• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.8
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• pp.1014-1021
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• 1999

PID controllers with constant gains have been widely used in various control systems. But it is difficult to have uniformly good control performance in all operating conditions. In this paper, we propose a variable PID controller for robot manipulators. We divide total workspace of manipulators into several subspaces. PID controllers in each subspace are optimized using evolution strategy which is a kind of global search algorithm. In real operation, the desired trajectories may cross several subspaces and we select the corresponding gains in each subspace. The gains may have large difference on the boundary of subspaces, which may cause oscillatory motion. So we use artificial neural network to have continuous smooth gain curves to reduce the oscillatory motion. From the experimental results, although the proposed variable PID controller for robots should pay for some computational burden, we have found that the controller is more superior to the conventional constant gain PID controller.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.2
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• pp.303-311
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• 2012

In this study, we introduce a dynamic process model as well as the design methodology of optimized fuzzy controller for its efficient application to vacuum production system to produce a semiconductor, solar module and display and so on. In a vacuum control field, PID control method is widely used from the viewpoint of simple structure and preferred performance. But, PID control method is very sensitive to the change of environment of control system as well as the change of control parameters. Therefore, it's difficult to get a preferred performance results from target system which has a complicated structure and lots of nonlinear factors. To solve such problem, we propose the design methodology of an optimized fuzzy PID controller through a following series of steps. First a dynamic characteristic of the target system is analyzed through a series of experiments. Second the process model is built up and its characteristic is compared with real process. Third, the optimized fuzzy PID controller is designed using genetic algorithms. Finally, the fuzzy controller is applied to target system and then its performance is compared with that of other conventional controllers(PID, PI, and Fuzzy PI controller). The performance of the proposed fuzzy controller is evaluated in terms of auto-tuned control parameters and output responses considered by ITAE index, overshoot, rise time and steady state time.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.291-294
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• 1996

By far the PID controller is most widely sed in the process industries. However, current tuning methods yield PID parameters only for a restricted class of process models. There is no general methodology of PID controller tuning for arbitrary process models. In this paper, we generalize the IMC-PID approach and obtain the PID parameters for general models by approximating the ideal controller with a Maclaurin series. Further, the PID controller tuned by the proposed PID tuning method gave more closer closed-loop response to the desired response than those tuned by other tuning methods.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.2
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• pp.55-61
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• 2000

In this paper, we proposed a new PID tuning algorithm by the fuzzy set theory to improve the performance of the PID controller. The new tuning algorithm for the PID controller has the initial value of parameter Kc, $\tau$I, $\tau$D by the Ziegler-Nichols formula using the ultimate gain and ultimate period from a relay tuning experiment. We get error and error change of plant output correspond to the initial value and new proportion gain(Kc) and integral time($\tau$I) from fuzzy tunner. This fuzzy tuning algorithm for PID controller considerably reduced overshoot and rise time compare to any other PID controller tuning algorithms. In real parametric uncertainty systems, the PID controller with Fuzzy auto-tuning give appreciable improvement in the performance. The significant properties of this algorithm is shown by simulation In this paper, we proposed a new PID algorithm by the fuzzy set theory to improve the performance of the PID controller.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.11C
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• pp.1062-1069
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• 2003

This paper presents a new loop shaping technique for design of robust optimal PID controllers in order to satisfy the performance requirements. PID controller can be designed by selecting the suitable weighting factors Q and R. This technique is developed by pushing all two zeros formed by PID controller closely to a larger pole of the second order plant. As a result, a good loop shaping is achieved in the high frequencies region on the Bode plot. For the robust optimal tuning of PID controller for second order system, a new loop shaping procedure is developed via LQR approach.

• Journal of the Semiconductor & Display Technology
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• v.1 no.1
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• pp.21-28
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• 2002

This paper presents a dynamic modeling and a robust PID controller design process for the wire bonder head assembly. For modeling elements, the system is divided into electrical part, magnetic part, and mechanical part. Each part is modeled using the bond graph method. The PID controller is used for high speed/high accuracy position control of the wire bonder assembly. The Taguchi method is used to obtain the more robust PID gain combinations than conventional one. This study makes use of an L18 array with three parameters varied on three levels. Results of simulations and experimental show that the designed PID controller provides a improved ratio of signal to noise and a reduced sensitivity improved to the conventional PID controller.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2557-2561
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• 2005

The PID controller design and choosing PID parameters according to system response are proposed in this paper. Here PID controller is employed to control DC motor speed and Matlab program is used for calculation and simulation. Choosing PID parameters are demonstrated by several contrast experiments and a way for setting PID parameters values is discussed.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.3 no.2
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• pp.403-410
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• 1999

A conventional PID controller has poor performance when it applied to systems with unknown deadzones. To solve this problem, this paper proposes PID controller using two layered-fuzzy logic. The structure of controller is reconstructed with fuzzy compensator and fuzzy tuner on the conventional PID controller. Our proposed control scheme shows superior transient and steady-state performance compared to conventional PID controller. The scheme is robust to variations in deadzone nonlinearities as well as the steady-state gain of the plant. The performance of the developed controller is verified through simulation.

• Proceedings of the KIEE Conference
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• 1998.07b
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• pp.617-619
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• 1998

A PID-controller is proposed as a controller to the IFAC93 benchmark process. It is compared with a Textbook PID-controller and a Derivative of output PID-controller. Especially, the Derivative of output PID controller works within the critical bounds of ${\pm}1.5$ except for 1 out of 15 periods at stress level 1,2. The objective of this paper, then, is to report on an alternative benchmark (IFAC93) and reveal more efficient PID controller between Textbook PID-control and Derivative of output PID-controller.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.627-630
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• 2004

The PID type controller has been widely used in industrial application due to its simply control structure, ease of design, and inexpensive cost. However, control performance of the PID type controller suffers greatly from high uncertainty and nonlinearity of the system, large disturbances and so on. This paper presents a hybrid fuzzy logic proportional plus conventional integral derivative controller (fuzzy P+ID). In comparison with a conventional PID controller, only one additional parameter has to be adjusted to tune the fuzzy P+ID controller. In this case, the stability of a system remains unchanged after the PID controller is replaced by the fuzzy P+ID controller without modifying the original controller parameters. Finally, the proposed hybrid fuzzy P+ID controller is applied to BLDC motor drive. Simulation results demonstrated that the control performance of the proposed controller is better than that of the conventional controller.