• Journal of the Institute of Convergence Signal Processing
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• v.5 no.2
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• pp.138-142
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• 2004

This paper proposes the design of the model following control system using the PID control structure. PID control system became model following control by inserting new pre-compensator in order to improve control performance in discrete-time region. Gain of the PID controller needs to be readjusted when response of system changes due to disturbance or load fluctuation. Performance of control system improves by joining neural network to PID control system because performance of control system depends largely on each PID gain in PID control system. And the games of the PID controller in the proposed control system are automatically adjusted by back-propagation algorithm of the neural network. Angular position of DC servo motor is selected as a plant in order to verify control performance in model following control. After it is applied to the position control system, it's performance is verified through computer experiment.

• 제어로봇시스템학회:학술대회논문집
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• 1986.10a
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• pp.456-458
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• 1986

A method for on-line tuning of the PID-controller parameters for a discrete-time multivariable process system is presented. And it is based on a step change in the controller set point. The system is presumed to be a linear, open loop stable and known one. The controller parameters are determined by the performance criterion and Fletcher-Powell methods.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.2 no.1
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• pp.19-26
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• 1998

In this paper, Simulation result was studied by PID controller in series to the estblised neural networks controller. Neural network model is composed of two layers to evaluate tracking performance improvement. The regular dynamics was also studied for the expected error to be minimized by using Widrow-Hoff delta rule. As a result of the study, We identified that tracking performance improvement was developed more in case of connecting PID than conventional neural network controller and that tracking plant parameter in 251 sample was approached rapidly in case of time varying.

• Proceedings of the KSME Conference
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• 2001.06b
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• pp.99-104
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• 2001

Discrete-time controller design is proposed using feedback system identification in frequency domain. System Stability imposed by a new controller is checked in the function of a conventional closed-loop system, instead of a poorly modeled plant due to non-linearity and disturbance as well as unstable components, etc. The stability of the system is evaluated in view of Popov criterion. All the equations are formulated in the framework of the discrete-time system. Simulation results are shown on the plant with input saturation components, DC disturbance and a pure integration.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2006.06a
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• pp.85-88
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• 2006

Many control techniques have been proposed in order to improve the control performance of the discrete-time domain control system. In the position control system, the output of a controller is generally used as the input of a plant but the undesired noise is include in the output of a controller. In this paper, the neuro-network 2-DOF PID Controller is designed by a neural network and the gains of this controller are adjusted automatically by the back-propagation algorithm of the neural network when the response characteristic of system is changed under a condition.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.5
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• pp.139-147
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• 1996

PID control has been widely used for real control systems. Particularly, there are many researches on control schemes of tuning PID gains. However, to the best of our knowledge, there is no result for discrete-time systems with unknown time-delay and unknown system parameters. On the other hand, Generalized predictive control has been reported as a useful self-tuning control technique for systems with unknown time-delay. So, in this study, based on minimization of a GPC criterion, we present a self-tuning PID control algorithm for unknown papameters and unknown time-delay system. A numerical simulation was presented to illustrate the effectiveness of this method.

• International Journal of Precision Engineering and Manufacturing
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• v.2 no.4
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• pp.54-60
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• 2001

This paper deals with control design method having anticipation delay which is proposed for the discrete nonlinear engine where system dynamics is not accurate. Due to the induction-to-power delay in internal combustion(IC) engine having abrupt torque loss, underdamping and chattering in engine idle speed becomes a serious problem and it could make drivers uncomfortable. For this reason, Three types of the closed-loop controller are developed for the stable engine idle speed control. The inputs of the controllers are an engine idle speed and air conditioning signal. The output of the controllers is an duty cycle to operate the idle speed control valve(ISCV). The proposed controllers will be useful for improving actual vehicles since these shows good test

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.4
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• pp.441-447
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• 1998

Motivated by a recent work, a fuzzy-power-controller(FPC) is designed for the relieving-horsepower control of output variable pump with electrical proportional valve and actually implemented on the industrial excavator. In order to calculate the output power of pump with input of FPC, a linear discrete time model of load system to pump is obtained and the result is applied to control the engine-pump coupled system by software without pressure and flow sensor. The FPC controls the engine and pump coupled system by relieving horsepower control according to the change of load and the running conditions in relieving horsepower control are selected by fuzzy inference engine. A case study is peformed through the construction of the control device and installation on the excavator. It shows that the relieving-horsepower control system with the FPC, as suggested in this paper, is superior to the conventional PID controllers. And also, the excavator, with the FPC, shows that the power-loss of the coupled system is reduced and the running speed of the hydraulic actuator is enhanced.

• Proceedings of the KIEE Conference
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• 1992.07a
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• pp.333-336
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• 1992

In this paper, We propose a PID-type of self-tuning algorithm which is based on the parameter estimation and the minimization of the cost function. We use the CARIMA model for parameter estimation and determine the discrete PID controller parameters by minimizing the cost function which considers the quadratic deviations of the predicted output over the set-point as well as the control efforts. Also, The algorithm is extended by incorporating constraints of the control signal. Simulations are performed to illustrate the efficiency of the proposed method.

• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.293-295
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• 1993

Most control system design problems involve finding state feedback gain for good response by the pole or characteristic polynomial assignment. In this paper, the characteristic polynomial assignment using PID controller for discrete 2-dimensional system descrived by the Fornasini-Marchesini's 2nd model (F-MM II) is considered. This method it not only available to F-MM II but also to Rosser's model.