• Journal of Advanced Navigation Technology
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• v.13 no.6
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• pp.813-819
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• 2009

Designing actuator controllers of aircraft, which control aileron, flap, elevator and so on, is quiet difficult, because they have time variant nonlinear mechanical structures and also have many kinds of disturbances which are not been able to model easily. This paper reports about the performance of Fuzzy Auto gain tuning Control algorithm applied unmaned aerial vehicle. Fuzzy Auto gain tuning PID control uses PID control and Fuzzy control, therefore It can be applied very easily and it also has advances of PID control. It can control a unmaned aerial vehicle actuators adaptively even though the designer does not have enough information of plant.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2002.04a
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• pp.621-624
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• 2002

The purpose of this paper is a study on getting proper gain set of PID controller which satisfies multi-performance specifications of the control system. The multi-objective optimization method is introduced to evaluate specifications, and the genetic algorithm is used as an optimal problem solver. To enhance the performance of genetic algorithm itself, adaptive technique is included. According to the proposed method in this paper, finding suitable gain set can be more easily accomplishable than manual gain seeking and tuning.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.117-120
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• 2003

A method for PID controller tuning based on process models for unstable processes was introduced. The optimal. proportional and derivative gains of the AMBs were determined by the tuning method and utilized for the chatter stability analysis in order to search for the chatter-free cutting region. The stability analysis results showed that the optimal gains give wider chatter-free cutting region, and as a result the proposed tuning method was confirmed to be an effective tuning method for determining the optimal gains of the AMBs.

• Proceedings of the KIEE Conference
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• 2002.07b
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• pp.1137-1139
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• 2002

In this paper, recurrent artificial neural network (RNN) based self tuning speed controller is proposed for the high performance drives of induction motor. RNN provides a nonlinear modeling of motor drive system and could give the information of the load variation, system noise and parameter variation of induction motor to the controller through the on-line estimated weights of corresponding RNN. Thus, proposed self tuning controller can change gains of the controller according to system conditions. The gain is composed with the weights of RNN. For the on-line estimation of the weights of RNN, extended kalman filter (EKF) algorithm is used. Self tuning controller that is adequate for the speed control of induction motor is designed. The availability of the proposed controller is verified through the MATLAB simulation with the comparison of conventional PI controller.

• The Transactions of the Korean Institute of Power Electronics
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• v.9 no.6
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• pp.602-611
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• 2004

Servo system has commonly adapted PI controller with fixed gains, because of its simplicity and determinative relationship among the parameters. The fixed gains PI system may be applied well to some operation conditions, but not non-linearities, complex and time variant operation conditions. For solving these problems, another conventional method, 'variable gun schedule according to speed', is published. The value of gain is determined according to the absolute value of the mover real speed. In this paper, FSTPIC(Fuzzy Self-Tuning PI Controller) is proposed based on various experiences to rapidly reduce speed error and to secure a good speed response characteristics. The effectiveness of proposed algorithms is demonstrated by comparing to two conventional gain systems via 4-quadrant operation.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.3
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• pp.76-85
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• 1998

In this paper, a fuzzy tuning method of a control gain in the discrete-time repetitive controller is proposed for precise tracking control of a system whose reference signal is repetitive. The control gain is modified by fuzzy rules which use the magnitude and the variation ofthe maximum output error in the previous repetitive period. The proposed method is applied to a direct drive 2-axis SCARA-type robot and, it is illustratedby computer simulations and real-time experimentation that better performance can be obtained that the fixed gain-based repetitive controller.

• 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.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.6
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• pp.25-35
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• 1999

This paper presents a control gain tuning scheme for multi-axis PID control systems by Taguchi method. As an experimental set-up, a parallel mechanism machine tool has been selected. This machine has eight servodrives and each servodrive has four control gains, respectively. Therefore, total 32 control gains have to be tuned. Through a series of design of experiments, an optimal and robust set of PID control gains is tuned. The index of the sum of position error and velocity error is reduced to 61.4% after the experimental gain tuning regardless of the feedrate variation.

• Journal of the Korea Convergence Society
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• v.4 no.4
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• pp.31-40
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• 2013

PID auto-tuning controller was designed via fuzzy logic. Typical values such as error and error derivative feedbackwere changed as heuristic expressions, and they determine PID gain through fuzzy logic and defuzzification process. Fuzzy procedure and PID controller design were considered separately, and they are combined and analyzed. Obtained auto-tuning PID controller by Fuzzy Logic showed the ability for less than 3rd order plant control.

• Journal of Drive and Control
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• v.13 no.3
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• pp.15-23
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• 2016

The direct-drive servo valve(DDV) is a kind of one-stage valve because the main spool valve is directly driven by the dc motor. Since the DDV structure is simple, it is less expensive, more reliable, and offers a reduced internal leakage and a reduced sensitivity to fluid contamination. The control system of the DDV is highly nonlinear due to a current limiter, a voltage limiter, and the flow-force effect on the spool motion. The shape of the step response of the DDV-control system varies considerably according to the magnitudes of the step input and the load pressure. The system-design requirements mean that the overshoots should be less than 20%, and the errors at 0.02s should be less than 2%, regardless of the reference-step input sizes of 1V and 5V and the load-pressure magnitudes of 0MPa and 20.7MPa. To satisfy the system-design requirements, the PID-controller parameters of $K_c$, $T_i$ and $T_d$, and the derivative-feedback gain of $K_{der}$ are designed using the root locus and manual tuning.