• Journal of Bio-Environment Control
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• v.8 no.3
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• pp.152-163
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• 1999

It is required to analyze the controlled response of air temperature in greenhouse according to control techniques for precise control. In this study, a mathematical model was established for air heating of greenhouse with hot-water heating system The parameters of the model were decided by regression analysis using reference data measured at the greenhouse being heated In the simulation for the digital control of air temperature in the greenhouse, the mathematical model to evaluate the control performances was used. Tested control methods were ON-OFF contpol, p control, rl control and PID control. The mathematical model represented by inside air temperature ( T$_{i}$), hot-water temperature (T$_{w}$) in heating pipe and outside air temperature (T$_{o}$) was expressed as a following discrete time equation ; T$_{i}$($textsc{k}$＋1)＝ 0.851.T$_{i}$($textsc{k}$)＋0.055.T$_{w}$($textsc{k}$)＋0.094.T$_{o}$($textsc{k}$) Control simulations for various control methods showed the settling time, the overshoot and the steady state nor as follows; infinite time, 3.5$0^{\circ}C$, 3.5$0^{\circ}C$ for ON-OFF control : 30min 2.37$^{\circ}C$, 0.51$^{\circ}C$ for P control; 21min, 0.0$0^{\circ}C$, 0.23$^{\circ}C$ for PI control; 18min 0.0$0^{\circ}C$, 0.23$^{\circ}C$ for PID control, respectively. PI and PID controls appeared to be optimal control methods. There was no effect of differential gain on the heating process but much effect of integral gain on it.on it.

• Journal of Institute of Control, Robotics and Systems
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• v.3 no.6
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• pp.639-643
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• 1997

This paper presents how nonlinear PID control algorithms can be applied on chemical processes for a more stable operation and perfect automation. A pass balance controller is designed to balance the exiting temperatures of a heater and a heat exchange network. The proposed controller has gain-varying integral action and deals with the operational constraints in an efficient manner. Also, the use of a PID gap controller is proposed to maximize energy saving and operation stability and to minimize operator intervention in operation of air fan coolers. The proposed controller adjusts the opening of a louver automatically in such a way that it keeps the air fan pitch position within the desired range. All these nonlinear PID controllers have been implemented on the distributed control system (DCS) for good reliability and operability. Operator acceptance was very high and the implemented controllers have shown good performance and high service factor still now on. The proposed methodology can be directly applied to similar processes without any modification.

• Journal of Power Electronics
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• v.9 no.1
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• pp.74-84
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• 2009

The design and implementation of a high performance PID (Proportional Integral & Differential) style controller with zero-phase error tracking property is considered in this article. Unlike a ball screw driven system, the controller in a direct drive system should provide a high level of tracking performance while avoiding the problems due to the absence of the gear system. The stiff mechanical element in a direct drive system allows high precise positioning capability, but relatively high tracking ability with minimal position error is required. In this work, a feasible position controller named 'Unified PID controller' is presented. It will be shown that the function of the closed position loop can be designed into unity gain system in continuous time domain to provide minimal position error. The focus of this work is in two areas. First, easy gain tunable PID position controller without speed control loop is designed in order to construct feasible high performance drive system. Second, a simple but powerful zero phase error tracking strategy using the pre-designed function of the main control loop is presented for minimal tracking error in all operating conditions. Experimental results with a s-curve based position pattern commonly used in industrial field demonstrate the feasibility and effective performance of the approach.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1585-1588
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• 1997

In this paper, divide total workspace of robot manipulator into several subspaces and construct PID controller ineach subspace. Using EvolutionSTrategy we optimize the gains of PID controller in each subspace. But the gains may have a large difference on the boundary of subspaces, which can cause bad oscillatory performance. So we use Aritificial Neural Network to have continuous gain curves htrough the entire subspaces. Simualtion results show that the proposed method is quite useful.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.352-354
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• 2004

In this paper, a parallel fuzzy controller for one degree of freedom magnetic levitation is designed and its performance is compared with the performance of a PID controller. Input, output scaling factor of fuzzy controller and gain of PID controller were tuned using the GA algorithm. The designed controllers are validated by numerical simulations. So it's shown that parallel fuzzy controller can give the better performance for the plant than PID controller.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.8
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• pp.1811-1817
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• 2014

In this paper, a PID controller with interpolated gains by use of neural networks is proposed for the formation control problem that following robots track a leading robot with constant distances and angles when there are changes in the mass of the following robot. The whole control system is composed of a kinematic controller and a dynamic controller considering the robot dynamics. The dynamic controller is the PID controller with varying gains, and the proper gains are obtained for some representative masses of the follower robot by the genetic algorithm. Neural networks is trained using the genetic algorithm with the gain data obtained in the previous step. The trained neural network determines optimal PID gains for a random mass of following robot. Simulation studies show that for arbitrary masses of the tracking robot, the PID controller with interpolated gains by the trained neural network has better tracking performance than that of the PID controller with fixed gains.

• Proceedings of the KIEE Conference
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• 1999.11b
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• pp.389-391
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• 1999

Recently, the application of the linear machine for industrial field is remarkable increased, especially for the gantry machine. machine tool system and CNC. In these application fields. high precise position control performance is essentially required in both the steady and transient state. And linear machine is necessary for high-precision processing and manipulation when relatively high forces are involved. This paper presents the new unified PID position control algorithm which have rare sensitivity to disturbance, which the gain adjusting process is simple. Also this paper investigates the use of the New Unified PID control to design for high stiffness. Through the experimental results, it is shown that the proposed algorithm has high dynamic characteristic for the linear machine application field nevertheless of its simple structure.

• Journal of The Institute of Information and Telecommunication Facilities Engineering
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• v.3 no.2
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• pp.5-10
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• 2004

In this paper, the hybrid-type current controller for inverter TIG systems was implemented and it was shown that the low-current pulse wave forms with high dynamic performance could be obtained. It is not sri easy to obtain the optimum gain tuning of PID controllers in digital PWM control methods. Hybrid control methods which uses automatic tuning techniques after adding fuzzy control methods to traditional PID controllers are chosen to improve the dynamic performance of PID controller's. To demonstrate the practical significance and dynamic performance improvement of the results, some simulation and experimental results are presented.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.3 no.1
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• pp.78-86
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• 2003

Multivariable control system exist widely in many types of systems such as chemical processes, biomedical processes, and the main steam temperature control system of the thermal power plant. Up to the present time, Pill Controllers have been used to operate these systems. However, it is very difficult to achieve an optimal PID gain with no experience, because of the interaction between loops and gain of the Pill controller has to be manually tuned by trial and error. This paper suggests a tuning method of the Pill Controller for the multivariable power plant using an immune algorithm, through computer simulation. Tuning results by immune algorithms based neural network are compared with the results of genetic algorithm.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2005.11a
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• pp.423-426
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• 2005

In this paper, we proposed a 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 Kp, $\tau_{I}$, $\tau_{D}$. by the Ziegler-Nichols formula that uses the ultimate gain and ultimate period from a relay tuning experiment. We will get the error and the error rate of plant output corresponding to the initial value of parameter and fnd the new proportion gain(Kp) and the integral time ($\tau_{I}$) from fuzzy tuner by the error and error rate of plant oueut as a membership function of fuzzy theory. This fuzzy auto tuning algorithm for PID controller considerably reduced the overshoot and rise time as compared to any other PID controller tuning algorithms. And in real parametric uncertainty systems, it constitutes an appreciable improvement of performance. The significant property of this algorithm is shown by simulation