• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.13 no.4
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• pp.102-108
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• 1999

The sliding rmde controller(SMC) is known as having the robust variable structures for the nonlinear control systems such as coupled tank system with the pararretric perturbations and with the rapid disturbances. But the adaptive tuning algorit1uns for their pararreters are not satisfactory. Therefore, in this paper, a Real Variable Elitist Genetic Algorithm based Sliding Mode Controller (RVEGA SMC) for the precise control of the coupled tank level was tried. The SMC's switching pararreters were optimized easily and rapidly by RVEGA The simulation results showed that the tank level could be satisfactorily controlled without any overshoot and any steady-state error by the proposed RVEGA SMC.GA SMC.

• Journal of Advanced Marine Engineering and Technology
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• v.24 no.1
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• pp.104-111
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• 2000

It is very difficult to maintain the desired tank level without any overflow or any shortage in a dangerous shemical plant and in a cooling one. Futhermore, because its dynamics are very complicate and nonlinear, it is impossible to realize the precise control using the accurate mathematical model which can be applied to the various peration modes. Nonetheless, the sliding mode controller(SMC) is known as having the robust variable structures for the nonlinear control system with the parametric perturbations and with the rapid disturbances. But the adaptive tuning algorithms for their parameters are not satisfactory. Therefore, in this paper, a Real Variable Elitist Genetic Algorithm based Sliding Mode Controller (RVEGA SMC) for the precise control of the coupled tank level was tried. The SMC's switching parameters were optimized easily and rapidly by RVEGA. The simulation results showed that the tank level could be satisfactorily controlled without and overshoot and any steady-state error by the proposed RVEGA SMC.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.10
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• pp.1327-1334
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• 1999

The stabilization control of ball-beam system is difficult because of its nonlinearity and structural unstability. Futhermore, a series of classical methods such as the PID and the full state feedback controller(FSFC) based on the local linearizations have narrow stabilizable regions. At the same time, the fine tunings of their gain parameters are also troublesome. Therefore, in this paper, three improved design techniques of stabilization controller for a ball-beam system were proposed. These parameter tuning methods in the double PID controller(DPIDC), the FSFC and the a sliding mode controller(SMC) were dependent upon the Real Value Elitist Genetic Algorithm (RVEGA). Finally, by applying the DPIDC, the FSFC and the Real Variable Elitist Genetic Algorithm based Sliding Mode Control(RVEGA SMC) to the stabilizations of a ball-beam system, the performances of the RVEGA SMC technique were showed to be superior to those of two other type controllers.

• Journal of Advanced Marine Engineering and Technology
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• v.21 no.4
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• pp.393-403
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• 1997

In this paper, we proposed an optimal identification method of identifying the membership func¬tions and the fuzzy rules for the stabilization controller of the nonlinear system by RVEGA( Real Variable Elitist Genetic Algo rithm l. Although fuzzy logic controllers have been successfully applied to industrial plants, most of them have been relied heavily on expert's empirical knowl¬edge. So it is very difficult to determine the linguistic state space partitions and parameters of the membership functions and to extract the control rules. Most of conventional approaches have the drastic defects of trapping to a local minima. However, the proposed RVEGA which is similiar to the processes of natural evolution can optimize simulta¬neously the fuzzy rules and the parameters of membership functions. The validity of the RVEGA - based fuzzy controller was proved through applications to the stabi¬lization problems of an inverted pendulum system with highly nonlinear dynamics. The proposed RVEGA - based fuzzy controller has a swing -. up control mode(swing - up controller) and a stabi¬lization one(stabilization controller), moves a pendulum in an initial stable equilibrium point and a cart in an arbitrary position, to an unstable equilibrium point and a center of the rail. The stabi¬lization controller is composed of a hierarchical fuzzy inference structure; that is, the lower level inference for the virtual equilibrium point and the higher level one for position control of the cart according to the firstly inferred virtual equilibrium point. The experimental apparatus was imple¬mented by a DT -- 2801 board with AID, D/A converters and a PC - 586 microprocessor.

• Proceedings of the Korean Society of Marine Engineers Conference
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• 2001.05a
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• pp.238-242
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• 2001

In this paper, we proposed an optimal identification method of the membership functions and the numbers of fuzzy rule base for the stabilization controller of the Thermal process control system by RVEGA. Although fuzzy logic controllers and expert systems have been successfully applied in many complex industrial process, they must rely on experts knowledges. So it is difficult in determination of the linguistic state space, definition of the membership functions of each linguistic term and the derivation of the control rules. To verify the validity of this RVEGA-based fuzzy controller, Thermal process control system, with strong nonlinear dynamics, was selected for application of this algorithm and compare with PI controller, and the empirically improved fuzzy controller.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.51 no.10
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• pp.483-494
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• 2002

In this thesis an optimal design technique of fuzzy logic controller using the real variable elitist genetic algorithm(RVEGA) as a supplementary control to Static Var Compensator(SVC) in order to damp oscillation in an AC-DC Dower system was proposed. Fuzzy logic controller is designed self-tuning shape of fuzzy rule and fuzzy variable using genetic algorithm based on natural selection and natural genetics. To verify the robustness of the proposed method, considered dynamic response of system by applying a load fluctuation.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.50 no.7
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• pp.324-332
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• 2001

In this paper, it is suggested that the selection method of parameter of Power System Stabilizer(PSS) with robustness in low frequency oscillation for Static VAR Compensator(SVC) using a Real Variable Elitism Genetic Algorithm(RVEGA). A SVC, one of the Flexible AC Transmission System(FACTS), constructed by a fixed capacitor(FC) and a thyristor controlled reactor(TCR), is designed and implemented to improve the damping of a synchronous generator, as well as controlling the system voltage. The proposed PSS parameters are optimized using RVEGA in order to maintain optimal operation of generator under the various operating conditions. To decrease the computational time, real variable string is adopted. To verify the robustness of the proposed method, we considered the dynamic response of generator speed deviation and generator terminal voltage by applying a power fluctuation and three-phase fault at heavy load, normal load and light load. Thus, we prove the usefulness of proposed method to improve the stability of single machine-infinite bus with SVC system.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.6
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• pp.683-691
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• 1999

In this paper, it is suggested that the selection method of optimal parameter of power system stabilizer(PSS) with robustness in low frequency oscillation for power system using Real Variable Elitism Genetc Algorithm(RVEGA). The optimal parameters were selected in the case of power system stabilizer with one lead compensator, and two lead compensator. Also, the frequency responses characteristic of PSS, the system eigenvalues criterion and the dynamic characteristic were considered in the normal load and the heavy load, which proved usefulness of RVEGA compare with Yu's compensator design theory.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.966-968
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• 1999

It is very difficult to maintain the desired tank level without overflow or shortage in a dangerous chemical plant. and a cooling one. Futhermore, because its dynamics are very complicate and nonlinear, the accurate mathematical model cannot be technique acquired and also their problems cannot be solved easily. In this paper, a RVEGA SMC for the robust control of a coupled tank level was proposed. The simulation results were very appreciative.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2624-2626
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• 2000

The stabilization controls of coupled tank system and ball-beam system are difficult control tasks because of their high order time delay, nonlinearity and structural unstability. Fuhermore, a series of classical methods such as a conventional PID and a full state feedback controller(FSFC) based on the local linearizations have narrow stabilizable regions. Therefore, in this paper, in order to stabilize two representative nonlinear system mentioned above, a Sliding Mode Controller based on a Real Variable Elitist Genetic Algorithm(RVEGA SMC) was proposed.