• Proceedings of the KIEE Conference
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• 1989.07a
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• pp.125-128
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• 1989

This paper presents a DC servo motor controller using self-tuning PID algorithm, which can support Multi-processor for the real time processing. Computer simulation as well as experiment using Multi-processor(8088) are implemented with self-tuning PID algorithm. Presented algorithm is used to compare the performance of the controller with that of the classical PID controller through computer simulation and experiment. The result which use the Self-Tuning algorithm show that motor output follows the reference input trajectory fairly well inspite of load disturbances and parameter variations.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.504-506
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• 1999

In this paper, we propose a method which control parametric uncertainty systems using PID controller by fuzzy auto tuning. We get the error and the error change rate of plant output correspond to the initial value of parameter using the Ziegler-Nickols tuning and determine the new proportional gain$(K_p)$ and the integral time $(T_i)$ from fuzzy tuner by the error and error change rate of plant output as a membership function of fuzzy theory. The Fuzzy Auto-tuning algorithm for PID controller operate to adapt variable parameter of plant in parametric uncertainty systems. It is shown this method considerably improve the transient response at computer simulation.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.628-631
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• 2005

In this paper, we propose 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 that consist of the convex set of PID and PI-PD controller controls the closed-loop response to locate 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.

• Proceedings of the Korean Society of Marine Engineers Conference
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• 2002.05a
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• pp.261-266
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• 2002

In this Paper, we Propose model-based tuning rules of the PID controller incorporating with genetic algorithms. Three sets of optimal PID parameters for step set-point tracking are obtained based on the first-order time delay model of plants and a genetic algorithm which minimizes performance indices(IAE, ISE and ITAE). Then tuning rules are obtained using the tuned parameter sets, potential rule models and a genetic algorithm. Simulation is carried out to verify the effectiveness of the proposed rules.

• Proceedings of the Korean Society of Marine Engineers Conference
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• 2006.06a
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• pp.87-88
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• 2006

In this paper, tuning rules of the PID controller for load disturbance rejection are proposed incorporating with real-coded genetic algorithms(RCGAs). The optimal parameters sets of the PID controller are obtained based on a first-order plus time delay model and a RCGA. As for assessing the performance of the controller, criteria(ISE, IAE and ITAE) are adopted. Then tuning formulae are derived using the tuned parameters sets, potential tuning rule models and another RCGA. A simulation work is carried out to verify the effectiveness of the proposed rules.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.376-381
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• 1992

In this thesis, a self-tuning control method based on Variable Structure System technique for tracking control of Direct-Drive motor is presented. The self-tuning control could not make the tracking error zero in the transient period. This tracking error may be due to disturbances or the error in parameter identification. To overcome this problem, a self-tuning control method based on discrete time VSS technique is presented. The STC based on VSS technique gives good tracking performance of the reference signal in the transient period. The proposed controller is robust to parameter errors and disturbances. The performance of the proposed controller is compared with that of simple STC through digital computer simulation.

• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.119-121
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• 2007

PID control is windely used to control stable processes, however, its application to integrating processes is less common. In this paper, we proposed a simple PID controller tuning method for integrating processes with time delay to meet a sensitive function $M_s$. With the proposed PID tuning method, we can obtain stable integrating processes using PD controller in inner feedback loop and a loop transfer function with desired stable specification. This guarantees both robustness and performance. Simulation examples are given to show the good performance of the proposed tuning method to other methods.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.9
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• pp.1618-1623
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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 and phase margins, 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.

• 한국연소학회:학술대회논문집
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• 2012.04a
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• pp.195-196
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• 2012

This paper describes combustion tuning methodology of double-swirl gas turbine combustor using six sigma tools. This methodology is consist of five steps-Define, Identify, Design, Optimize and Verify (DIDOV). First, the NOx reduction target was defined in the step design; second, the current status of the plant was diagnosed in the step of identify; third, the vital few control parameters to achieve the defined target were determined by analyzing the correlation between the control parameters and NOx emissions in the step of design; fourth, the optimum condition was derived from one of the six sigma tools in the step of optimize; finally, the optimum condition was verified by applying the condition to the gas turbine combustor in the step of verify. As a result of the suggested method, averaged NOx emissions were reduced by more than 70% and the standard deviation was improved by more than 60%. Thus, this methodology can be attributed to the efficient reduction of NOx emission with saving combustion tuning time.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.229-229
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• 2000

Conventional gain-tuning methods such as Ziegler-Nickels methods, have many disadvantages that optimal control ler gain should be tuned manually. In this paper, modified PID controllers which include self-tuning characteristics are proposed. Proposed controllers automatically tune the PID gains in on-1ine using neural networks. A new learning scheme was proposed for improving learning speed in neural networks and satisfying the real time condition. In this paper, using a nonlinear mapping capability of neural networks, we derive a tuning method of PID controller based on a Back propagation(BP)method of multilayered neural networks. Simulated and experimental results show that the proposed method can give the appropriate parameters of PID controller when it is implemented to DC Motor.