• Proceedings of the Korean Society of Precision Engineering Conference
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• 2009.10a
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• pp.339-340
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• 2009

• Proceedings of the KIPE Conference
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• 2003.07b
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• pp.994-997
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• 2003

Simple tuning formulae are derived to design a Pl controller to meet the gain and phase margin specifications. These formulae are suitable for the auto-tuning of a process where the robustness should be guaranteed. The auto-tuned PI controller is examined for the speed regulation of a PM synchronous motor.

• Transactions of the Korean Society of Mechanical Engineers
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• v.17 no.9
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• pp.2153-2161
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• 1993

Self-tuning control algorithms for an input-amplitude constrained system are developed and implemented. Magnitude of control input for small motors is generally restricted to narrow bound due to actuator saturation. The gain-adjusted control algorithm and the bounded-gain control algorithm proposed in this study yield smoother control input variations within the magnitude constraints comparing with the existing Clarke's suboptimal control algorithm. In the gain-adjusted control algorithm, the feedforward gain is adjusted using maximum gain, while in the bounded-gain control algorithm, the feedforward gain is bounded using weighting factor. For the DC servo motor control, the system performances of the proposed algorithms are compared with those of the existing algorithm by computer simulation and experiment. It is shown that the input variations of the proposed algorithms are smoother as compared with the existing algorithm.

• The Journal of Korea Robotics Society
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• v.2 no.1
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• pp.1-8
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• 2007

This paper presents a PID automatic gain-tuning algorithm for the electronic throttle valve which is driven by wire. Since the system characteristics of position control for electronic throttle valve are so complicated that both the real time robustness and the manufacturing cost must be considered for mass production. To resolve this paradox, a kind of algorithm called RLS (Recursive Least Square) is adopted for the control of the ETB (Electronic Throttle Body). Using this algorithm, the PID gains can be adjusted automatically with the estimated system parameters. Furthermore, a pre-filter is supplemented for the sake of the robustness against the friction and loads. From the industrial requests for the system, the design specifications are decided as follows: the settling time should be less than 1sec and the overshoot should be kept below 3%. The results of the experiments based on this approach show that the high robustness can be achieved while the system stability is satisfied steadily. A parameter estimation scheme and a gain-tuning algorithm have been properly combined and utilized in this research and the effectiveness is verified through the real experiments.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.3
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• pp.199-207
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• 2002

In this paper, a self-tuning gain-scheduled skyhook control for semi-active suspension systems is investigated. The dynamic characteristics of a continuously variable damper including electro-hydraulic pressure control valves is analyzed. A 2-d.o.f. time-varying quarter-car model that permits variations in sprung mass and suspension spring coefficient is considered. The self-tuning skyhook control algorithm proposed in this paper requires only the measurement of body acceleration. The absolute velocity of the sprung mass and the relative velocity of the suspension deflection are estimated by using integral filters. The skyhook gains are gain-scheduled in such a way that the body acceleration and the dynamic tire force are optimized. An ECU prototype is discussed. Experimental results using a 1/4-ear simulator are discussed. Also, a suspension ECU prototype targeting real implementation is provided.

• Proceedings of the KIEE Conference
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• 1998.07b
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• pp.541-543
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• 1998

Generally, PI control is simple and easy to implement and gains of PI control are determined by specifying a dynamics of the servo driver system. However, the gain-tuning is so difficult that it is relied on an expert's effort. This paper presents a gain auto-tuning method for PI controllers based on a fuzzy inference mechanism. First, the proposed fuzzy inference system identifies a system moment of inertia and adjusts control gains by using the difference in speed responses between a real plant and a reference model. Second, this paper proposes an improved fuzzy PI controller. To reduce the speed overshoot, we adapt a control method that selects a proper PI gains with respect to the load inertia variation. To prove the validity of the proposed gain tuning algorithm and the feasibility of the servo drive, a high performance servo drive will be implemented by DSP(TMS320C31) and intelligent power module (IPM). The proposed controller is applied to the speed control of the 300W AC servo motor. Some simulations and experimental results show that the proposed fuzzy PI controller is more robust than the conventional PI controller against the load inertia variation.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.2
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• pp.55-61
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• 2000

In this paper, we proposed a new PID tuning algorithm by the fuzzy set theory to improve the performance of the PID controller. The new tuning algorithm for the PID controller has the initial value of parameter Kc, $\tau$I, $\tau$D by the Ziegler-Nichols formula using the ultimate gain and ultimate period from a relay tuning experiment. We get error and error change of plant output correspond to the initial value and new proportion gain(Kc) and integral time($\tau$I) from fuzzy tunner. This fuzzy tuning algorithm for PID controller considerably reduced overshoot and rise time compare to any other PID controller tuning algorithms. In real parametric uncertainty systems, the PID controller with Fuzzy auto-tuning give appreciable improvement in the performance. The significant properties of this algorithm is shown by simulation In this paper, we proposed a new PID algorithm by the fuzzy set theory to improve the performance of the PID controller.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1380-1385
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• 2004

In this paper, auto-tuning technique of the PID controller gain by particle swarm optimization algorithm is presented. PID controller is easy to implement to numerous control systems. After PID gain tuning is completed, its result could be implemented to control spacecraft vibration such as jitter that is high frequency vibration usually over 10Hz. The off-line PID controller tuning is done under system nonlinearities and uncertainties existence, then its result is applied to control experiment device to prove the PSO efficiencies.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.3 no.1
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• pp.78-86
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• 2003

Multivariable control system exist widely in many types of systems such as chemical processes, biomedical processes, and the main steam temperature control system of the thermal power plant. Up to the present time, Pill Controllers have been used to operate these systems. However, it is very difficult to achieve an optimal PID gain with no experience, because of the interaction between loops and gain of the Pill controller has to be manually tuned by trial and error. This paper suggests a tuning method of the Pill Controller for the multivariable power plant using an immune algorithm, through computer simulation. Tuning results by immune algorithms based neural network are compared with the results of genetic algorithm.

• Journal of Institute of Control, Robotics and Systems
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• v.3 no.1
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• pp.32-39
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• 1997

One of the most important performance criteria in tuning the gain of position loop controller for CNC machining center is the contour error. In this papre we analyze contour error in the linear and circular interpolations for the axis-matched and mismatched cases. To have small contour errors, it is necessary to set the P gain for each axis to be same. And the D gain should be much smaller than the P gain. Baded on the analysis in the frequency domain, we propose a gain tuning method for the P and PD controllers. We show that the PD controller is better than the P controller. The effectiveness of this method is demonstrated by experiments.