• 제어로봇시스템학회:학술대회논문집
• /
• 2004.08a
• /
• pp.272-276
• /
• 2004

The conventional PID (Proportional-Integral-Derivative) control technique is widely used for the process control in many industries since it is simple in structure and provides the good response. Nowadays, this control technique has been developed on the Programmable Logic Controller (PLC) to use for the process control loop. However, using this technique is difficult when tuning the PID parameters ($K_p$, $T_i$ and $T_d$) to achieve the best response. Moreover, trial-and-error procedure along with the operator experiences are required to obtain the best results when tuning the PID controller parameters. This paper proposes the self-tuning PID controller based on PLC for the process control in the industries. The proposed self-tuning PID controller uses the PLC-based PID structures to control the process production. The proposed PID tuning utilizes the PLC to synthesize and analyze controller parameter as well as to tune for appropriate parameters using Dahlin method and extrapolation. Experimental results using a self-tuning PID controller to control temperature of the oven show that the controller developed is capable of controlling the process very effectively and provides a good response.

• International Journal of Control, Automation, and Systems
• /
• v.4 no.6
• /
• pp.756-762
• /
• 2006

Shape Memory Alloy(SMA) actuators, which have the ability to return to a predetermined shape when heated, have many potential applications such as aeronautics, surgical tools, robotics and so on. Although the conventional PID controller can be used with slow response systems, there has been limited success in precise motion control of SMA actuators, since the systems are disturbed by unknown factors beside their inherent nonlinear hysteresis and changes in the surrounding environment of the systems. This paper presents a new development of a SMA position control system by using a self-tuning fuzzy PID controller. This control algorithm is used by tuning the parameters of the PID controller thereby integrating fuzzy inference and producing a fuzzy adaptive PID controller, which can then be used to improve the control performance of nonlinear systems. The experimental results of position control of SMA actuators using conventional and self-tuning fuzzy PID controllers are both included in this paper.

• The Transactions of the Korean Institute of Electrical Engineers D
• /
• v.50 no.1
• /
• pp.22-30
• /
• 2001

This paper describes a neural network based fuzzy PID control scheme. The PID controller is being widely used in industrial applications. However, it is difficult to determine the appropriated PID gains in nonlinear systems and systems with long time delay and so on. In this paper, we re-analyzed the fuzzy controller as conventional PID controller structure, and proposed a neural network based self tuning fuzzy PID controller of which output gains were adjusted automatically. The tuning parameters of the proposed controller were determined on the basis of the conventional PID controller parameters tuning methods. Then they were adjusted by using proposed neural network learning algorithm. Proposed controller was simple in structure and computational burden was small so that on-line adaptation was easy to apply to. The experiment on the magnetic levitation system, which is known to be heavily nonlinear, showed the proposed controller's excellent performance.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.57 no.3
• /
• pp.518-526
• /
• 2008

The fuzzy self-tuning PID controller is a PID controller with a fuzzy logic mechanism for tuning its gains on-line. In this structure, the proportional, integral and derivative gains are tuned on-line with respect to the change of the output of system under control. This paper deals with two types of fuzzy self-tuning PID controllers, rule-based fuzzy PID controller and learning fuzzy PID controller. As a medical application of fuzzy PID controller, the proposed controllers were implemented and evaluated in a laparoscopic surgery robot system. The proposed fuzzy PID structures maintain similar performance as conventional PID controller, and enhance the position tracking performance over wide range of varying input. For precise approximation, the fuzzy PID controller was realized using the linear reasoning method, a type of product-sum-gravity method. The proposed controllers were compared with conventional PID controller without fuzzy gain tuning and was proved to have better performance in the experiment.

• Journal of Power Electronics
• /
• v.17 no.6
• /
• pp.1577-1586
• /
• 2017

The Proportional-Integral-Derivative (PID) controller is still the most widespread control strategy in the industry. PID controllers have gained popularity due to their simplicity, better control performance and excellent robustness to uncertainties. This paper presents the optimal tuning of a PID controller for domestic induction heating systems with a series resonant inverter for controlling the induction heating power. The objective is to design a stable and superior control system by tuning the PID controller with a derivative filter (PIDF) through Fuzzy logic. The paper also compares the performance of the Fuzzy PIDF controller with that of a Ziegler-Nichols PID controller and a fine-tuned PID controller with a derivative filter. The system modeling and controllers are simulated in MATLAB/SIMULINK. The results obtained show the effectiveness and superiority of the proposed Fuzzy PID controller with a derivative filter.

• The Transactions of the Korean Institute of Electrical Engineers
• /
• v.37 no.7
• /
• pp.475-483
• /
• 1988

One of the advantages of the well-known PID controller is that it is a sufficiently flexible controller for many applications. But, when the plant parameters and disturbances are unknown or change with time, it is desirable to make automatic tuning of PID controller in order to achieve an acceptable level of performance of the control system. This paper presents a reformulation of the self-tuning pole-zero placement controller subject to some conditions and restrictions. It has the structure of a digital PID controller and is based on Vogel and Edgar's pole-zero placement design method. Various properties of this self-tuning PID controller are described and illustrated by simulation examples.

• Journal of the Institute of Electronics Engineers of Korea SC
• /
• v.44 no.6
• /
• pp.1-10
• /
• 2007

This paper presents a direct nonlinear multivariable self-tuning PID controller using neural network which adapts to the changing parameters of the nonlinear multivariable system with noises and time delays. The nonlinear multivariable system is divided linear part and nonlinear part. The linear controller are used the self-tuning PID controller that can combine the simple structure of a PID controllers with the characteristics of a self-tuning controller, which can adapt to changes in the environment. The linear controller parameters are obtained by the recursive least square. And the nonlinear controller parameters are achieved the through the Back-propagation neural network. In order to demonstrate the effectiveness of the proposed algorithm, the computer simulation results are presented to adapt the nonlinear multivariable system with noises and time delays and with changed system parameter after a constant time. The proposed PID type nonlinear multivariable self-tuning method using neural network is effective compared with the conventional direct multivariable adaptive controller using neural network.

• Journal of Advanced Marine Engineering and Technology
• /
• v.23 no.1
• /
• pp.40-46
• /
• 1999

A self-tuning FPID(Fuzzy Proportional Intergral Derivative) controller fo load frequency control of 2-area power systemis proposed in this paper. The paramters of the proposed self-tuning FPID controller are self-tuned by the proposed fuzzy inference technique. Therefore in this paper the fuzzy inference technique of PID gains using PSGM(Product Sum Gravity Method) is presented and is applied to the load frequency control of 2-area power system. The computer simulation results show that the proposed controller give better more control characteristics than convention-al PID, FLC under load changes.

• The Transactions of the Korean Institute of Electrical Engineers A
• /
• v.48 no.10
• /
• pp.1251-1258
• /
• 1999

The water level control of a steam generator in the unclear power plant is an important process. Most of the water level controllers of the actual plant are PID controllers. But they have limitations in appling for tracking the set point and getting rid of disturbances, so there are some defects to apply in the actual ground even though many research works represented the resolutions to solve it. In this paper, it is suggested that the established simple PID controller in low power has the ability to remove disturbances and trace the set-point, and then possesses the real-time self-tuning function according to the variety of moving peculiarity of a plant. This function realized by making use of fuzzy logic. PID parameters are formulated by a variable ${\alpha}$ and made it fluctuate by a fuzzy inference according to level error and level error change. This mechanism makes application of actual plant effective as well as taking advantage of improving the efficiency of water level controller by way of adding the function of self-tuning instead of replacing PID controller. The computer simulation of this scheme shows the improved performance compare to conventional PID controller.

• Proceedings of the KIEE Conference
• /
• 2001.07b
• /
• pp.1182-1184
• /
• 2001

This paper presents a neural network based self-tuning fuzzy PID control scheme for induction motor speed control. The PID controller is being widely used in industrial applications. When continuously used long time, the electric and mechanical parameters of induction motor change, degrading the performance of PID controller considerably. This paper re-analyzes the fuzzy controller as conventional PID controller structure, and proposes a neural network based self-tuning fuzzy PID controller whose scaling factors are adjusted automatically. Proposed scheme is simple in structure and computational burden is small. The simulation using Matlab/Simulink is performed to verify the effectiveness of the proposed scheme.