• Journal of Satellite, Information and Communications
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• v.11 no.4
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• pp.39-43
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• 2016

In this paper, we propose PID gain auto tuning method in steering type mobile robot. PID controller gain select method are various methods. Ziegler-Nichols step tuning method is one method tuning in PID controller. Use step tuning method find a the first gain and did experiment in steering mobile robot. and Make a new the second gains from the first gains. After appling the second gain in PID controller, Where perform observe for convergence time and stabilization error. Experiments result the second gain are useful in real steering mobile robot system.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.8
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• pp.1811-1817
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• 2014

In this paper, a PID controller with interpolated gains by use of neural networks is proposed for the formation control problem that following robots track a leading robot with constant distances and angles when there are changes in the mass of the following robot. The whole control system is composed of a kinematic controller and a dynamic controller considering the robot dynamics. The dynamic controller is the PID controller with varying gains, and the proper gains are obtained for some representative masses of the follower robot by the genetic algorithm. Neural networks is trained using the genetic algorithm with the gain data obtained in the previous step. The trained neural network determines optimal PID gains for a random mass of following robot. Simulation studies show that for arbitrary masses of the tracking robot, the PID controller with interpolated gains by the trained neural network has better tracking performance than that of the PID controller with fixed gains.

• Proceedings of the KIEE Conference
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• 2005.07d
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• pp.2510-2512
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• 2005

본 논문은 선형시불변시스템(LTI) 대하여 안정도여유(이득 및 위상여유)와 시간응답 규격(오버슈트와 응답속도)을 보장하는 PID 제어기의 이득 셋을 결정하는 방식을 제시한다. 이 방법은 시스템을 안정화시키는 전체 PID 제어기의 이득 셋을 결정하는 최근의 결과를 이용한다[1]. 본 논문에서는 폐루프 특성다항식의 계수공간에서 계수와 안정도여유 및 시간응답 성능요구 조건과의 관계를 제시한다. 제시한 방법을 이용하여 안정도를 보장하고 안정도여유와 시간영역 규격을 동시에 만족하는 PID 이득 셋을 구한다. 예제를 통해 실제 설계에 매우 유용함을 보였다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.3
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• pp.536-544
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• 2011

In this paper, a controller for two wheeled inverted pendulum type robot is designed to have more stable balancing capability than conventional controllers. Traditional PID control structure is chosen for the two wheeled inverted pendulum type robot, and proper gains for the controller are obtained for specified user's weights using trial-and-error methods. Next a neural network is employed to generate PID controller gains for more stable control performance when the user's weight is arbitrarily selected. Through simulation studies we find that the designed controller using the neural network is superior to the conventional PID controller.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.1
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• pp.1-6
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• 2013

For regulating generator speed above the rated wind, versatile methods have been published based on PID. However, these methods with the fixed PID gains could not guarantee that the controller works well in the whole area. In this paper, variable PID gain method has been suggested to overcome this problem. The sensitivity of power to blade pitch angle changes according to wind speed. The variable PID gain function has been derived from this sensitivity.

• Journal of the Korea Convergence Society
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• v.11 no.11
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• pp.195-201
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• 2020

This paper implemented quadcopter-type drone system and proposed the heuristic method for obtaining the optimum gain coefficients in order to minimize the settling time. Control system for quadcopter posture stabilization reads the posture data from accelerator and gyro sensor, revises the original posture data using Mahony filter, and drives 4 DC motors using PID controller. The first step of the proposed method is to obtain the gain coefficients using the Ziegler-Nichols method, and then determine the optimum gain coefficients using the heuristic method at the next 3 steps. The experimental result shows that the maximum overshoot decreases from 44.3 to 29.8 degrees and the settling time decreases from 2.6 to 1.7 seconds compared to the Ziegler-Nichols method. Therefore, we proved that the proposed method works well in quadcopter flight system with high motor noise while reducing trial and error to obtain the optimal PID gain coefficients.

• 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.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.9
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• pp.1871-1880
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• 2011

In this paper, a controller for two wheeled inverted pendulum robot, i.e., Segway type robot that is a convenient and easily handled vehicle is designed to have more stable balancing and faster velocity control compared to the conventional method. First, a widely used PID control structure is applied to the two wheeled inverted pendulum robot and proper PID control gains for some specified weights of users are obtained to get accurate balancing and velocity control by use of experimental trial-and-error method. Next, neural network is employed to generate appropriate PID control gains for arbitrarily selected weight. Here the PID gains based on the trial-and-error method are used as training data. Simulation study has been carried out to find that the performance of the designed controller using the neural network is more excellent than the conventional PID controller in terms of faster balancing and velocity control.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.1
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• pp.88-95
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• 2006

PID controllers, which have been widely used in industry, have a simple structure and robustness to modeling error. But They we difficult to have uniformly good control performance in system parameters variation or different velocity command. In this paper, we propose a nonlinear adaptive PID controller based on a cell-mediated immune response and a gradient descent learning. This algorithm has a simple structure and robustness to system parameters variation. To verify performances of the proposed nonlinear adaptive PID controller, the speed control of nonlinear DC motor is performed. The simulation results show that the proposed control systems are effective in tracking a command velocity under system parameters variation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.10C
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• pp.1370-1377
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• 2004

Optimal control gain for time-delay systems is made by an optimal control gain for delay-free systems multiplied by a state transition function for the delay time. The optimal control gain for delay-free systems is obtained by pushing two zeros of the PID controller closely to a larger pole of the second order plant. Thus the optimal tuning of PID controller for time-delay second order system is able to be obtained by calculation for the state transition function.