• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.13 no.2
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• pp.63-70
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• 1999

This paper is proposed a new method to deal with the optimized auto-tuning for the Pill controller which is used to the process-control in various fields. First of all, in this method, 1st order delay system with dead time which is modelled from the unit step response of the system is Pade-approximated, then initial values are determined by the Ziegler-Nichols method. So we can find the parameters of Pill controller so as to minimize the fuzzy criterion function which includes the maximum overshoot, damping ratio, rising time and settling time. Finally, after studying the parameters of Pill controller by Backpropagation of Neural-Network, when we give new K, L, T values to Neural-Network, the optimized parameter of Pill controller is found by Neural-Network Program.rogram.

• 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 the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.12 no.3
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• pp.7-13
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• 1998

In this paper, the control technique that ID controller are autotuned according to system dynamics, driving out sample in the changeable limits of system dynamics and learning neural network, is presented. In order to lean neural network, the backpropagation learning algorithm is used and the controller parameters obtained by rule-base are used as teacher's values. When load changes, the auto-tuning of PID controller proper to system dynamics is conformed by simulation.

• Proceedings of the KIEE Conference
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• 2002.11c
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• pp.83-86
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• 2002

This paper presents an implementation of Pill controller for DC-DC converter using the microcontroller. The features of the microcontroller such as the on chip ADC and Pulse width Modulator (PWM) eliminate the external components needed to perform these functions. The duty rate cycle for the DC-DC converter can be updated every time when the (ADC) conversation and the calculation time are finished. The stable response can be obtained for any kind of DC-DC converters. The SMPS controller looks at the converter output, compares the output to a set point, performs a control algorithm (Pill algorithm) and finally applies the algorithm output to the PWM. PWM output is then used to drive the DC-DC converter. Figure (1) shows a simplified block diagram of a complete DC-DC converter system.

• Journal of the Korean Society for Precision Engineering
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• v.25 no.9
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• pp.45-52
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• 2008

As multiple functions arc required in a robot controller, RTOS(Real Time Operating System) should be adopted to manage complex situations, such as choosing most urgent task among competing ones. In this paper, we implemented RTAI(Real Time Application Interface) based robot controller for wafer handling robots including graphic simulator. We showed how multiple tasks are organized and also explained in detail about task priorities and execution periods. Finally, we presented simulation results.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.14 no.1
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• pp.30-37
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• 2000

We studied on acquiring of transfer function and tuning of 2-DOF PID controller using ANFIS for the optimum control to turbine's variables variety. Since the shape of a membership function in the ANFIS based on the characteristics of plant. ANFIS based control method is effective for plant that its variable vary. On the other hand, a start-up time is very short and its variable's value for optimal start-up in gas turbine should be varied, but it is very difficult for such a controller to design. In this paper, we tune 2-DOF PID controller after apply a ANFIS to the operating data of Gun-san gas turbine and verify the characteristics. Its results is compared to the conventional PID controller and discuss. We expect this method will be used for another process because it is studied on the real operating data.

• Proceedings of the KIEE Conference
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• 2001.07b
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• pp.1147-1150
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• 2001

This paper represents a realization of a fuzzy PI control method for a speed control of BLDC motor. In other words, the gains of the PI controller is tuned by a fuzzy logic controller. Simplified reasoning methods are used for fuzzy reasoning. Fuzzy logic speed controller is designed by using the high performance of DSPchip(TMS320F240). By experiment, it is confirmed that the speed of BLDC motor well follows an command speed in the load variables or speed variables.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.9
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• pp.1676-1679
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• 2007

In control of the time delay systems, if the disturbance information can be estimated exactly, the ideal response for the disturbance can be achieved. Therefore, in this paper, a new adaptive disturbance observer for the time delay system control is proposed. The disturbance observer is designed and adaptive laws for adjusting the observer are proposed. The new Smith predictor controller to eliminate the effects of the disturbance can be achieved by adding an estimated disturbance to the Smith model. The improved performances of the proposed system and the adaptive disturbance observer are verified by computer simulation.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.1
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• pp.187-192
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• 2009

This paper presents a method for designing a robust controller that alleviates disturbance effects and compensates performance degradation owing to the time-delay. Disturbance observer(DOB) approach as a tool of robust control has been widely employed in industry. However, since the Pade approximation of time-delay makes the plant non-minimum phase, the classical DOB cannot be applied directly to the system with time-delay. By using a new DOB structure for non-minimum phase systems together with the Smith Predictor, we propose a new controller for reducing the both effects of disturbance and time-delay. Moreover, the closed-loop system can be made robust against uncertain time-delay with the help of a Pill controller tuning method that is based on a second-order plus dead time modeling technique.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.2
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• pp.215-221
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• 2006

This paper is concerned with the control of multiple nonlinearities included in a humanoid robot system. A humanoid robot has some problems such as the structural instability, which leads to consider the control of multiple nonlinearities caused by driver parts as well as gear reducer. Saturation and backlash are typical examples of nonlinearities in the system. The conventional algorithms of backlash control were fuzzy algorithm, disturbance observer and neural network, etc. However, it is not easy to control the system by employing only single algorithm since the system usually includes multiple nonlinearities. In this paper, a switching Pill is considered for a control of saturation and a dual feedback algorithm is proposed for a backlash control. To implement the above algorithms, the system identification is firstly performed for the minimization of the difference between the results of simulation and experiment, and then the switching Pill gains are determined using genetic algorithm with some heuristic approach. The performance of the switching Pill controller for saturation and the dual feedback for backlash control is investigated through the simulation. Finally, it is shown that the implemented control system has good results and can be applied to the real humanoid robot system ISHURO.