• Proceedings of the KIEE Conference
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• 1997.07b
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• pp.390-393
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• 1997

Fuzzy logic and neural networks are complemetary technologies in the design of intelligent system. Fuzzy neural network(FNN) as an auto-tuning method is actually known to an excellent method for the adjustment of the fuzzy rule. However, this has a weak point, because the convergence to the optimum depends on the initial condition. In this paper we develop a coding format to determine a FNN model by chromosome in GA and present systematic approach to identify the parameters and structure of FNN. The proposed hybrid tuning method realizes to construct minimal and optimal structure of the fuzzy mode simultaneously and automatically. This paper shows effectiveness of the tuning system by simulations compared with conventional methods.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.23 no.3
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• pp.318-324
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• 2014

Recent years have witnessed a growing demand for a wide variety of high-performance industrial robots. In this paper, for accurate gain tuning of a 6-axis articulated industrial robot with reduced noise, a program routine for a dynamic signal analyzer (DSA) using the frequency response method will be programmed using $LabVIEW^{(R)}$. Then, robot transfer functions can be obtained experimentally using the frequency response method with the DSA program. Data from the robot transfer functions are transformed into Bode plots, based on which an optimal gain tuning will be executed. Gain tuning can enhance the response quality of the output signal for a given input signal during real-time control of the robot. The effectiveness of our proposed technique will be verified by implementation with a (lab-manufactured) 6-axis articulated industrial robot (hereinafter called "RS2") and comparison with the zero position gain tuning, as well as other positions.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.20 no.5
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• pp.589-597
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• 2011

In this paper, optimal tuning of a cross-coupled controller linked with the feedforward controller and the disturbance observer is studied to improve contouring and tracking accuracy as well as robustness against disturbance. Previously developed integrated design and optimal tuning methods are applied for developing the robust tuning method. Strict mathematical modeling of the multivariable system is formulated as a state-space equation. Identification processes of the servomechanism are conducted for mechanical servo models. An optimal tuning problem to minimize both the contour error and settling time is formulated as a nonlinear constrained optimization problem including the relevant controller parameters of the servo control system. Constraints such as relative stability, robust stability and overshoot, etc. are considered for the optimization. To verify the effectiveness of the proposed optimal tuning procedure, linear and circular motion experiments are performed on the xy-table. Experimental results confirm the control performance and robustness despite the variation of parameters of the mechanical subsystems.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1350-1353
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• 1993

A fuzzy control system typically requires“tuning,”or adjuctment of the parameters defining its linguistic variables. Automating this process amounts to applying a second“metacontrol”layer to drive the controller and plant to desired performance levels. Current methods of automated tuning rely on a single crisp numeric functional to evaluate control system performance. A generalization of Box's complex algorithm allows more realistic tuning based on lexicographic aggregation of multiple ordinal scales of performance, such as effectiveness and efficiency. The method is presented and illustrated using a simple inverted pendulum control system.

• Journal of the Korean Institute of Telematics and Electronics
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• v.25 no.9
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• pp.1039-1045
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• 1988

In the original incremental generalized predictive control, the receding horizon predictive control is introduced as a control law. But in this paper, we propose a generalized predictive self-tuning control using full-valued incremental controls. The control law is a mean horizon predictive control. The effectiveness of this algorithm in a variable time delay or load disturbances environment is demonstrated by computer simulation. The controlled plant is a nonminimum phase system.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2648-2650
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• 2000

The PID tuning algorithm which can be applied generally to processes with varies dynamic characteristics is proposed by Wang[7]. However, it can be applied well to process model without zeros and with $\angle$G(jw)=-${\pi}$/2 and -${\pi}$ point in Nyquist curve, but it gives unsatisfactory tuning performance for processes with zeros and without $\angle$G(jW)=-${\pi}$/2 and -${\pi}$ in Nyquist curve. In this paper, the method which improve it using Pade reduction method is proposed. Satisfactory responses can be expected for processes with various dynamics, including those with low or high order, small or large dead time, monotonic or oscillatory responses. Simulation examples are given to show the effectiveness and flexibility of the controller in handling processes of different characteristics.

• Proceedings of the KIPE Conference
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• 2002.11a
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• pp.40-44
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• 2002

In this paper, robust control method using fuzzy PI parameter tuning is proposed to control constant thrust force on load variation. First, a structure and thrust force equations of the LPM are described. Second, an controller with PI parameter-tuning using a fuzzy theory is proposed to achieve high-precision position with constant thrust force of the LPM. Finally, the effectiveness of an fuzzy PI controller is demonstrated by some simulated and experimental results. Accurate tracking response and superior dynamic performance can be obtained due to the powerful on-line Fuzzy PI gain tuning method with regard parametric variations and load thrust force variations.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.213-217
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• 2008

In this paper, a new design method for IMC-PID that adds a phase scaling factor of system identifications to the standard IMC-PID controller as a control parameter is proposed. Based on analytically derived frequency properties such as gain, phase margin and maximum magnitude of sensitivity function, this tuning rule is an optimal control method determining the optimum values of controlling factors to minimize the cost function, integral error criterion of the step response in time domain, in the constraints of design parameters to guarantee qualified frequency design specifications. The proposed controller improves existing single-parameter design methods of IMC-PID in the inflexibility problem to be able to consider various design specifications. Its effectiveness is examined by a simulation example, where a comparison of the performances obtained with the proposed tuning rule and with other common tuning rules is shown.

• Journal of Advanced Marine Engineering and Technology
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• v.27 no.1
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• pp.24-32
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• 2003

The PID controller has been widely used in industrial applications due to its simple structure and robustness. Even if it is initially well tuned, the PID controller must be retuned to maintain acceptable performance when there are system parameter changes due to the change of operation conditions. In this paper, a self-tuning control scheme which comprises a parameter estimator, a NN-based rule emulator and a PID controller is proposed, which can cope with changing environments. This method involves combining neural networks and real-coded genetic algorithms(RCGAs) with conventional approaches to provide a stable and satisfactory response. A RCGA-based parameter estimation method is first described to obtain the first-order with time delay model from over-damped high-order systems. Then, a set of optimum PID parameters are calculated based on the estimated model such that they cover the entire spectrum of system operations and an optimum tuning rule is trained with a BP-based neural network. A set of simulation works on systems with time delay are carried out to demonstrate the effectiveness of the proposed method.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.44 no.1
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• pp.19-24
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• 2007

In this paper, we propose a tuning method of PID-PD controller to satisfy design specifications in frequency domain as well as time domain. The proposed tuning method of PID-PD controller consists of the convex set of PID and PI-PD controller. PID-PD controller controls the closed-loop response to be located between the step responses, and Bode magnitudes of closed-loop transfer functions controlled by PID and PI-PD controller. The controller is designed by the optimum tuning method to minimize the proposed specific cost function subject to sensor noise insensitivity and robust stability. Its effectiveness is examined by the case study and analysis.