• The Journal of Korea Robotics Society
• /
• v.17 no.2
• /
• pp.221-229
• /
• 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 Intelligent Systems
• /
• v.12 no.3
• /
• pp.261-268
• /
• 2002

This paper represents that auto tunings of membership functions and weights in the fuzzy neural networks are effectively performed by immune algorithm. A number of hybrid methods in fuzzy-neural networks are considered in the context of tuning of learning method, a general view is provided that they are the special cases of either the membership functions or the gain modification in the neural networks by genetic algorithms. On the other hand, since the immune network system possesses a self organizing and distributed memory, it is thus adaptive to its external environment and allows a PDP (parallel distributed processing) network to complete patterns against the environmental situation. Also, it can provide optimal solution. Simulation results reveal that immune algorithms are effective approaches to search for optimal or near optimal fuzzy rules and weights.

• Proceedings of the KIEE Conference
• /
• 1993.07a
• /
• pp.436-438
• /
• 1993

A rule based fuzzy expert system in self-tune PID controllers is presented in this paper. The rule base. the core of the expert system, is extracted from the Wills' tuning map and the author's knowledge about the implicit relations between PID gains and controlled output response. The overall control system consists of the relay feedback scheme and the expert system, where the one is responsible for initial tuning and the other for subsequent tuning. The PID control system with the proposed fuzzy expert system, shows better convergence rate and control performances than those of a Litt in spite of the fact that the two rule bases are extracted from the same maps provided by Wills.

• Proceedings of the KAIS Fall Conference
• /
• 2009.05a
• /
• pp.458-460
• /
• 2009

The parameters of PID controller should be readjusted whenever system character change. In spite of a rapid development of control theory, this work needs much time and effort of expert. In this paper, to resolve this defect, after the sample of parameters in the changeable limits of system character is obtained, these parametrs are used as desired values of back propagation learning algorithm, also neural network auto tuner for PID controller is proposed by determing the optimum structure of neural network. Simulation results demonstrate that auto-tuning proper to system character can work well.

• 제어로봇시스템학회:학술대회논문집
• /
• 1993.10a
• /
• pp.847-852
• /
• 1993

In this paper, we present a recursive algorithm for the auto-tuning of PID controllers by optimizing a GPC criterion. Also, we develop an intelligent PID controller by combination of a recursive algorithm together with a supervisor, that allows to adjust the main controller parameters (prediction horizon, control weighting, sample time etc.) using some simple rules which is mainly built up through relay tuning experiments. The intelligent PID controller has been implemented successfully on an IBM PC/AT and some simulation results are presented.

• 제어로봇시스템학회:학술대회논문집
• /
• 1992.10a
• /
• pp.123-128
• /
• 1992

This paper presents an autotuning algorithm of scaling factor in order to improve system performance. We define the scaling factor of fuzzy controller as a function of error and error change. This function is tuned by the output of performance evaluation level utilizing the error of overshoot and rising time. Simulation results show that the proposed algorithm has good tuning performance for a system with parameter change.

• Proceedings of the KIEE Conference
• /
• 2001.07d
• /
• pp.2702-2704
• /
• 2001

In this Letter, we propose a comprehensive design methodology of hybri'd Fuzzy controllers (HFC). The HFC comes as a form of a convex combination of a standard PID controller and a fuzzy controller. The design procedure dwells on the use of evolutionary computing (genetic algorithm) and an auto-tuning algorithm. The tuning of the scaling factors of the HFC is an essential component of the entire optimization process. A numerical study is presented and a detailed comparative analysis is also included.

• Journal of the Korean Institute of Telematics and Electronics S
• /
• v.35S no.12
• /
• pp.36-45
• /
• 1998

In this paper, a method of on-line PI gain-tuninng is proposed for the speed control of brushless D.C. motor by investigating the pattern of input and output without estimating parameter. Proportional gain is tuned in the process to obtain a fast speed response by supplying the maximum constant input. And integral gain is appropriately tuned in the process of proportional control so that the response may be stably converged and the overshoot may be prevented. Therefore because both control and gain-tuning are executed concurrently, additional works that estimate parameters and so on aren't required in the proposed method. In the proposed method, both fast-response and overshoot problem are well solved, and it is more useful and convenient than existing auto-tuning methods in the speed control of D.C. motor. It is illustrated by simulations and experimental results that the proposed method is useful and stable.

• Journal of Biosystems Engineering
• /
• v.33 no.1
• /
• pp.58-62
• /
• 2008

The need for position information in agriculture is gradually increasing for precise control farm vehicle and effective manage farm land. Though geomagnetic sensor has a lot of merits in estimating heading angle of vehicle because of low costs and sensing ability of magnetic north, it is easy that sensor outputs are distorted in electro magnetic field environment. This study was conducted to develop geomagnetic compass which could be available in measuring relative position from reference point correcting output distorted by external electro magnetic field in a small scale field. Magnetic inducing sensor (PNI's Vector2X) which wound enamel coated copper coil on ferrite core in order to measure and correct earth magnetic field. Magnetic azimuth was corrected using the algorithm which estimated amount of magnetic distortion from the difference between each outputs of magnetic sensors that located on the cross shaped base. Developed auto-tuning magnetic sensor was showed less then 5% as bearing accuracy in the strong magnetic field.

• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.8 no.3
• /
• pp.64-70
• /
• 1994

We propose a new method to deal with optimal auto-tuning of the PID controller which is used to process control in various fields. First of all, in this method, 1st order system which was modeled from the unit step response of the system is Pade-approximated, then initial values are determined by the Ziegler-Nichols method. Finally, we can find the parameters of PID controller so as to maximize the fuzzy criterion function which includes the maximum overshoot, damping ratio, rising time and settling time. The Proposed method also shows good adaptability for variations in characteristics and dead m e of the system.