• Proceedings of the KIEE Conference
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• 2002.07d
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• pp.2382-2384
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• 2002

The accuracy in maneuvering target tracking using multiple models is caused by the suitability of each target motion model to be used. The interacting multiple model (IMM) algorithm and the adaptive IMM (AIMM) algorithm require the predefined sub-models and the predetermined acceleration intervals, respectively, in consideration of the properties of maneuvers in order to construct multiple models. In this paper, to solve these problems intelligently, a genetic algorithm (GA) based-IMM method using fuzzy logic is proposed. In the proposed method, the acceleration input is regarded as an additive noise and a sub-model is represented as a set of fuzzy rules to model the time-varying variances of the process noises of a new piecewise constant white acceleration model. The proposed method is compared with the AIMM algorithm in simulations.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2837-2839
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• 2000

We design a stable controller for a mobile robot with variable gains and reference velocity in order to apply the proper gains and reference velocity, which are generated with fuzzy logic in on-line. The stability is guranteed by the Lyapunov theory. The fuzzy logic rules is found in off-line with GA strategy which drives each object function to be the least. The proposed controller is applied smooth path tracking due to the local path planing. Simulation results show robust performances under a different initial conditions.

• ETRI Journal
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• v.27 no.3
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• pp.243-249
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• 2005

A mobile antenna for multimedia communications with Ku-band geostationary satellite KOREASAT-3 and JSAT-2A is presented. The forward link of the satellite communication is 11.7 to 12.75 GHz, and the return link is 14.0 to 14.5 GHz. The mobile antenna is designed to be a stair structure using 24 active phased array elements in order to provide a low profile, and to be at a non-periodic array distance using the genetic algorithm. Also, the designed antenna uses the double beam forming method for stable satellite tracking. The fabricated mobile antenna is examined using various experiments to confirm its capability for practical application. From the measured results, the fabricated mobile antenna system is confirmed to have a good performance.

• Proceedings of the KIEE Conference
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• 1999.11c
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• pp.530-532
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• 1999

In adaptive fuzzy control, system designer develops an adaptive law for the output of the unknown plant to track a given signal. The adaptation gains of the adaptive law are critical elements in the overall system, however, they were used to be selected by the designer's experience or intuition. In this paper, genetic algorithm is used to search an optimal adaptation gain and simulation results will be presented to show the improved tracking responses.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.10 no.4
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• pp.40-47
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• 2001

In this pater, the QLQG/LTR control method is applied for the position control of the nonlinear timing belt driving sys-tem. Parameters fo the plant are identified by genetic algorithm and nonlinear elements, such as Coulomb friction and dead-zone, and quasi-linearized by RIDE method. Comparing with the LQG/LTR contro. the QLQG/LTR has similar structures of the LQG/LTR, but this method can consider nonlinear effects in designing the controller. Thus, the QLQG/LTR control system is robust to hard nonlinearities such as Coulomb friction, dead-zone, etc. Forma given hard non-linear system through experiments, it is shown that the tracking performance of the QLQG/LTR control system can be very improved that the LQF/LTR control system.

• Journal of Advanced Marine Engineering and Technology
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• v.30 no.6
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• pp.753-759
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• 2006

Integrating processes are frequently encountered in process industries. In this paper, new tuning formulae of the PID controllers for set-point tracking and load disturbance rejection are presented for integrating processes involving time delay. First, the controller parameter sets are tuned using a real-coded genetic algorithm (RCGA) such that performance criterion(IAE, ISE or ITSE) is minimized. Then, tuning rules are addressed using tuned PID parameter sets. tuning model and another RCGA. The performances of the proposed rules are tested on two processes.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.6
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• pp.656-666
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• 1999

In this paper, we design the optimal PD control system which has the robust performance. This PD control system is designed by applying genetic algorithm (GA) to the determination of proportional gain KP and derivative gain KD that are given by PD servo controller, to make the output of plant follow the output of reference model optimally. These proportional and derivatibe gains are simultaneously optimized in the search domain guaranteeing the robust performance of system. And, this PD control system is compared with $\mu$ -synthesis control system for the robust performance. The PD control system designed by the proposed method has not only the robust performance but also the better command tracking performance than that of the $\mu$ -synthesis control system. The effectiveness of this control system is verified by computer simulation.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.1
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• pp.35-42
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• 1998

This paper presents the introduction of Pseudo-2 axes robot module and its GA-based fuzzy control implementation. Pseudo-2 axes robot module which use a single motor and controller for driving 2 joints of a robot mechanism, is devised towards a lower priced robot with its degree of freedom maintained GA-based Fuzzy controller is considered for the better control implementation of the developed system than the conventional PID controller. Here. the scaling factors of the membership function with high fitness values are selected using a genetic algorithm for a pulse-type input trajectory. The obtained controller also shows better trajectory tracking performance than a PID controller.

• Proceedings of the KIEE Conference
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• 1997.11a
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• pp.130-132
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• 1997

This paper proposes a reference model following control system using fuzzy logic controller and genetic algorithm. A fuzzy logic controller is designed such that plant output follows the output generated by a reference model. In this paper, First-order and second-order reference model with no overshoot and fast rise time is designed. Experiment results show the effectiveness of the proposed controller in tracking property and robustness.

• Journal of Korean Institute of Industrial Engineers
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• v.37 no.4
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• pp.382-389
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• 2011

Salesperson Monitoring System (SMS) is geographic based information system that supports business auditing, sales area coordinating and customer management for each salesperson. Conventional SMSs focus mainly on the monitoring or logging functions, i.e., a salesperson locating or moving trail tracking. However, the schedules have been planned by human planner, and they have rarely been managed with a software system like SMS. In this paper, a mixed integer programming model for a salesperson routing schedule is provided. Then, 2-phase Genetic Algorithm (GA) is proposed to make salesperson routing schedule. Experimental results show a validity of the proposed method.