• Journal of Power Electronics
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• v.18 no.3
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• pp.723-735
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• 2018

Linear proportional-integral (PI) controllers are an attractive choice for controlling the speed of induction machines because of their simplicity and ease of implementation. Fractional-order PI (FO-PI) controllers, however, perform better than PI controllers because of their nonlinear nature and the underlying iso-damping property of fractional-order operators. In this work, an FO-PI controller based on the proposed first-order plus dead-time induction motor model and integer-order (IO) controllers, such as Ziegler-Nichols PI, Cohen-Coon PI, and a PI controller tuned via trial-and-error method, is designed. Simulation and experimental investigation on an indirect field-oriented induction motor drive system proves that the proposed FO-PI controller has better speed tracking, lesser settling time, better disturbance rejection, and lower speed tracking error compared with linear IO-PI controllers. Our experimental study also validates that the FO-PI controller maximizes the torque per ampere output of the induction machine and can effectively control the motor at low speed, in field-weakening regions, and under detuned conditions.

• Journal of Power Electronics
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• v.10 no.2
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• pp.171-175
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• 2010

This paper introduces the application of a SUI PID controller for permanent magnet (PM) drive systems. The drive system model is developed via FO control. Simulation of the system is carried out to predict the performance at no load and under load. The results and comparisons indicate that application of a SUI PID controller is effective for sensorless PM drive systems.

• Journal of Power Electronics
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• v.19 no.4
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• pp.835-845
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• 2019

This paper presents a robust-optimal control strategy to improve the output-voltage error-tracking and control capability of a DC-DC boost converter. The proposed strategy employs an optimized Fractional-order Proportional-Integral (FoPI) controller that serves to eliminate oscillations, overshoots, undershoots and steady-state fluctuations. In order to significantly improve the error convergence-rate during a transient response, the FoPI controller is augmented with a pre-stage nonlinear error-modulator. The modulator combines the variations in the error and error-derivative via the signed-distance method. Then it feeds the aggregated-signal to a smooth sigmoidal control surface constituting an optimized hyperbolic secant function. The error-derivative is evaluated by measuring the output-capacitor current in order to compensate the hysteresis effect rendered by the parasitic impedances. The resulting modulated-signal is fed to the FoPI controller. The fixed controller parameters are meta-heuristically selected via a Particle-Swarm-Optimization (PSO) algorithm. The proposed control scheme exhibits rapid transits with improved damping in its response which aids in efficiently rejecting external disturbances such as load-transients and input-fluctuations. The superior robustness and time-optimality of the proposed control strategy is validated via experimental results.

• Journal of Advanced Marine Engineering and Technology
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• v.23 no.2
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• pp.227-235
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• 1999

In this paper a vibration control fo a one-link flexible beam is considered. At first a state-space model for a flexible beam is derived by using the assumed-modes approach. Based on this model the transfer function between the applied torque and the tip deflection fo the beam is presented because it is convenient to apply our method. In general there exist some control difference due to flexibility of the beam so we adop a forward-passive controller to reduce these phenomena. And a complex dual-input describing function compensator is used to control the tip deflection. The stabiltiy and the performance of the closed-loop system are analyzed. Finally the validity of the derived model and the effectiveness of proposed controller are confirmed throuth simula-tions and experiments.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.6
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• pp.1-10
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• 1997

This paper presents an adaptive optimal learning controller for uncertian robot systems which makes use fo simple DNN(dynamic neural network) units to estimate uncertain parameters and learn the unknown desired optimal input. With the aid of a lyapunov function, it is shown that all that error signals in the system are bounded and the robot trajectory converges to the desired one globally exponentially. The effectiveness of the proposed controller is hsown by applying the controller to a 2-DOF robot manipulator.

• Journal of Advanced Marine Engineering and Technology
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• v.23 no.1
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• pp.40-46
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• 1999

A self-tuning FPID(Fuzzy Proportional Intergral Derivative) controller fo load frequency control of 2-area power systemis proposed in this paper. The paramters of the proposed self-tuning FPID controller are self-tuned by the proposed fuzzy inference technique. Therefore in this paper the fuzzy inference technique of PID gains using PSGM(Product Sum Gravity Method) is presented and is applied to the load frequency control of 2-area power system. The computer simulation results show that the proposed controller give better more control characteristics than convention-al PID, FLC under load changes.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.7
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• pp.582-588
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• 2001

The Multiple Model/Controller IMC(MMC-IMC) is a model-based control method which uses a set of model/controller pairs rather than a single model/controller to handle all possible operating conditions in the IMC control structure. During operation, one model/controller pair that best fit, for current plant situation is chosen by the switching algorithm. The major drawback of the switching controller is the bad transient performance due to the model error and the use fo linear controller for nonlinear plants. In this paper, we propose a method that transient response of the MMC-IMC using two recurrent neural networks. Simulation result shows that the proposed method represents better performance than the usual MMC-IMC`s.

• Journal of Ocean Engineering and Technology
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• v.15 no.1
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• pp.67-72
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• 2001

In this study, a methodology of synchronous control which can be applied to position synchronization of a two-axes driving system has been developed. The synchronous error is caused by model uncertainties and torque disturbance of each axis. To overcome these problems, the proposed synchronous control system has been composed of two speed controllers, disturbance observers, and one synchronous controller. The speed controllers, based on the PID control law are aimed at the following to speed reference. And the parameters of speed controllers have been designed in order for the speed response fo the second axis to correspond with the one of the first axis. The disturbance observer has been designed to restrain the torque disturbance. The synchronous controller eliminates the synchronous error by controlling the speed of the second axis. The effectiveness of the proposed method has been verified through simulation.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.49 no.1
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• pp.62-69
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• 2000

The strip tension as well as the line speed should be controlled tightly for the quality of products and productivity of the continuous strip processing line. In this paper, a new tension control algorithm with tension observer is proposed using observed tension as regulator feedback. The tension observer is based on the torque balance of a roller stand including the acceleration torque. Using this estimated tension, new tension controller can be constructed with faster dynamic response in case of line speed acceleration or deceleration. The proposed scheme needs no additional hardware because the inputs of observer, current and speed, are already being monitored by the motor drive system. Through the simulations and experiments with laboratory set up, performances fo conventional schemes and proposed one are compared. The results show the effectiveness of the proposed tension controller.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.16 no.7
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• pp.610-614
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• 1991

This paper proposes a trajectory constrol fo a robot manipulator by using neural network. The inverse dynamic model of manipuator is learned by neural network. The manipulator is controlled by weight values of the learned neural network. The weight valuese is change with a torque of liner vontroller and a acceleration error. Phsically, the totlal torque for a manipualator is a sum of the liner controller torque and the nerural network controller torque. The proposed control effect is estimated by computer simulation.