• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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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.

• The Journal of Korea Robotics Society
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• v.17 no.2
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• pp.221-229
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• 2022

Sliding mode control (SMC) is a robust control method to control a robot arm with nonlinear properties. A high switching gain of SMC causes chattering problems, although the SMC allows the adequate control performance by giving high switching gain, without the exact robot model containing nonlinear and uncertainty terms. In order to solve this problem, SMC with sliding perturbation observer (SMCSPO) has been researched, where the method can reduce the chattering by compensating the perturbation, which is estimated by the observer, and then choosing a lower switching control gain of SMC. However, optimal gain tuning is necessary to get a better tracking performance and reducing a chattering. This paper proposes a method that the Q-learning automatically tunes the control gains of SMCSPO with an iterative operation. In this tuning method, the rewards of reinforcement learning (RL) are set minus tracking errors of states, and the action of RL is a change of control gain to maximize rewards whenever the iteration number of movements increases. The simple motion test for a 7-DOF robot arm was simulated in MATLAB program to prove this RL tuning algorithm. The simulation showed that this method can automatically tune the control gains for SMCSPO.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.11
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• pp.22-33
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• 1999

This paper presents the method for the automatic tuning of a design weighting polynomial parameters of a generalized minimum-variance stochastic ultivariable self-tuning controller which adapts to changes in the higher order nonminimum phase system parameters with time delays and noises. The self-tuning effect is achieved through the recursive least square algorithm at the parameter estimation stage and also through the Robbins-Monro algorithm at the stage of optimizing the design weighting polynomial parameters of the controller. The proposed multivariable self-tuning method is simple and effective compared with pole restriction method. The computer simulation results are presented to adapt the higher order multivariable system with nonminimum phase and with changeable system parameters.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.8
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• pp.1259-1265
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• 2003

We present a new post-fabrication frequency tuning method for laterally driven electrostatic microresonators using a DC-biased electrostatic comb array of linearly varied finger-length. The electrostatic tuning force and the equivalent stiffness, adjusted by the DC-biased tuning-comb array, have been formulated as functions of geometry and DC tuning voltage. A set of frequency-turnable microresonators has been designed and fabricated by 4-mask surface-micromachining process. The resonant frequency of the microfabricated microresonator has been measured for a varying tuning voltage at the reduced pressure of 1 torr. The maximum 3.3% reduction of the resonant frequency is achieved at the tuning voltage increase of 20V.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.256-261
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• 2004

This paper presents a simple two-degree of freedom PID tuning table based on the CDM design method. The structure of the control system will be composed of plant, P or PI or PID controller and a pre-filter. The finalized formula can be used based on the experimental test of the plant in the same manner as the Ziegler-Nichols' second method. That is; users just need to find the critical gain and critical period experimentally and the parameters of the P, PI or PID controller with the pre-filter can be obtained by substituting the values of critical gain and critical period in the tuning table. The simulation results of the control systems utilizing the proposed controllers compared with those using the Ziegler-Nichols' second method will also be demonstrated.

• Proceedings of the KIEE Conference
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• 1997.07f
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• pp.2139-2142
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• 1997

The most important thing in vector control scheme is the knowledge of accurate electrical motor parameters. These parameters can computed by conventional motor test, such as no-load and locked rotor tests. However, the values from these tests are different from actual motor parameters, and the adjustment process of the parameters is time consuming. This paper presents an auto-tuning method for vector control of induction motor. The tuning algorithm is based on the rotor flux behavior of the induction motor for stepwise torque current command. The transient terminal voltage caused by the undesirable variation of the rotor flux is used for tuning the slip gain $K_5$ defined as the inverse of the rotor time constant. The electrical parameters of induction motor can also calculated by this method. The presented method is evaluated through the computer simulations.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.19 no.5
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• pp.475-481
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• 2009

Real-coded genetic algorithm(RCGA) has better performances than conventional genetic algorithm about dealing with a large domain, the precision and the constrain problem. Also the RCGA has advantage of operation time because it doesn't have to following about decoding operation. In this paper the ranges of PID gains are limited based on Ziegler-Nichols method to consider a long operation time problem that is the main problem of genetic algorithm. Result shows proposed method represents better performance without ignored about result of ZN tuning method and reduces the calculation time.

• Management Science and Financial Engineering
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• v.17 no.1
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• pp.19-43
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• 2011

Tuning the architecture of SVM (support vector machine) is to build an SVM model of better performance. Two different tuning methods of the grid search and the GA (genetic algorithm) have been addressed in the literature, each of which has its own methodological pros and cons. This paper suggests a combined method for tuning the architecture of SVM models, which employs the GAM (generalized additive models), the grid search, and the GA in sequence. The GAM is used for selecting input variables, and the grid search and the GA are employed for finding optimal parameter values of the SVM models. Applying the method to a bankruptcy prediction problem, we show that SVM model tuned by the proposed method outperforms other SVM models.

• Proceedings of the KIEE Conference
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• 1990.07a
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• pp.68-71
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• 1990

In this paper, it is introduced about Auto-Tuning Method which applied to Expert Controller. This method constructs heuristic knowledge of the tuning experiment in order to realize relay tuning theory of Astrom &. Hagglund. This method applies to various Plant and showes utility which is used for Controller design of PID group. Result of simulation showed superiority for speed reponse and robustness of all Plant.

• Journal of the Korean Institute of Telematics and Electronics T
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• v.35T no.3
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• pp.87-95
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• 1998

This paper presents the method for the automatic tuning of a design weighting polynomial parameter of a generalized minimum-variance stochastic self tuning controller which adapts to changes in the system parameters with time delays and noises. The self tuning effect is achieved through the recursive least square algorithm at the parameter estimation stage and also through the Robbins-Monro algorithm at the stage of optimizing a design weighting polynomial parameters. The proposed self tuning method is simple and effective compared with other existing self tuning methods. The computer simulation results are presented to illustrate the procedure and to show the performance of the control system.