• Proceedings of the KIEE Conference
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• 2001.07e
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• pp.58-61
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• 2001

The purpose of this paper is a fuzzy logic controller for XY positioning system. The overall control system consists of three parts, the position controller, the speed controller, the fuzzy logic controller. Precise tracking is achieved by fuzzy logic controller. In practice, such systems contain many uncertainties. Therefore, the XY positioning system must receive and evaluate the motion of all axis for a better contouring accuracy. Cross coupled controller utilizes all axis position error information simultaneously to produce accurate contours. However, the existing Cross coupled controllers cannot overcome friction, backlash and parameter variation. So, we propose a fuzzy logic controller of XY positioning system. Experimental results show that the proposed fuzzy logic controller is effective to improve the contouring accuracy of XY positioning system.

• Journal of Advanced Marine Engineering and Technology
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• v.10 no.1
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• pp.51-64
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• 1986

Recently, being due to development of a small microprocessor, microprocessor have found increasing application as a digital controller in the control system. In this paper, authors analyze theoretically the continuous PID controller of a position control system with servomotor, and program the microprocessor as digital PID controller by an assembly language, and search the optimal parameters of the digital PID controller which make the smallest integral square error criterion for a performance criterion, and take experiment the indicial responses with optimal parameter. The results are following. 1) PD- behavior controller was better than P-behavior controller. 2) The smaller the smapling times of P-behavior controller and PD-behavior controller were, the better the indicial responses of the discrete system were. 3) Using a small microprocessor could replace the traditional continuous PID controller for good control.

• Journal of Aerospace System Engineering
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• v.12 no.3
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• pp.45-52
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• 2018

This paper deals with the analysis of the inner-loop algorithm of the Pixhawk which is a representative multi-copter open source. The algorithm is based on flight control-law structure. The inner-loop algorithm of the Pixhawk can be divided into a position controller and an attitude controller. The position controller generates the attitude of the multi-copter to move to the destination The position controller also generates the demand force and moment acting on each actuator. We confirm that the position controller saturates the desired acceleration and speed by using a proper relational expression. The expression can be used in order to prevent the sudden change in the attitude of a multi-copter.

• Journal of KSNVE
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• v.10 no.6
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• pp.1083-1093
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• 2000

This paper is concerned with the real-time automatic tuning of the positive position feedback controller for smart structures by the genetic algorithms. The genetic algorithms haute proven its effectiveness in searching optimal design parameters without falling into local minimums thus rendering globally optimal solutions. The advantage of the positive position feedback controller is that if it is tuned properly it can enhance the damping value of a target mode without affecting other modes. In this paper, we develop for the first time a real-time algorithm for determining a tuning frequency of the PPF controller based on the genetic algorithms. To this end, the digital PPF control law is downloaded to the DSP chip and a main program, which runs the genetic algorithms in real time, updates the parameter of the controller in real time. Hence, any kind of control including the positive position feedback controller can be used in adaptive fashion in real time. Experimental results show that the real-time tuning of the positive position feedback controller can be achieved successfully. so that vibrations are suppressed satisfactorily.

• Proceedings of the KIEE Conference
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• 2004.07d
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• pp.2501-2503
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• 2004

In this paper, we propose an auto-tuning control algorithm for a mobile robot. This controller consists of a three layer neural networks and a PID controller. In order to compensate for uncertainties from unknown dynamics and ignored dynamic effects such as slip conditions, neural network based position schemes are proposed. The results of simulations show the validity of proposed method. This controller learns quickly the model and has good position control performance.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.658-663
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• 1992

In this paper, the control of a DC servo motor position control is implemented with fuzzy controller using IBM PC AT. In addition to the fuzzy controller with the error and change of error inputs PI controller is applied as well to improve the steady state error response. It shows the above configuration results in a good control characteristics.

• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.6 no.4
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• pp.60-68
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• 1992

In this paper, an implementation approach of Fuzzy Position Controller for DC servo motor which requires the faster and more accurate dynamics is presented. Fuzzy position controller implemented with 80286 microprocessor and DT 2801 board consists of an adjustment routine of optimal scale factors and a Fuzzy inference routine of optimal control signals. Comparison to conventional PD controllers, the control performances of proposed Fuzzy controller such as reaching time, overshoot, and disturbance adaptability are substantially improved.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.9 no.4
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• pp.294-300
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• 2009

The neural network with radial basis function is introduced for position tracking control of AC servo drive with the existence of system uncertainties. An adaptive robust term is applied to overcome the external disturbances. The proposed controller is implemented on a high performance digital signal processing DSP TMS320C6713-300. The stability and the convergence of the system are proved by Lyapunov theory. The validity and robustness of the controller are verified through simulation and experimental results

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2003.06a
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• pp.145-148
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• 2003

In this paper an nonlinear neuro PID controller is constructed by the control system of general PID controller using a Self-Recurrent Neural Network. And the games of the PID controller in the proposed control system are automatically adjusted by back-propagation algorithm of the neural network. Applying to the position control system, it's performance is verified through the results of computer simulation.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.5
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• pp.972-980
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• 2010

In this study, we introduce the design methodology of an optimized type-2 fuzzy cascade controller with the aid of hierarchical fair competition-based genetic algorithm(HFCGA) for ball & beam system. The ball & beam system consists of servo motor, beam and ball, and remains mutually connected in line in itself. The ball & beam system determines the position of ball through the control of a servo motor. Consequently the displacement change of the position of the moving ball and its ensuing change of the angle of the beam results in the change of the position angle of a servo motor. The type-2 fuzzy cascade controller scheme consists of the outer controller and the inner controller as two cascaded fuzzy controllers. In type-2 fuzzy logic controller(FLC) as the expanded type of type-1 fuzzy logic controller(FLC), we can effectively improve the control characteristic by using the footprint of uncertainty(FOU) of membership function. The control parameters(scaling factors) of each fuzzy controller using HFCGA which is a kind of parallel genetic algorithms(PGAs). HFCGA helps alleviate the premature convergence being generated in conventional genetic algorithms(GAs). We estimated controller characteristic parameters of optimized type-2 fuzzy cascade controller applied ball & beam system such as maximum overshoot, delay time, rise time, settling time and steady-state error. For a detailed comparative analysis from the viewpoint of the performance results and the design methodology, the proposed method for the ball & beam system which is realized by the fuzzy cascade controller based on HFCGA, is presented in comparison with the conventional PD cascade controller based on serial genetic algorithms.