• 한국정밀공학회지
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• 제21권10호
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• pp.65-77
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• 2004

In this paper, we propose an adaptive mechanism based on immune algorithm and neural network identifier technique. It is also applied fur an autonomous guided vehicle (AGV) system. When the immune algorithm is applied to the PID controller, there exists the case that the plant is damaged due to the abrupt change of PID parameters since the parameters are almost adjusted randomly. To solve this problem, we use the neural network identifier (NNI) technique fur modeling the plant and humoral immune algorithm (HIA) which performs the parameter tuning of the considered model, respectively. 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 an immune adaptive algorithm. Moreover, even though the neural network model may not be accurate enough initially, the weighting parameters are adjusted to be accurate through the on-line fine tuning. Finally, the simulation and experimental result fur the control of steering and speed of AGV system illustrate the validity of the proposed control scheme. These results for the proposed method also show that it has better performance than other conventional controller design methods.

• 대한전기학회논문지
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• 제39권4호
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• pp.364-370
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• 1990

In this paper, we propose a self-tuning PID controller for unknown systems with time-varying delay. Using pole placement equations, we derive the controller that can be extended to the multi-step time delay case. The time-varying delays are estimated by a prediction error delay method using multiple predictors. Since the order of the estimation vector is not increased, the persistant exciting condition of control input is alleviated. Since the least square method gives biased parameter estimates for colored noise cases, the recursive instrumental variable method is used to estimate system parameters. The computational burden of the proposed method is less than the conventional adaptive methods. Computer simulations are performed to illustrate the efficiency of the proposed method.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1996년도 하계학술대회 논문집 B
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• pp.1110-1112
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• 1996

In this paper, we propose a new approach for robust auto-tuning of PID gains using Evolution Strategy. Evolution Strategy is searching algorithm which imitate the principles of natural evolution as a method to solve parameter optimization problem and easy to use without any other special mathematical theory. Through the simulation of the speed control of a series-connected de motor, our proposed method shows more improved performance by finding optimal parameters of PID controller than a classical Ziegler-Nichols method.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1993년도 하계학술대회 논문집 A
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• pp.366-368
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• 1993

In this paper, we present an approach to automatically tune and adapt PID parameters by using Fuzzy Logic. PID controllers are well-known and found in many industries. Although the potentials of PID controllers, PID controllers are often poorly tuned and their capabilities are not fully used. We can think that the tuning of PID parameters is based on heuristics and some rule of thumbs. This is the reason we come to use Fuzzy Logic. We show that by imbedding heuristics and some rule of thumbs in PID controllers, reperesented by Fuzzy Logic. we can make PID controllers be robust to uncertainties such as load variations and adapt parameter changes.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2005년도 춘계학술대회 논문집
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• pp.1836-1840
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• 2005

This work proposes a controller tuning method of a Hyundai 8608 robot in order to improve its performance. For this, we analyzed the control structure of the robot, and the functions of all the adjustable parameters in the robot controller with a reference 'NACHI Technical Report'. Through the analysis, we found out that 3 important parameters(VRRL, VRF, VRGIN) act like a conventional PID gains and other parameters are closely related to these 3 parameters. Conclusively, parameter tuning of these 3 parameters is enough in most cases of applications with other parameters fixed. The conventional PID tuning is performed to each joint of the test robot with Robot Performance Evaluation System(shown in our companion paper) so that the acceptable gain ranges for each joint are determined and then the robot performance tests are repeatedly done with the combination of the acceptable gains. Finally, the best combination is selected for its best performance. For the effectiveness of the proposed method, it was implemented on a Hyundai 8608 robot and its results are compared with the results of NACHI's Semi-Auto Tuning Method and the results which are done by a tuning expert with his eyes.

• 대한전자공학회논문지
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• 제27권2호
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• pp.55-64
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• 1990

직류 전동기의 위치 및 속도 제어를 위해 그동안 주로 사용해 왔던 고전적인 선형 PID 제어 알고리듬을 사용하여 왔으나, 주위환경의 변화나 부하의 변경 또는 외란과 같은 비션형 요소들로 인해 실제 시스템의 모델링에는 많은 제한이 따랐다. 이 문제를 해결하기 위해 시스템의 모델링 없이 매개변수들을 온라인으로 추정하여 식별할 수 있는 PID 자기 동조기의 설계 방법을 제안하였다. 본 논문에서는 극 배치 PID 자기 동조 제어기의 설계 기법을 제안하고, 각각의 제어기 매개변수들을 추정하기 위하여 순환 최소자승 알고리듬을 사용하야T으며, Diophantine 방정식의 도입으로 인한 4개의 추가매개 변수들을 추정된 제어기 매개변수들을 이용하여 새롭게 유도된 방정식에서 구하였다. 제안된 제어기의 성능을 평가하기 위하여 최소, 비최소 위상 시스템에 대한 시뮬레이션을 하였고 실제 로보트 매니플레이터용 DC 서어보 전동기에 대하여 무부하와 부하 실험을 거쳐 그 특성이 양호함을 검증하였다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 하계학술대회 논문집 D
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• pp.2655-2657
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• 2000

this paper suggests a genetic algorithms combining simulated annealing for PID factor tunning. This paper made Off-Line control parameter tuning of the DC servo motor for the speed, In this paper new method to design PID controller through proposed genetic algorithm. Two experiments compared both the PID controller using genetic algorithms and PID controller using proposed genetic algorithm for a DC-servo motor. The result of two experiments was safty higher PID controller using proposed genetic algorithm than PID controller using genetic algorithm.

• 한국항만학회지
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• 제14권2호
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• pp.187-197
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• 2000

In this paper, an adaptive mechanism based on immune algorithm is designed and it is applied to the driving control of the autonomous guided vehicle(AGV). When the immune algorithm is applied to the PID controller, there exists the case that the plant is damaged by the abrupt change of PID parameters since the parameters are adjusted almost randomly. To solve this problem, a neural network used to model the plant and the parameter tuning of the model is performed by the immune algorithm. After the PID parameters are determined through this off-line manner, these parameters 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 initially, the weighting parameters are adjusted more accurately through the on-line fine tuning. The experiment for the control of steering and speed of AGV is performed. The results show that the proposed controller provides better performances than other conventional controllers.

• 대한전기학회논문지:시스템및제어부문D
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• 제52권3호
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• pp.134-141
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• 2003

PID controllers with constant gains have been widely used in various control systems due to its powerful performance and easy implementation. But it is difficult to have uniformly good control performance in all operating conditions. In this paper, we propose a nonlinear variable PR controller with immune feedback mechanism. An immune feedback mechanism is based on the functioning of biological T-cells, they include both an active term, which controls response speed. and an inhibitive term, which controls stabilization effect. Therefore, the proposed nonlinear PID controller is based on immune responses of biological. immune feedback mechanism which is the cell mediated immunity and In order to choose the optimal nonlinear PID controller games, we also propose the tuning algorithm of nonlinear function parameter in immune feedback mechanism. To verify performance of the proposed algorithm, the speed control of nonlinear DC motor are performed. Front the simulation results, we have found that the proposed algorithm is more superior to the conventional constant fain PID controller.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.85.2-85
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• 2001

In this paper, we propose a modified Ziegler-Nichols PID controller using the fuzzy logic system. The proposed method is to parameterize a Ziegler-Nichols formula with a single parameter, and use the fuzzy logic system for automatic tuning of a single parameter of the modified Ziegler-Nichols formula. The fuzzy logic system has simple nine control rules. In order to verify the effectiveness of the proposed method, we simulated with the servo system. Simulation results demonstrate that better control performance can be achieved when compared with that of the Ziegler-Nichols PID controller.