• Journal of Electrical Engineering and information Science
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• v.1 no.2
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• pp.101-108
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• 1996

A new speed controller based on the fuzzy algorithm with hierarchical structure is presented. The input variables of the controller are speed error and its derivative(change of error), where the output variable is the change of torque current command. Several comparisons were performed with conventional PI (proportional plus integral) controller and proposed controller. These controllers are applied to the laboratory model drive system with 2.2kW induction motor. Some simulation and experimental results show that the speed controller using fuzzy algorithm is more robust than the conventional PI controller.

• Journal of Electrical Engineering and Technology
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• v.12 no.5
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• pp.1821-1834
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• 2017

Medium voltage control applications due to obtain better output voltage and reduced electro-magnetic interference multi level inverter is used. In closed loop control with inverter, the PI controller does not operate satisfactorily when the operating point changes. This paper presents the performance of Co-Efficient diagram PI controller based indirect vector controlled induction motor drive fed from three-level inverter under different operating conditions (dynamic and steady state). The proposed Co-Efficient diagram PI controller based three level inverter significantly reduces the torque ripple compared to that of conventional PI controller. The performance of the indirect vector controlled induction motor drive has been simulated at different operating conditions. For three-level inverter control, a simplified space vector modulation technique is implemented, which reduces the coordinate transformations complications in the algorithms. The performance parameters, torque ripple contents and THD of induction motor drive with three-level inverter is compared under different operating conditions using CDM-PI and conventional PI controllers.

• Journal of Drive and Control
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• v.15 no.1
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• pp.28-37
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• 2018

When the wind speed rises above the rated wind speed, the produced power of the wind turbines exceeds the rated power. Even more, the excessive power results in the undesirable mechanical load and fatigue. A solution to this problem is pitch control of the wind turbines. This paper presents a systematic design method of a collective pitch controller for the wind turbines using a discrete fuzzy Proportional-Integral (PI) controller. Unlike conventional PI controllers, the fuzzy PI controller has variable gains according to its input variables. Generally, tuning the parameters of fuzzy PI controller is complex due to the presence of too many parameters strongly coupled. In this paper, a systematic method for the fuzzy PI controller is presented. First, we show the fact that the fuzzy PI controller is a superset of the PI controller in the discrete-time domain and the initial parameters of the fuzzy PI controller is selected by using this relationship. Second, for simplicity of the design, we use only four rules to construct nonlinear fuzzy control surface. The tuning parameters of the proposed fuzzy PI controller are also obtained by the aforementioned relationship between the PI controller and the fuzzy PI controller. As a result, unlike the PI controller, the proposed fuzzy PI controller has variable gains which allow the pitch control system to operate in broader operating regions. The effectiveness of the proposed controller is verified with computer simulations using FAST, a NREL's primary computer-aided engineering tool for horizontal axis wind turbines.

• Proceedings of the KIPE Conference
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• 2010.07a
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• pp.602-603
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• 2010

This paper presents a comparison and evaluation between different anti-windup proportional-integral (PI) controller strategies used in variable-speed motor drives, and the anti-windup methods are to the speed control of a vector-controlled induction motor driven by a pulse width modulated (PWM) voltage-source inverter (VSI). The simulation results are compared for the different operating conditions and the characteristic of speed response has been analyzed in order to obtain the optimal performance of anti-windup PI controller method.

• Proceedings of the KIPE Conference
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• 2005.07a
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• pp.538-541
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• 2005

Most realistic control systems contain nonlinearities of some form. One nonlinearity commonly found in control systems is a saturating element. If integral control is applied to such a system to eliminate steady state error, an undesired side effect known as integrator windup may occur when lage setpoint changes are made. This effect leads to a characteristic step response with a large overshoot and a very high settling time. To avoid this situation, many different anti-windup strategies have been suggested. But existing strategies remain over shoot and high settling time. This paper proposes a new anti-windup strategy for PI speed controllers. When the speed control system is changed P controller to PI controller. Integrator has an appropriate initial value. This value results over shoot and high settling time. The SIMULINK/MATLAB-based comparative simulation results and experiment results of speed controller have shown its superior control performance to that of a proposed anti-windup speed controller.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.16 no.11
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• pp.1068-1076
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• 2004

Technology on the proportional integral (PI) control have grown rapidly owing to the needs for the robust capacity of the controllers from industrial building sectors. However, PI controller requires tuning of gains for optimal control when the outside weather condition changes. The present study presents the possibility of reinforcement learning (RL) control algorithm with PI controller adapted in the HVAC system. The optimal design criteria of RL controller was proposed in the Environment Chamber experiment and a theoretical analysis was also conducted using TRNSYS program.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.7 no.3
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• pp.117-120
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• 2014

In general a main technology of control a sluice gate is accurate synchronous position control for the two cylinders when they are moving with the sluice gate together over 10[m]. Because the nonlinear friction and the unconstant supply flow. Cylinders' displacement will be different. In this case the sluice gate may be deformed and abraded, and even the sluice gate may unable to work. In order to design the controller for this system, we designed two kinds of Fuzzy PI controllers. Fuzzy PI position controller and Fuzzy PI synchronous controller have been designed. We show some simulation results for its availability.

• Proceedings of the KIEE Conference
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• 1998.07b
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• pp.541-543
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• 1998

Generally, PI control is simple and easy to implement and gains of PI control are determined by specifying a dynamics of the servo driver system. However, the gain-tuning is so difficult that it is relied on an expert's effort. This paper presents a gain auto-tuning method for PI controllers based on a fuzzy inference mechanism. First, the proposed fuzzy inference system identifies a system moment of inertia and adjusts control gains by using the difference in speed responses between a real plant and a reference model. Second, this paper proposes an improved fuzzy PI controller. To reduce the speed overshoot, we adapt a control method that selects a proper PI gains with respect to the load inertia variation. To prove the validity of the proposed gain tuning algorithm and the feasibility of the servo drive, a high performance servo drive will be implemented by DSP(TMS320C31) and intelligent power module (IPM). The proposed controller is applied to the speed control of the 300W AC servo motor. Some simulations and experimental results show that the proposed fuzzy PI controller is more robust than the conventional PI controller against the load inertia variation.

• Journal of Power Electronics
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• v.8 no.3
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• pp.280-290
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• 2008

This paper deals with an investigation and evaluation of the performance of a state observer based Permanent Magnet Synchronous Motor (PMSM) drive controlled by PI (Proportional Integral), PID (Proportional Integral and Derivative), SMC (sliding mode control), ANN (Artificial neural network) and FLC (Fuzzy logic) speed controllers. A detailed study of the steady state and dynamic performance of estimated speed and angle is given to demonstrate the capability of the controllers.

• Proceedings of the KIEE Conference
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• 2004.05a
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• pp.10-12
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• 2004

Recently, Datta at al. [1] have developed a metDattad of obtaining the complete set of stabilizing PI, PID controllers for a given LTI system, in which tDattase are determined by solving a set of linear inequalities parameterized by the proportional(P) gain. In this paper, we provide a note about Dattaw Datta's idea can be extended to the problem of finding all stabilizing PD controllers and about an improved metDattad that allows us to calculate the admissible range of P gain more rigorously. An illustrative example is given.