• Proceedings of the KIEE Conference
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• 1999.11c
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• pp.588-590
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• 1999

In this paper the design method of a fuzzy logic controller with a genetic algorithm is proposed. Fuzzy logic controller is based on linguistic descriptions(in the form of fuzzy IF-THEN rules) from human experts. The auto-tuning method is presented to automatically improve the output performance of controller utilizing the genetic algorithm. The GA algorithm estimates automatically the optimal values of scaling factors and membership function parameters of fuzzy control rules. Controllers are applied to the processes with time-delay and the DC servo motor. Computer simulations are conducted at the step input and the output performances are evaluated in the ITAE.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1196-1198
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• 1996

It is well known that the controller output limits have a significant effect on the closed loop system performance. GPC has many tuning-knobs which can he used to minimize actuator activity. Especially, increasing the control weighting $\lambda$ cuts down the controller output variance. Using this property, we propose the GPC with Input constraints(GPCIC) which is based on the relation between control weighting $\lambda$ and optimal solution of the unconstrained GPC. The GPCIC algorithm is the calculation of the optimal $\lambda$ such that the output of the unconstrained GPC is satisfied with the rate Ind the level constraint.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.34 no.1
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• pp.1-9
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• 1985

In this study we described Binary-Decision Method Programmable Controller that is faster than conventional Programmable Controller (P.C) using the Boolean method. An algorithm for the optimal BD program was systematically developed by using the incomplete multiple output function and the residual characteristic function. The potential applications of BD programmable controller for the problems of industrial control were illustrated, which include on-off sequential control function and also the tasks involving continuous data processing and PID control. An example was presented that has shown how BD programmable controller and ICU (Industrial Control Unit) controller can be applied to the sequential logics.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.3 no.2
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• pp.363-371
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• 1999

In this paper proposes the optimal fuzzy controller design method using the genetic algorithm. Proposed method is that fuzzy rules and input - output scaling factors of the fuzzy controller are determined by using genetic algorithm that is very effectively in the optimization problem. The optimal fuzzy rules of servo system uses the fitness function which are the performance index in fuzzy controller. In order to verify excellent control performances of the proposed control method, we compare the control performance and characteristics about the proposed control method with a conventional fuzzy control method through a lot of simulations and experiments with one link manipulator.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.972-974
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• 1993

This paper presents a new method to automatically design fuzzy logic controller(FLC). The main problems of designing FLC are how to optimally and automatically select the control rules and the parameters of membership function (MF). Cell state space algorithms (CSS), differential competitive learning (DCL) and multialyer neural network are combined in this paper to solve the problems. When the dynamical model of a control process is known. CSS can be used to generate a group of optimal input output pairs(X, Y) used by a controller. The(X, Y) then can be used to determine the FLC rules by DCL and to determine the optimal parameters of MF by DCL and to determine the optimal parameters of MF by multilayer neural network trained by BP algorithm.

• 한국생물공학회:학술대회논문집
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• 2000.04a
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• pp.173-176
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• 2000

A neural network based controller (NN controller) was studied for the control of ammonia concentrations in biological processes. An ammonia FIA has been employed to on-line monitor the concentrations of ammonia in a bioreactor. The optimal neural network structure was investigated by computer simulation and found to be a 3(inputlayer)-2(hidden layer)-1(output layer). The NN controller had advantage over the PID controller, even though the former is more time consuming. The 3-2-1 NN controller has been used to control the ammonia concentrations in a simulated bioprocess and also in a real cultivation process of yeast, and its performance were investigated.

• 제어로봇시스템학회:학술대회논문집
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• 1986.10a
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• pp.576-579
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• 1986

In this paper, a design method of an optimal output PIM(Proportional-Integral-Measurable) controller is presented so that the closed-loop output response of the switching regulator closely match to that of ideal model system satisfying the time domain specifications. The computer simulation for a design example is given to show the usefulness of the proposed technique.

• Transactions of the Korean Society of Automotive Engineers
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• v.3 no.4
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• pp.1-11
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• 1995

Active suspension control for vehicles is developed to improve both ride comfort and steering stability which are in trade off relation. In this study, the modal sky-hook controller for 7 D. O. F. model is proposed to resolve the problems such as computaional power restriction and uncertainties in modeling of systems and environments. Modal sky-hook controller reduces the coupling between the modes to be controlled. The simulation result for ride comfort shows that the perform ance of the proposed controller matches that of the optimal controller. Systematic method of determining its gain is proposed. The model sky-hook controller shows the robustness to road irregularity and modeling error.

• Journal of Electrical Engineering and Technology
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• v.13 no.5
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• pp.2074-2079
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• 2018

Global state space's optimal policy is used for offline controller in the form of table by using Dynamic Programming. If an optimal policy table has a large amount of control data, it is difficult to use the system in a low capacity system. To resolve these problem, controller using the compressed optimal policy table is proposed in this paper. A DCT is used for compression method and the cosine function is used as a basis. The size of cosine function decreased as the frequency increased. In other words, an essential information which is used for restoration is concentrated in the low frequency band and a value of small size that belong to a high frequency band could be discarded by quantization because high frequency's information doesn't have a big effect on restoration. Therefore, memory could be largely reduced by removing the information. The compressed output is stored in memory of embedded system in offline and optimal control input which correspond to state of plant is computed by interpolation with Inverse DCT in online. To verify the performance of the proposed controller, computer simulation was accomplished with a one link inverted pendulum.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10a
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• pp.206-209
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• 1988

For feedback control of a linear dynamic system the optimum linear slace regulator (OLSR) can be implemented only if all state are available for feedback. This work demonstrates that when only the output state is available for feedback, a nonlinear controllers can be improved performance over that obtained by a proportional controller. This paper found the optimal control law by well-known dynamic programming and principles of optimality. Thus, performance of both proportional and nonlinear controllers is compared with performance of optimum linear state regulator.