• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.13 no.2
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• pp.195-195
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• 1999

This paper is Proposed a new method to deal with the optimized auto-tuning for the PID 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-Nickels method. So we can find the parameters of PID 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 PID controller by Backpropagation of Neural-Network, when we give new K, L, T values to Neural-Network, the optimized parameter of PID controller is found by Neural-Network Program.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1110-1112
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• 1996

In this paper, we propose a new approach for robust auto-tuning of PID gains using Evolution Strategy. Evolution Strategy is searching algorithm which imitate the principles of natural evolution as a method to solve parameter optimization problem and easy to use without any other special mathematical theory. Through the simulation of the speed control of a series-connected de motor, our proposed method shows more improved performance by finding optimal parameters of PID controller than a classical Ziegler-Nichols method.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2000.08a
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• pp.109-112
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• 2000

We propose a new method to deal with the optimized auto-tuning for the PID 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. After inputting constraints of evolution programs, we perform crossover and mutation to generate the descendant generation. The advantage of this method is better than the Ziegler-Nickels method in characteristic of output and has extent of applying without limit of K, L, T.

• Journal of the Korean Institute of Telematics and Electronics T
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• v.36T no.1
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• pp.41-50
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• 1999

The brushless DC motor is widely being used in unmanned factories for its easy maintenance and characteristics of controllability. In this paper, we designed a speed control servo system of a sinusoidal type bmshless DC motor which has high efficiency and usefulness in the industrial fields. This servo system is realized by a controller which is required for driving motors and a new auto-tuning PI control algorithm. The DSP(Digita1 Signal Processor) is adopted as a main controller and a sensor signal processor owing to its fast computational capability and suitable architecture. Also, the hardware PWnl(Pulse Width Modulation) current controller is implemented to pursue a speed command exactly. By experimental results, it is verified that the speed response is pursued fast after command value and the steady-state response is well converged for command value variation without overshoots.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.1 s.173
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• pp.7-15
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• 2000

This paper suggests an auto-tuning I'll) control algorithm that uses the advantage of PID controller and improves the system performance. The PID gains being designed by th- conventional method are tuned through the plant parameter estimation. The Extended Kalman Filter is used for the estimation. It works as an observer and noise filter. Moreover, as the plant state and the uncertain parameter could be estimated simultaneously, the proposed algorithm is very useful in the tracking control of a system with uncertain parameter. The auto-tuning I'll) controller could maintain the system performance in the case that the plant parameters are uncertain or varying. The proposed control algorithm requires a correct estimation of the plant parameter. The controller stability and the performance is considered through the stability criteria and a servo motor model. The Kalman filter estimates the most sensitive plant parameter, which is determined by the sensitivity analysis.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.16 no.11
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• pp.1068-1076
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• 2004

Technology on the proportional integral (PI) control have grown rapidly owing to the needs for the robust capacity of the controllers from industrial building sectors. However, PI controller requires tuning of gains for optimal control when the outside weather condition changes. The present study presents the possibility of reinforcement learning (RL) control algorithm with PI controller adapted in the HVAC system. The optimal design criteria of RL controller was proposed in the Environment Chamber experiment and a theoretical analysis was also conducted using TRNSYS program.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.51-56
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• 1998

In this paper, we analyze the effects of scaling factors on the performance of a fuzzy logic controller(FLC). The quantitative relation between input and output variables of FLC is obtained by using a qualsi-linear fuzzy model, and an approximate transfer function of FLC is dervied from the comparison of it with the conventional PID controller. Then we analyze in detail the effects of scaling factor using this approximate transfer function and root locus method. Also we suggest an on-line tuning method for scaling factors which employs an sample performance function and a variable reference for tuning index.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 1998.10a
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• pp.153-158
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• 1998

In this paper, we present a design of optimal 2-DOF PID controller for control of gantry crane which has to control swing motion and trolley position. For tuning the parameter of 2-DOF PID controller, we used evolution strategy(ES). During operate the crane system in yard, the goal is transporting the load to a goal position as quick as possible without rope oscillation. The crane is generally operated by an expert operator, but recently an automatic control system with high speed and rapid transportation is required. However, we developed an optimal controller which has to control the crane system with disturbance.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.83-86
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• 1995

This paper proposes an auto-tuning method of feedforward signal in boiler control of thermal power plants by using the neural network. The neural network produces an optimal feedforward signal by tuning the weights of the network. The weights are adapted effectively by using the teaching signal of PI control output. The proposed method was evaluated based on a detailed simulator which expressed non-linear characteristics of the 600 MW actual thermal power plant at load chaning operations, showed effectiveness in the learning of the weights of the neural network, and gave an accurate control performance in the temperature control of the system. Through the evaluation, the proposed method was proved to be effectively applicable to the actual thermal plants as the automatic adjustment tool.

• Proceedings of the KIEE Conference
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• 2002.11c
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• pp.110-113
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• 2002

This paper propose a method for the temperature control using cool-plate in the track equipment. The employed control algorithm is PID control algorithm. The control gains are found using relay auto-tuning algorithm. After that the gains are adjusted manually in trial and error. The control hardware circuit is designed and implemented in the lab. The controlled temperature reached the desired value Within $\pm0.05^{\circ}C$ accuracy.