• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.1
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• pp.60-67
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• 1998

In this paper, a gain scheduling method of PID controller is proposed using fuzzy logic for balancing control of an inverted pendulum. First, gains of PID controller are calculated using pole-placement technique for the linearized model of an inverted pendulum and these gains are modified by fuzzy logic throughout control operations. A PD controller is used by switching near the set-point to improve the performance. It is illustrated by simulations that the proposed hybrid fuzzy control method yidels smaller rising time and overshoot compared to the fixed-gain PID controller or fuzzy logic-based only PID controller.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.4
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• pp.296-303
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• 2007

This paper proposes a new width control system composed of an ANWC(Automatic Neural network based Width Control) and a fuzzy-PID controller in hot strip finishing mills which aims at obtaining the desirable width. The ANWC is designed using a neural network based width prediction model to minimize a width variation between the measured width and its target value. Input variables for the neural network model are chosen by using the hypothesis testing. The fuzzy-PlD control system is also designed to obtain the fast looper response and the high width control precision in the finishing mill. It is shown through the field test of the Pohang no. 1 hot strip mill of POSCO that the performance of the width margin is considerably improved by the proposed control schemes.

• Transactions of the Korean Society of Automotive Engineers
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• v.9 no.1
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• pp.139-147
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• 2001

In this study a path control scheme of simulation models of various vehicles to evaluate their handling characteristic is developed. Based on the forward target method, path deviation error is estimated and the required steering effort to reduce the error is computed by Ziegler-Nichols PID control rule. Velocity control model is also included in the proposed path control scheme to achieve the desired velocity. The path control scheme is implemented on a full vehicle model to perform ISO test procedures, such as steady state cornering, lane change, and sinusoidal input, etc. Through the simulations of ISO test procedures and comparison with actual tests, effectiveness and validity of the path control model is demonstrated.

• Journal of Advanced Marine Engineering and Technology
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• v.26 no.6
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• pp.638-645
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• 2002

This paper presents a scheme for integrating PID control, gain scheduling and emerging techniques in the field of artificial intelligence, such as fuzzy logic and genetic algorithms for the speed control of a marine diesel engine. At first, local PID controllers are designed based on a local model obtained at each speed mode, whose parameters are optimally tuned using a real-coded genetic algorithm. Then, fuzzy "if-then" rules combine the local controllers as a consequence part to implement fuzzy gain scheduling. To demonstrate the performance of the proposed fuzzy PID controller on overall operating conditions, a set of simulation works on B'||'&'||'W's 4L80MC diesel engine are carried out.t.

• Journal of KSNVE
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• v.11 no.2
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• pp.292-300
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• 2001

This research is concerned with the validation of the modeling technique and controller design for slewing beam structures. When cantilever beam rotates about axes perpendicular to the undeformed beam's longitudinal axis, it experiences inertial loading. Hence, the beam vibrates from the initial stage of slewing. In this paper, the analytical model for a single slewing flexible beam with surface bonded piezoelectric sensor and actuator is developed using the Hamilton's principle with discretization by the assumed mode method. Comparisons with the theoretical model are made based upon the frequency responses and time responses. A new factor called the coupling coefficient is introduced to incorporate the discrepancies between the theoretical and experimental results. The slewing is achieved by applying the PID control, which is found to be less sensitive to vibrations. The vibrations are controlled by PPF controller, which is found to be effective in suppressing residual vibrations after slewing. The vibrations occurred during slewing is difficult to control because the piezoceramic actuator is not powerful enough to overcome inertial loadings.

• Proceedings of the KIEE Conference
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• 2002.07d
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• pp.2445-2447
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• 2002

In this paper, CAN-based feedback control system is proposed for the pressurization system of korean high-speed train. The control performance of the system is evaluated. According to the requirement of the pressurization system A process model considering network delay and an adaptive PID control method based on the process model are proposed here. And it is shown that the proposed adaptive PID control method considering the network delay has on adequate feature compared to some other existing methods consequently it can be considered to be applied the pressurization system of korean high-speed train.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.4
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• pp.201-212
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• 2000

In this paper, an adaptive mechanism based on immune algorithm is designed and it is applied for the autonomous guided vehicle(AGV) driving. When the immune algorithm is applied to the PID controller, there exists the cast that the plant is damaged due to the abrupt change of PID parameters since the parameters are adjusted almost randomly. To solve this problem, a neural network is used to model the plant and the parameter tuning of the model is performed by the immune algorithm. After the PID parameters are determined in this off-line manner, these gains are then applied to the plant for the on-line control using immune adaptive algorithm. Moreover, even though the neural network model may not be accurate enough intially, the weighting parameters are adjusted to be accurate through the on-line fine tuning. The computer simulation for the control of steering and speed of AGV is performed. The results show that the proposed controller has better performances than other conventional controllers.

• Proceedings of the KIEE Conference
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• 2005.05a
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• pp.72-74
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• 2005

In this paper, we propose an adaptive PID controller using a cell-mediated immune response to improve a PID control performance. The proposed controller is based on the specific immune response of the biological immune system that is cell-mediated immunity. The immune system of organisms in the real body regulates the antibody and the T-cells to protect an attack from the foreign materials like virus, germ cells, and other antigens. It has similar characteristics that are the adaptation and robustness to overcome disturbances and to control the plant of engineering application. We first build a model of the T-cell regulated immune response mechanism and then designed an I-PID controller focusing on the T-cell regulated immune response of the biological immune system. We apply the proposed methodology to building structures to mitigate vibrations due to strong winds for evaluation of control performances. Through computer simulations, system responses are illustrated and additionally compared to traditional control approaches.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.2
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• pp.209-214
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• 1998

In this paper, we are dealing with the problem of controlling unknown nonlinear dynamical system by using neural networks. A novel error self-recurrent(ESR) neural model is presented to perform black-box identification. Through the various outcome of the experiment, a new neural network is seen to be considerably faster than the BP algorithm and has advantages of being less affected by poor initial weights and learning rate. These characteristics make it flexible to design the controller in real-time based on neural networks model. In addition, we design an adaptive PID controller that Keyser suggested by using ESR neural networks, and present a method on the implementation of adaptive controller based on neural network for practical applications. We obtained good results in the case of robot manipulator experiment.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.20 no.2
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• pp.129-137
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• 2010

This paper presents a position tracking control of a flexible beam using the piezoelectric actuator. This is achieved by implementing both feedforward hysteretic compensator of the actuator and PID feedback controller. The Preisach model is adopted to develop the feedforward hysteretic compensator. In the design of the compensator, estimated displacement of the piezoceramic actuator is used based on the limiting triangle database that results from collecting data of the main reversal curve and the first order ascending curves. Experimental implementation is conducted for position tracking control and performance comparison is made between a PID feedback controller without considering the effect of hysteresis, and a PID feedback controller integrated with the feedforward hysteretic compensator.