• JSTS:Journal of Semiconductor Technology and Science
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• v.13 no.3
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• pp.198-206
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• 2013

This paper presents a wide band, fine-resolution digitally controlled oscillator (DCO) with an on-chip 3-D solenoid inductor using the 0.13 ${\mu}m$ digital CMOS process. The on-chip solenoid inductor is vertically constructed by using Metal and Via layers with a horizontal scalability. Compared to a spiral inductor, it has the advantage of occupying a small area and this is due to its 3-D structure. To control the frequency of the DCO, active capacitor and active inductor are tuned digitally. To cover the wide tuning range, a three-step coarse tuning scheme is used. In addition, the DCO gain needs to be calibrated digitally to compensate for gain variations. The DCO with solenoid inductor is fabricated in 0.13 ${\mu}m$ process and the die area of the solenoid inductor is 0.013 $mm^2$. The DCO tuning range is about 54 % at 4.1 GHz, and the power consumption is 6.6 mW from a 1.2 V supply voltage. An effective frequency resolution is 0.14 kHz. The measured phase noise of the DCO output at 5.195 GHz is -110.61 dBc/Hz at 1 MHz offset.

• Proceedings of the KIEE Conference
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• 1998.07c
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• pp.1143-1146
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• 1998

Static excitation systems with high gain and fast response times greatly aid transient stability. but at the same time tend to reduce small signal stability. The objective of the power system stabilizer(PSS) control is to provide a positive contribution to damping of the generator rotor angle swings, which are in a broad range of frequencies in the power system. Therefore, this paper shows the field test results for the GE's EX2000 PSS tuning on units at Seo-Incheon power plant. The test is to verify that the PSS response meets GE's design, criteria. The responses of generator terminal voltage, active power, field voltage and current were analyzed and PSS gain was tuned by 10 finally.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10a
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• pp.236-241
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• 1988

This note considers the class of controllers with integral action which arise directly from appropriate system models. Via internal model principle approach, a corresponding class of self-tuning controller is shown to have both integral action in controller and offset removal in the tuning algorithm. The key idea is to constrain the estimator in each step in order to ensure that dc gain of feedforward and feedback polynomial of adaptive controller are always equal, thus allowing the loop integrator to work properly.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.1
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• pp.8-14
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• 2000

In this paper, three adaptive sliding mode control algorithms, which self-tune both the sliding mode gain and the boundary layer thickness, are proposed. The first algorithm uses a gain adaptation rule is combined with the boundary layer thickness adaptatioin rule to satisfy the sliding condition. In the third algorithm, the computation burden of the second algorithm is reduced further, and therefore no extra cost is required for real-time implementation. Due to the mixed sliding mode gain and the boundary layer thickness adaptation scheme, the tracking error and the chattering of the control input can be reduced greatly.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.614-616
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• 2004

It is waste of time in industrial plant that the PI controller gain tuning. The PI controller has many trial-and-error steps for gain design. This paper proposes the optimum gain design of PI controller using a speed estimation in sensorless vector-control. In this method, a degree of stability and Hurwitz theory are applied and the controller gain is expressed by system parameters.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.36 no.7
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• pp.797-803
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• 2012

Proportional solenoid valves are a modulating type that can control the displacement of valves continuously by means of electromagnetic forces proportional to the solenoid coil current. Because the solenoid-type modulating valves have the advantages of fast response and compact design over air-operated or motor-operated valves, they have been gaining acceptance in chemical and power plants to control the flow of fluids such as water, steam, and gas. This paper deals with the auto tuning of the position controller that can provide the proportional and integral gain automatically based on the dynamic system identification. The process characteristics of the solenoid valve are estimated with critical gain and critical period at a stability limit based on implemented relay feedback, and the controller parameters are determined by the classical Ziegler-Nichols design method. The auto-tuning algorithm was verified with experiments, and the effects of the operating point at which the relay control is activated as well as the relay amplitude were investigated.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2001.04a
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• pp.413-417
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• 2001

High speed linear motor feed system has been simulated using neural network technique. Due to the limited resources, control gain tuning has been the most troublesome part in controller design. Regardless of the system structure, conventional control gain could be adjusted minimizing the resulting error using the proposed method. Slight performance deterioration was observed at the small value of training epoch.

• Proceedings of the KIEE Conference
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• 1993.11a
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• pp.299-303
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• 1993

There can be two methods in control systems: one is to use a linear controller, the other is to use a nonlinear controller. The PID controller and the fuzzy controller can be said to belong the linear and the nonlinear controller respectively. In this paper, a new hybrid controller which is consist of the linear PID controller of which the gain is tuned and the nonlinear self tuning fuzzy controller is proposed. In the PID controller, an algorithm which parameterizes the proportional, the intergral, and the derivative gain as a single parameter is used to improve the performance of the PID controller. In the self tuning fuzzy controller, an algorithm which changes the shape of the triangle membership function and changes the scaling factor which is multiplied to the error and the error change. The evaluation of the performance of the suggested algorithm is carried on by the simulation for the Rhino XH-2 robot manipulator with 5 links revolute joints.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.54 no.8
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• pp.395-401
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• 2005

This paper presents Hybrid PI(HBPI) controller of induction motor drive using fuzzy control. In general, PI controllers used in computer numerically controlled machines process fixed gain. They may perform well under some operating conditions, but not all. To increase the robustness of fixed gain PI controller, HBPI controller proposes a new method based self tuning PI controller. HBPI controller is developed to minimize overshoot and settling time following sudden parameter changes such as speed, load torque, inertia, rotor resistance and self inductance. The results on a speed controller of induction motor are presented to show the effectiveness of the proposed gam tuner. And this controller is better than the fixed gains one in terms of robustness, even under great variations of operating conditions and load disturbance.

• Nuclear Engineering and Technology
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• v.50 no.6
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• pp.877-885
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• 2018

Various controllers such as proportional-integral-derivative (PID) controllers have been designed and optimized for load-following issues in nuclear reactors. To achieve high performance, gain tuning is of great importance in PID controllers. In this work, gains of a PID controller are optimized for power-level control of a typical pressurized water reactor using particle swarm optimization (PSO) algorithm. The point kinetic is used as a reactor power model. In PSO, the objective (cost) function defined by decision variables including overshoot, settling time, and stabilization time (stability condition) must be minimized (optimized). Stability condition is guaranteed by Lyapunov synthesis. The simulation results demonstrated good stability and high performance of the closed-loop PSO-PID controller to response power demand.