• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2002.12a
• /
• pp.191-194
• /
• 2002

In this paper, a new GA-based methodology with information granules is suggested for construction of the fuzzy classifier. We deal with the selection of the fuzzy region as well as two major classification problems-the feature selection and the pattern classification. The proposed method consists of three steps: the selection of the fuzzy region, the construction of the fuzzy sets, and the tuning of the fuzzy rules. The genetic algorithms (GAs) are applied to the development of the information granules so as to decide the satisfactory fuzzy regions. Finally, the GAs are also applied to the tuning procedure of the fuzzy rules in terms of the management of the misclassified data (e.g., data with the strange pattern or on the boundaries of the classes). To show the effectiveness of the proposed method, an example-the classification of the Iris data, is provided.

• 제어로봇시스템학회:학술대회논문집
• /
• 2002.10a
• /
• pp.120.2-120
• /
• 2002

In this paper auto-tuning scheme of weight function in the neural networks has been suggested by immune algorithm for nonlinear process. A number of structures of the neural networks are considered as learning methods for control system. A general view is provided that they are the special cases of either the membership functions or the modification of network structure in the neural networks. On the other hand, since the immune network system possesses a self organizing and distributed memory, it is thus adaptive to its external environment and allows a PDP (parallel distributed processing) network to complete patterns against the environmental situation. Also. It can provi..

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.14 no.2
• /
• pp.136-144
• /
• 2014

The existing conventional motion controller does not perform well in the presence of nonlinear properties, uncertain factors, and servo lag phenomena of industrial actuators. Hence, a feasible and effective fuzzy self-tuning proportional integral derivative (PID) and feed-forward control scheme is introduced to overcome these problems. In this design, a fuzzy tuner is used to tune the PID parameters resulting in the rejection of the disturbance, which achieves better performance. Then, both velocity and acceleration feed-forward units are added to considerably reduce the tracking error due to servo lag. To verify the capability and effectiveness of the proposed control scheme, the hardware configuration includes digital signal processing (DSP) which plays the main role, dual-port RAM (DPRAM) to guarantee rapid and reliable communication with the host, field-programmable gate array (FPGA) to handle the task of the address decoder and receive the feed-back encoder signal, and several peripheral logic circuits. The results from the experiments show that the proposed motion controller has a smooth profile, with high tracking precision and real-time performance, which are applicable in various manufacturing fields.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2000.05a
• /
• pp.138-141
• /
• 2000

공정제어시스템을 위한 제어기로써 현재까지는 PID 제어기가 보편화되어 적용되어 왔으나 비선형 시스템이나 복잡한 시스템 제어를 위해서는 목표치 추종특성이 우수하며 환경이나 공정 파라미터변화에 둔감하여 외란에 대한 영향이 적은 제어기가 요구된다. PID 제어기로는 이러한 목적을 달성하는 데에 한계가 있기 때문에 이를 해결하기 위한 연구들이 활발히 수행되어 목표치 추종성능과 외란 억제를 동시에 만족토록 하는 다양한 2자유도 PID 제어시스템들이 제안되었고, 본 연구에서는 먼저 현재까지 제안된 2자유도 PID 제어시스템들 중 제어성능이 가장 우수한 것으로 나타난 목표치 필터형 2자유도 PID 제어시스템(Target Value Filter Type 2-DOF PID Control System: 이하 TVF-2DOF) [2]보다 우수한 2자유도PID 제어시스템을 제안하고, 이를 바탕으로 2자유도 선행필터(Pre-Filter)부분에 지능제어기법의 하나인 퍼지로직을 적용함으로써 PID 제어기의 장점과 퍼지로직의 장점을 동시에 활용하는 지능형 튜닝(Tuning)기법에 관한 연구를 수행하였고, 지능형 시스템이 2자유도 PID 제어시스템들보다 목표치 추종 성능 및 외란억제효과가 우수하다는 사실을 컴퓨터 시뮬레이션을 통해 입증하였다. 시스템으로는 유량 제어 밸브가 사용되었다.

• Proceedings of the KIEE Conference
• /
• 2001.07d
• /
• pp.2126-2128
• /
• 2001

This paper suggests that the immune network algorithm based on fuzzy set can effectively be used in tuning of a PID controller for multivariable process or nonlinear process. The artificial immune network always has a new parallel decentralized processing mechanism for various situations, since antibodies communicate to each other among different species of antibodies/B-cells through the stimulation and suppression chains among antibodies that from a large-scaled network. In addition to that, the structure of the network is not fixed, but varies continuously. On the other hand, a number of tuning technologies have been considered for the tuning of a PID controller. As a less common method, the fuzzy and neural network or its combined techniques are applied. However, in the case of the latter, yet, it is not applied in the practical field, in the former, a higher experience and technology is required during tuning procedure. Along with these, this paper used the fuzzy set in order that the stimulation and suppression relationship between antibody and antigen can be more adaptable controlled against the external condition, including noise or disturbance of plant. The immune network based on fuzzy set suggested here is applied for the PID controller tuning of multivariable process with two inputs and one output and is simulated.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.4 no.2 s.7
• /
• pp.81-87
• /
• 2005

In this paper, a VCDRO(Voltage Control Dielectirc Resonator Oscillator) for signal source of doppler radar system is designed and fabricated. The proposed VCDRO is made with new tuning mechanism using CPW line. The coplanar waveguide of $\lambda_{g}$/2 in length with varactor diode is placed on the metallization side under the dielectric resonator and coupled to it. Tuning varactor diode is mounted at one end of the CPW. The proposed circuit tuned by a CPW allows one more varactor diode to be mounted on the optimized CPW, where a greater sensitivity of frequency tuning is needed. With varying the biasing voltage for the varactor diode from 0 V to 15 V, output frequency tuning of 12 MHz is obtained. The PLDRO exhibits output power of 16.5 dBm with phase noise in the phase locked state characteristic of -115 dBc/Hz at 100 Hz, -105 dBc/Hz at the 10 kHz, and -102 dBc/Hz at 1 Hz offset from 10.525 GHz , respectively.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.17 no.3
• /
• pp.355-367
• /
• 2007

This paper proposes a design method of the PI(Proportional-Integral)+D(Derivative) controller using self-tuning of the design variables and controller gains. The used fuzzy PI+D controller is the approximated conventional continuos time linear PI+D controller and the used fuzzification method is the fuzzy single tone and the adapted defuzzification method is the simplified tenter of gravity. Fuzzy estimation result would be calculated in the other function elements from the classified fuzzy variables and the result determined by the design variables decides the controller gains. As a result, the proposed method shows the capability of the high speed tuning and can be applied to the case of input variables with many fuzzy partitions and also can bring out the advantage to reduce the reconstruction(digital sampling reconstruction) error. Most simulation results show that this controller makes much bettor efficiency and improvement by using design variables and controller gains.

• 제어로봇시스템학회:학술대회논문집
• /
• 2004.08a
• /
• pp.885-890
• /
• 2004

Strictly maintaining the steam temperature can be difficult due to heating value variation to the fuel source, time delay changes in the main steam temperature, the change of the dynamic characteristics in the reheater. Up to the present time, PID Controller has been used to operate this system. However, it is very difficult to achieve an optimal PID gain with no experience, since the gain of the PID controller has to be manually tuned by trial and error. This paper focuses on tuning of the Controller with disturbance rejection for thermal power plant using immune based multiobjective approach. An ITSE(Integral of time weighted squared error) is used to decide performance of tuning results.

• Proceedings of the KIEE Conference
• /
• 1991.11a
• /
• pp.345-348
• /
• 1991

This paper describes a new auto tuning method for the intelligent PID control system. This new method is hosed on the settling time of the process and has been introduced into auto-tuning PID controller using fuzzy logic. The performance of the controller is measured by computer simulation. Simulation shows good results that controller searches well the optimal values of PID parameters in any conditions and the response characteristic of the control system is improved.

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