• 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.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.10a
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• pp.50-54
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• 1997

In general, the design of fuzzy logic controller has difficulties in the acquisition of expert's knowledge. So, some methods that can optimize the parameters for fuzzy logic controller automatically without expert knowledge was provided. Recently, tuning method for fuzzy logic controller using genetic algorithm(GA) were proposed in many papers. However, those are tuning methods for a part or some part of fuzzy logic controller. In this paper, we proposes auto tuning method for the whole part of tuzzy logic controller, such as parameters of membership functions for antecedence and consequence parts, rule base, scaling factor and the number of rule. Finally, second order dead time plant is provided to show the advantages of the proposed method.

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.790-794
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• 1989

A novel control method involving an automatic tuning of digital PID controller parameters has been developed for better regulation of DO (dissolved oxygen) concentration in batch fermentation processes. Heuristic reasoning allows the PID controller to reach improved tuning decisions based upon the supervision of certain control performance indices in the same cognitive manner as in an expert control.

• Congress of the korean instutite of fire investigation
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• 2010.12a
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• pp.91-119
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• 2010

There is an increasing number of car fires along with the increasing numbers of cars. The purpose of this study was to verify the possibility of fires caused by car tuning, which is one of the causes of car fires. The result showed that the possibility of car fires was increased by car tuning including replacement of headlights, excess of allowable current of wires or fuses by using multi cigar jacks, wire damage, earth fault, and vulnerability of wires and cables (sold in auto parts stores) to heat.

• Proceedings of the KIEE Conference
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• 1997.07b
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• pp.390-393
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• 1997

Fuzzy logic and neural networks are complemetary technologies in the design of intelligent system. Fuzzy neural network(FNN) as an auto-tuning method is actually known to an excellent method for the adjustment of the fuzzy rule. However, this has a weak point, because the convergence to the optimum depends on the initial condition. In this paper we develop a coding format to determine a FNN model by chromosome in GA and present systematic approach to identify the parameters and structure of FNN. The proposed hybrid tuning method realizes to construct minimal and optimal structure of the fuzzy mode simultaneously and automatically. This paper shows effectiveness of the tuning system by simulations compared with conventional methods.

• Proceedings of the KIEE Conference
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• 2000.07b
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• pp.994-996
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• 2000

Switched reluctance motor generally operates in the magnetically saturated region because the saturation gives several benefits to its performance. This paper investigates the modelling and fuzzy tuning PI control of a nonlinear switched reluctance motor. The modelling is performed through neural network technique. Fuzzy auto-tuning PI control is designed for a robust performance in load and speed variations. Simulation and experimental results indicate better performances compared with simple PI control.

• Proceedings of the Korean Magnestics Society Conference
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• 2008.12a
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• pp.98.1-98.1
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• 2008

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2009.10a
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• pp.344-350
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• 2009

According to torsional vibration characteristic of a damper clutch in auto-transmission, the input shaft system have occurred breakdown for the duration cycle and over-vibration happened on vehicle at specific condition. This paper describes the improvement of the torsional vibration of input shaft and the vehicle vibration by tuning of the damper clutch and suggests to the guide line about torsion characteristic on the design of damper clutch.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.20 no.10
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• pp.883-890
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• 2010

According to torsional vibration characteristic of a tunable dual stiffness type clutch(TDSTC) in auto-transmission, the input shaft system have occurred breakdown for the duration cycle and over-vibration happened on vehicle at specific condition. This paper introduces the improvement of the torsional vibration of input shaft and the vehicle vibration by tuning of the TDSTC.

• Journal of the Korean Institute of Telematics and Electronics T
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• v.36T no.1
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• pp.41-50
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• 1999

The brushless DC motor is widely being used in unmanned factories for its easy maintenance and characteristics of controllability. In this paper, we designed a speed control servo system of a sinusoidal type bmshless DC motor which has high efficiency and usefulness in the industrial fields. This servo system is realized by a controller which is required for driving motors and a new auto-tuning PI control algorithm. The DSP(Digita1 Signal Processor) is adopted as a main controller and a sensor signal processor owing to its fast computational capability and suitable architecture. Also, the hardware PWnl(Pulse Width Modulation) current controller is implemented to pursue a speed command exactly. By experimental results, it is verified that the speed response is pursued fast after command value and the steady-state response is well converged for command value variation without overshoots.