• 제어로봇시스템학회:학술대회논문집
• /
• 1991.10a
• /
• pp.922-927
• /
• 1991

This study is aimed to investigate a design problem of the fuzzy logic controller for the activated sludge process(ASP) in sewage treatment. The modeling technique proposed by Sugeno is used to express the ASP effectively and identification of a fuzzy model of the ASP is carried out utilizing actual operational data obtained from a metropolitan sewage plants. The model-based fuzzy controller is designed by rules generated from the identified ASP fuzzy model. Feasibility of the designed controller is tested through computer simulations.

• 제어로봇시스템학회:학술대회논문집
• /
• 1988.10a
• /
• pp.137-141
• /
• 1988

A sampled data controller for the quadruped walking robot is presented. To provide systematic design procedure, the relation between PI gain of velocity controller and sampling rate is analyzed with the ISE performance index and the time responses. The position controller for one-leg, 3-axis, was developed under consideration of compactness and expendability. And several experiments were performed.

• 제어로봇시스템학회:학술대회논문집
• /
• 1986.10a
• /
• pp.488-492
• /
• 1986

This paper presents a design method for PID controller using optimal control theory. The procedures of the applied method consist of (1) sampling the system response to the test signal, (2) processing the sampled data using RPE method to identify the parameters of the plant, (3) calculating the optimal value of the PID controller parameters using LQ theory. This controller is implemented on the digital computer and applied to real servomechanism, yielding satisfactory result.

• 제어로봇시스템학회:학술대회논문집
• /
• 1997.10a
• /
• pp.1557-1560
• /
• 1997

In this paper, we have built an experimental magnetic levitation system for a possible use of control education. We have give a mathermatical model of the nonlinear system and have shown the stability region of the linearized system when it is controlled by a PD controller. We also proposed a neural network control system which uses a neural network as a feedforward controller thgether with a conventional feedback PF controller. We have generated a desired output trajectory, which was designed for the benefit of the generalization of the neural network controller, and trained the desired output trajectory, which was desigend for the benefit of the generalization of the neural netowrk controller, and trained a neural network controller with the data of the actual input and the output of the system obtained by applying the desired output trajectroy. A good tracking performance was observed for both the desired trajectiories used and not used for the neural network training.

• 제어로봇시스템학회:학술대회논문집
• /
• 1993.10b
• /
• pp.378-384
• /
• 1993

In this paper, an intelligent adaptive controller is proposed for the process with unmodelled dynamics. The intelligent adaptive controller consists of the numeric adaptive controller and the intelligent tuning part. The continuous scheme is used for the numeric adaptive controller to avoid the problems occurred in the discrete time schemes. The adaptive controller is adopted to the process with time delay. It is an implicit adaptive algorithm based on GMV using the emulator. The tuning part changes the design parameters in the control algorithm. It is a multilayer neural network trained by robustness analysis data. The proposed method can improve the robustness of the adaptive control system because the design parameters are tuned according to the operating points of the process. Through the simulation, robustnesses are shown for intelligent adaptive controller. Finally, the proposed algorithms are implemented on the electric furnace temperature control system. The effectiveness of the proposed algorithm is shown from experiments.

• Transactions of the Korean Society of Machine Tool Engineers
• /
• v.11 no.2
• /
• pp.50-58
• /
• 2002

The test method using simulator to objectively measure the steering feel from several drivers was proposed. It has also described the ideas to analyse the principal factors affecting the steering feel of the driver using the correlation analysis of the measured data and the questionnaire. Proportional Derivative(PD) controller has been used to measure the steering feel, and the control parameters have been selected to obtain the optimal steering feel. Membership frictions of Sugeno fuzzy model are constructed from the assist torque values calculated from PD controller at each steering state. Moreover to verify the performance, this fuzzy controller has been compared with the another fuzzy controller of which membership frictions are derived from the knowledge of drivers. As a result it can be concluded that the proposed fuzzy controller improves the steering feel at each steering state more than any other conventional methods.

• 제어로봇시스템학회:학술대회논문집
• /
• 1996.10b
• /
• pp.956-959
• /
• 1996

In this study, we propose a neuro-genetic controller combined with a linear controller in parallel to improve the tracking performance of the Line of Sight(LOS) stabilization system and reject the effect of disturbances. A Genetic Algorithm(GA) is used to optimize weights of the neuro-genetic controller since this algorithm can search a global minimum without derivatives or other auxiliary knowledge. The LOS system is very complex and has limited measurable output data. Under these specific circumstances GA solves many problems that other training methods have. Computer simulation results show that the, proposed controller makes better tracking response and rejection of disturbance than a linear controller.

• 제어로봇시스템학회:학술대회논문집
• /
• 1992.10a
• /
• pp.200-205
• /
• 1992

The classical control theory has been developed successfully for the design of a system controller and has evolved continually. Even though sophisticated simulation techniques and software packages are available, there is still some difficulty in the design of a complex system controller at the desk. So the trial and error method is sometimes used to design a new controller, but it requires excess time and cost. This paper suggests a controller design method through the experimental approach. The basic concept is to adjust gradually the design parameters of the controller to the simulation results and experimental data of a similar real system. This method will be a very useful and easy way to design an accurate and/or optimal controller for a real plant while reducing time and giving a good solution at a reasonable cost.

• Journal of the Korean Society of Industry Convergence
• /
• v.6 no.4
• /
• pp.393-399
• /
• 2003

In this paper, a self-organizing fuzzy logic controller with hybrid structure is proposed. The structure of the proposed method is composed of a basic fuzzy logic controller and the FARMA SOC(Fuzzy Autoregressive Moving Average Self-organizing Controller). The self-organizing cntroller with hybrid structure has advantage over the FARMA controller as follows. The proposed controller improves poor performance due to the lack of I/O data to calculate predictive output. I executed some computer simulations on the regulation problem of an inverted pendulum system and compared the results of the proposed method with those of the FARMA SOC method.

• 제어로봇시스템학회:학술대회논문집
• /
• 1987.10b
• /
• pp.413-418
• /
• 1987

The software developed for the large scale Programmable Controller consists of the programmer's S/W, the Controller's S/W the RBC's (Remote Base Controller's) S/W and the Analog's S/W. The programmer's S/W, running on the Programmer, includes the editor, the compiler, the communication program, and some other programs for easy use. The Controller S/W, which requires the fast scanning time, consists of the BTI( Block Type Instruction) solving program, the timer service routine, the i/o update program, the communication program and etc. The RBC's S/W includes the communication program, the error recovery program and the i/o processing program. The analog S/W, controlled by the Programmer, includes the PID program. The data communication between the Programmer and the Controller the Controller and the RBC, and the RBC and the Analog are developed.