• Journal of Institute of Control, Robotics and Systems
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• v.14 no.9
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• pp.948-955
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• 2008

The conventional PID controller has been widely employed in industry. However, the PID controller with one degree of freedom(DOF) can not optimize both set-point tracking response and disturbance rejection response at the same time. In order to solve this problem, a few types of 2DOF PID controllers have been suggested. In this paper, a tuning formula for a 2DOF PID controller is presented. The optimal parameter sets of the 2DOF PID controller are determined based on the first-order plus time delay process and a real-coded genetic algorithm(RCGA) such that the ITAE performance criterion is minimized. The tuning rule is then addressed using calculated parameter sets and another RCGA. A set of simulation works are carried out on three processes with time delay to verify the effectiveness of the proposed rule.

• Journal of Electrical Engineering and Technology
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• v.8 no.3
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• pp.402-410
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• 2013

In this paper, a novel and robust Power System Stabilizer (PSS) is proposed as an effective approach to improve stability in electric power systems. The dynamic performance of proposed PSS has been thoroughly compared with Conventional PSS (CPSS). Both the Real Coded Genetic Algorithm (RCGA) and Particle Swarm Optimization (PSO) techniques are applied to optimum tune the parameter of both the proposed PSS and CPSS in order to damp-out power system oscillations. Due to the high sufficiency of both the RCGA and PSO techniques to solve the very non-linear objective, they have been employed for solution of the optimization problem. In order to verify the dynamic performance of these devices, different conditions of disturbance are taken into account in Single Machine Infinite Bus (SMIB) power system. Moreover, to ensure the robustness of proposed PSS in damping the power system multi-mode oscillations, a Multi Machine (MM) power system under various disturbances are considered as a test system. The results of nonlinear simulation strongly suggest that the proposed PSS significantly enhances the power system dynamic stability in both of the SMIB and MM power system as compared to CPSS.

• Journal of Navigation and Port Research
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• v.31 no.8
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• pp.697-703
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• 2007

In this paper, we focuses on the development of Takagi-Sugeno (T-S) fuzzy modeling in a nonlinear container crane system. A T-S fuzzy model is characterized by fuzzy "if-then" rules which represent the locally input-output relationship whose consequence part is described by a state space equation as subsystem. The T-S fuzzy model in container cranes first obtains a few number of linear models according to operation conditions and blends these conditions using fuzzy membership functions. Parameters of the membership functions are adjusted by a RCGA to have same dynamic characteristics with nonlinear system of a container crane. Simulations are given to illustrate the performance of T-S fuzzy model.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.19 no.5
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• pp.475-481
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• 2009

Real-coded genetic algorithm(RCGA) has better performances than conventional genetic algorithm about dealing with a large domain, the precision and the constrain problem. Also the RCGA has advantage of operation time because it doesn't have to following about decoding operation. In this paper the ranges of PID gains are limited based on Ziegler-Nichols method to consider a long operation time problem that is the main problem of genetic algorithm. Result shows proposed method represents better performance without ignored about result of ZN tuning method and reduces the calculation time.

• Journal of Power System Engineering
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• v.13 no.4
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• pp.68-73
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• 2009

The mathematical model has a different response character with the real system because this mathematical model has the modeling errors and the imprecise value of system's parameters. Therefore to find the value of system parameters as possible as near by real value in the model is necessary to design the controlled system. This study concern about the identification method to estimate the parameter for the magnetic bearing system with RCGA(Real Coded Genetic Algorithm). Firstly, we will get the mathematical model from the current amplifier circuit and the magnetic bearing system. Secondly we will get the step response data in this circuit and system. Finally, we will estimate the unknown parameter's value from the data.

• Journal of Advanced Marine Engineering and Technology
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• v.30 no.6
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• pp.746-752
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• 2006

This paper presents a scheme for the parameter estimation and stabilization of unstable systems, such as inverted pendulum systems. First a stable feedback loop is constructed for an inverted pendulum system and then its parameters are estimated based on input-output data, a real-coded genetic algorithm(RCGA) and the model adjustment technique. Then, a PI-type LQ control scheme is designed based on the estimated model. The performance of the proposed algorithm is demonstrated through a set of simulation and experiment.

• Proceedings of the Korean Society of Marine Engineers Conference
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• 2006.06a
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• pp.87-88
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• 2006

In this paper, tuning rules of the PID controller for load disturbance rejection are proposed incorporating with real-coded genetic algorithms(RCGAs). The optimal parameters sets of the PID controller are obtained based on a first-order plus time delay model and a RCGA. As for assessing the performance of the controller, criteria(ISE, IAE and ITAE) are adopted. Then tuning formulae are derived using the tuned parameters sets, potential tuning rule models and another RCGA. A simulation work is carried out to verify the effectiveness of the proposed rules.

• Journal of Advanced Marine Engineering and Technology
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• v.31 no.4
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• pp.448-454
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• 2007

The new tuning rules of the PID controller for the rejection of load disturbance are proposed incorporating with real-coded genetic algorithms (RCGAs). The optimal gain parameters of the PID controller for a first-order plus time delay model are obtained based on a RCGA. Then tuning formula are derived using the tuned parameters sets potential tuning rule models and another RCGA. The performance criteria of the controller are adopted as ISE, IAE and ITAE. A series of simulation are carried out to verify the effectiveness of the proposed tuning rules.

• Proceedings of the Korean Society of Marine Engineers Conference
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• 2005.11a
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• pp.49-50
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• 2005

This paper presents a scheme for state observer-based stabilization control of inverted pendulum systems. The feedback gain matrices of both the state feedback controller and the state observer are obtained by a real-coded genetic algorithm(RCGA) such that the given performances indices are minimized.

• Journal of Navigation and Port Research
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• v.31 no.3 s.119
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• pp.247-252
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• 2007

The container crane is one of the most important equipments at container terminal. If its working time in cycle could be reduced then container terminal efficiency and service level can be increased. So there are many i1forts to reduce working time of container cranes. It means how to design the controller with good performance which has small overshoot and swing motion of container crane. We, in this paper, present a state feedback controller based on LQ theory incorporating a RCGA which means real-coded genetic algorithm RCGA can search state feedback gains under given objective function. A set of simulation works are carried out in order to prove the control effectiveness of the proposed methods.