer perceptron) and the linear neurocontroller consists of SLPs (single layer perceptron). Compared with the previous type of neurocontroller which is using an inverse dynamic neurocontroller and a fixed PD gain controller, proposed architecture shows the superior performance over the previous type of neurocontroller because linear neurocontroller can adapt its gain according to the applied task. This superior performance is tested and verified through the control of PUMA 560. Without any knowledge on the dynamic model, its parameters of a robot , (The robot is treated as a complete black box), the neurocontroller, through practice, gradually and implicitly learns the robot's dynamic properties which is essential for fast and accurate control.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.5
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• pp.831-835
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• 2016

In this paper, a dual-channel feed-forward transimpedance(TIA) array is realized in a standard $0.18-{\mu}m$ CMOS technology which exploits automatic gain control function to provide 40-dB input dynamic range for either detecting targets nearby or sensing imminent danger situations. Compared to the previously reported conventional feed-forward TIA, the proposed automatic-gain-control feed-forward TIA(AFF-TIA) extends the input dynamic range 25 dB wider by employing a 4-level automatic gain control circuit. Measured results demonstrate the linearly varying transimpedance gain of 47 to $72dB{\Omega}$, input dynamic range of 1:100, the bandwidth of $${\geq_-}670MHz$$, the equivalent input referred noise current spectral density of 6.9 pA/${\surd}$HZ, the maximum sensitivity of -26.8 dBm for $10^{-12}BER$, and the power consumption of 27.6 mW from a single 1.8-V supply. The dual-channel chip occupies the area of $1.0{\times}0.73mm^2$ including I/O pads.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.29B no.8
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• pp.15-23
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• 1992

Neural network control has many innovative potentials for fast, accurate and intelligent adaptive control. In this paper, two kinds of neurocontrol architectures for the dynamic control of robot manipulators are developed. One is based on a System Identification and Control scheme and the other is based on the Feedback-Error leaming scheme. Both of the proposed architectures use an inverse dynamic neurocontroller in parallel with a linear neurocontroller. The difference is that the first architecture uses the system identifier to get the signals used for training neurocontrollers, while the second architecture uses a properly defined energy function. Compared with the previous types of neurocontrollers which are using an inverse dynamic neurocontroller and a fixed PD gain controller, the proposed architectures not only eliminate the painful process of the fixed gain tuning but also exhibit superior peformances because the linear neurocontroller can adapt its gains according to the applied task. This superior performance is tested and verified through computer simulation of the dynamic control of the PUMA 560 arm.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.1722-1723
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• 2008

This paper present dynamic stiffness of servo motor using labVIEW PXI module. In speed control loop, we apply proportional gain and integral gain, using PID controller, respectively in servo motor and confirmed dynamic stiffness of servo motor varing each gain. Changing proportional gain and integral gain, confirm what effect in dynamic stiffness are change in frequency response..

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.3A
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• pp.356-359
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• 2006

A monolithic SiGe HBT variable gain driver amplifier(VGDA) with high dB-linear gain control and high linearity has been developed as a driver amplifier with ground-shielded microstrip lines for 5-GHz transmitters. The VGDA consists of three blocks such as the cascode gain-control stage, fixed-gain output stage, and voltage control block. The circuit elements were optimized by using the Agilent Technologies' ADSs. The VGDA was implemented in STMicroelectronics' 0.35${\mu}m$ Si-BiCMOS process. The VGDA exhibits a dynamic gain control range of 34 dB with the control voltage range from 0 to 2.3 V in 5.15-5.35 GHz band. At 5.15 GHz, maximum gain and attenuation are 10.5 dB and -23.6 dB, respectively. The amplifier also produces a 1-dB gain-compression output power of -3 dBm and output third-order intercept point of 7.5 dBm. Input/output voltage standing wave ratios of the VGDA keep low and constant despite change in the gain-control voltage.

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.1140-1145
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• 1989

A general dynamic iterative learning control scheme is proposed for a class of nonlinear systems. Relying on stabilizing high-gain feedback loop, it is possible to show the existence of Cauchy sequence of feedforward control input error with iteration numbers, which results in a uniform convergance of system state trajectory to the desired one.