• Journal of the Korean Institute of Intelligent Systems
• /
• v.12 no.4
• /
• pp.353-360
• /
• 2002

Methods for automatic tuning of PID controllers have been on of the results of the active research on control. The proposed controller also is auto-tuning of PID controller The proposed immune algorithm has an uncomplicated structure and memory-cell mechanism as the optimization algorithm which imitates the principle of humoral immune response. We use the proposed algorithm to solve optimization of PID controller parameters. Up to now, the applications of immune algorithm have been optimization problems with non-varying system parameters. Therefore the usefulness of memory-cell mechanism in immune algorithm is without. And research of memory-cell mechanism does not give us entire satisfaction. This paper proposes the immune algorithm using a memory-cell mechanism which can be the application of system with nonlinear varying parameters. To verify performance of the proposed immune algorithm, the speed control of nonlinear DC motor are performed. The results of Computer simulations represent that the proposed immune algorithm shows a fast convergence speed and a good control performances under the varying system parameters.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.8 no.8
• /
• pp.1195-1200
• /
• 2013

In this paper, we proposed an enhanced Max-Min neural network by auto-tuning of learning rate using fuzzy control method. For the reduction of training time required in the competition stage, the method was proposed that arbitrates dynamically the learning rate by applying the numbers of the accuracy and the inaccuracy to the input of the fuzzy control system. The experiments using real concrete crack images showed that the enhanced Max-Min neural network was effective in the recognition of direction of the extracted cracks.

• Proceedings of the KIEE Conference
• /
• 1996.07b
• /
• pp.1377-1379
• /
• 1996

In this paper, each parameter was identified by the gradient descent method to overcome difficulty deciding fuzzy rules of FLC for the unknown process and the type of membership Junctions. Usually PID or optimal control theories have been mostly usee in control field so far. However, optimal control requires much time for calculation because of adaptation for disturbance and nonlinearity. And intricate technique such as MRAS which can be realized only by an expert are limited to be used in the systems requiring rapid and precise response because of comparatively longer calculating time and complicateness. Gradient descent method is a method to find Z minimizing a function about a certain vector Z. And required output of FLC is gained using gradient approaching method in order to adapt control rule parameters of FLC. Simulation proved validation of this algorithm.

• Proceedings of the KIPE Conference
• /
• 2001.10a
• /
• pp.69-74
• /
• 2001

In this Paper are described the indirect induction heated boiler and induction heated hot air producer using the voltage-fed series resonant high-frequency inverter which can operate in the frequency range from 20kHz to 50kHz. A specially designed induction heater, which is composed of laminated stainless assembly with many tiny holes and interconnected spot welding points between stainless plates, is inserted into the ceramic type vessel with external working coil. This working coil is connected to the inverter and turbulence fluid through this induction heater to moving fluid generates in the vessel. The operating performances of this unique appliance in next generation and its effectiveness are evaluated and discussed from a practical point of view.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.8 no.6
• /
• pp.106-118
• /
• 1998

The study concerns a design procedure of rule-based systems. The proposed rule-based fuzzy modeling implements system structure and parameter identification in the efficient from of "IF..., THEN..." statements, and exploits the theory of system optimization and fuzzy implication rules. The method for rule-based fuzzy modeling concerns the from of the conclusion part of the the rules that can be constant. Both triangular and Gaussian-like membership function are studied. The optimization hinges on an autotuning algorithm that covers as a modified constrained optimization method known as a complex method. The study introduces a weighted performance index (objective function) that helps achieve a sound balance between the quality of results produced for the training and testing set. This methodology sheds light on the role and impact of different parameters of the model on its performance. The study is illustrated with the aid of two representative numerical examples.

• Proceedings of the IEEK Conference
• /
• 1998.06a
• /
• pp.207-210
• /
• 1998

Brushless servomotor systems offer a great advantae in unmanned factories where a great number of servomotors are employed, because of its easy maintenance charateristics and controllability. This paper propose a sinusoidal type brushless DC motor speed servo system which has high efficiency and usability in industrial field as described above. And this servo system is realized by a new Auto-Tuning PI control algorithm and verified it's practical potential of implementation by self-designed driver system. In particular, DSP(digital signal processor) is adopted in this study as controller and sensor signal processor owing to their fast computational capability and suitable architecture.

• Proceedings of the KIEE Conference
• /
• 1992.07a
• /
• pp.135-137
• /
• 1992

A new algorithm for self-tuning digital controller is proposed. The system to be controlled is identified on line in auto-regressive-moving-average(ARMA) form via recursive least mean square method. The control law is obtained from the minimization of an objective function. The proposed objective function is similar to that of Generalized Minimum Variance(GMV) method but modified to lessen the overshoot and to avoid numerical divergence problem. This algorithm is applied to the power system stabilization and the comparison of the proposed method with a conventional power system stabilizer(PSS) is presented.

• 한국초전도학회:학술대회논문집
• /
• v.12
• /
• pp.43-43
• /
• 2002

• Proceedings of the KIEE Conference
• /
• 2000.07b
• /
• pp.1146-1150
• /
• 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, initial values are determined by the Switched Reluctance Motor of system and Ziegler-Nichols method. After deciding binary strings of parents generation using by the fitness values of genetic algorithms, we perform selection, crossover and mutation to generate the descendant generation. The advantage of this method is better than the neural network and multiple regression model method in characteristic of output, and has extent of applying without limit of initial parameters.

• Proceedings of the KIEE Conference
• /
• 1995.07b
• /
• pp.695-698
• /
• 1995

The shape and width of fuzzy membership function has an effect on performance of fuzzy controller. In this paper, fuzzy controller is proposed to improve the control performance of fuzzy controller. It has two fuzzy inference engine. The one is typical fuzzy inference engine, the other is proposed to infer optimal width of membership function in fuzzy controller from plant constant (K,T,L). To show the effectiveness of this fuzzy controller with double fuzzy inference engine, it is applied to plant (dead time + 1st order delay) with various plant constant.