• 제어로봇시스템학회:학술대회논문집
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• 1991.10b
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• pp.1671-1676
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• 1991

Direct digital design of computed torque controllers for a robot manipulator is discussed in this paper. A simple discrete-time model of the robot manipulator obtained by Euler's method is used for the design. Taking account of computation delay in the digital processor, we propose predictor-based designs of the PD and PID type controllers. The PID type controller is designed based on a modified version of the discrete-time integral controller proposed by Mita. For both controllers, the same formulas can be used to determine the feedback gains. A simulation example is presented to compare the robustness of the proposed controllers against physical parameter variations.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.241-244
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• 1996

This paper discusses the general properties and the design procedures of Internal Model Control(IMC) scheme for nonlinear plants. Also we propose new nonlinear IMC(NIMC) design method using linear IMC. Although all IMC controllers can be thought simple 'inverse controller', its nonlinear realization is not easy. Propose NIMC is composed multiple linear models, IMC controllers, and switching scheme. The advantages of this method are we can use simple linear IMC design method and need not nonlinear modelings.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.11
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• pp.1013-1021
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• 2000

This paper suggests fuzzy-PI controllers for a heavy-duty gas turbine. The fuzzy-PI controllers are designed to regulate rotor speed and exhaust temperature of the gas turbine. The controller gains are tuned by genetic algorithm(GA). This paper also proposes a new fitness function of GA using a desired output response. The suggested controller is compared with previous controllers via simulations and it is shown that the rotor speed variation of our controller is smaller than those of previous ones.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.92.3-92
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• 2001

This paper is concerned with robust attitude control of large space structures with collocated sensors and actuators. Since the transfer function matrices of such systems are symmetric, it seems suitable to employ symmetric controllers. This paper shows that it is true if no constraint is imposed on the orders of the controllers, but it is not true if the orders of the controllers are specified to be lower than that of the system to be controlled.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2000.04a
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• pp.349-356
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• 2000

EPC(Engineering process control) is usually applied to processes in which successive observations ate related over time and where the mean drifts dynamically. This paper aims to literature surrey concerned about EPC theory developments and their applications including macGregor model as Basic EPC model, feedback controllers, feedforward controllers, run-to-run controllers, MMSE controllers, PID model and PI adjustment model and so on. We suggest some perspective area for further study.

• Proceedings of the KIEE Conference
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• 1997.11a
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• pp.136-138
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• 1997

This paper proposes a design method to improve the performance of Indirect Adaptive Controllers using a CP net. This hybrid control architecture consists of Indirect Adaptive Controllers and CP net Controller. The performance of a single Adaptive Controller, multi Adaptive Controllers and the proposed model is compared by control problems. The simulation results show that the proposed model is superior to the others in most cases, in regard of not only learning speed but also control problems.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.9 no.2
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• pp.154-160
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• 2009

A control system composed of two fuzzy controllers is proposed to balance the pole as well as to move the cart to the center of the track of the cartpole system. The two fuzzy controllers are designed with 2 input variables respectively and their control characters are studied in order to devise a control scheme that alternates the two fuzzy controllers. It is found that the control system using the scheme works well even though there is some residual oscillations of the pole and the cart.

• Journal of the Korean Institute of Intelligent Systems
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• v.7 no.4
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• pp.48-57
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• 1997

This paper presents the automatic construction and parameter optimization technique for fuzzy logic controllers using genetic algorithm. In general. the design of fuzzy logic controllers has difficulties in the acq~lisition of expert's knowledge and relies to a great extent on empirical and heuristic knowledge which, in many cases, cannot be objectively justified. So, the performance of the controllers c:an be degraded in the case of plant parameter variations or unpredictable incident which a designer may have ignored, and the parameters of fuzzy logic controllers obtained by expert's control action may not be optirnal. Some of these problems can be resolved by the use of genetic algorithm. The proposed method can tune the parameters of fuzzy logic controllers including scaling factors and determine: the appropriate number of fuzzy rulcs systematically. Finally, we provides the second order dead time plant to evaluate the feasibility and generality of the proposed method. Comparison shows that the proposed method can produce fuzzy logic controllers with higher accuracy and a smaller number of fuzzy rules than manually tuned fuzzy logic controllers.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.1
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• pp.102-109
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• 2014

In this paper, an algorithm to design fuzzy PID controllers is proposed. The proposed controllers are composed of fuzzy rules of which consequences are linear PID controllers and are designed with help of TSK fuzzy controllers. TSK fuzzy controllers are designed from TSK fuzzy model using pole assignment and have outstanding ability making the output response of nonlinear systems similar to the desired one. However, because of its structure complexity the TSK fuzzy controller is difficult to be used in industry. The proposed controllers have PID controller structure which can be easily realized, and are designed by using the data obtained from control simulations with TSK fuzzy controllers. To verify the proposed algorithm, two example simulations are performed.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1008-1011
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• 1996

Most control systems of power plants are using classical PID controllers for their process control. In order to get the desired control performances, the correct tuning of PID controllers is very important. Sometimes, it is necessary to retune PID controllers after the change of system operating condition and system design change, etc. Commercial auto-tuning controllers such as relay feedback controller can be used for this purpose. However, using these controllers to the safety-critical systems of nuclear power plants may be cause of unsafe operation, because they are using test signals for tuning. A new system identification auto-tuning method without using test signal has been developed in this paper. This method uses process input/output signals for system identification of unknown control process. From the model information of control process which was obtained from system identification approach, the optimal PID parameters can be calculated. The method can be used in the safety-critical systems because it is not using test signals during system modeling process.