• Journal of Electrical Engineering and Technology
• /
• 제13권2호
• /
• pp.969-980
• /
• 2018

This paper aims to design of the neutrosophic fuzzy-PID controller and it has been compared with the conventional fuzzy-PID controller for position tracking control in terms of robustness. In the neutrosophic fuzzy-PID controller, error (e) and change of error (ce) were assessed separately on two fuzzy inference systems (FISs). In this study, the designed method is different from the conventional fuzzy logic controller design, membership degrees of antecedent variables were determined by using the T(true), I(indeterminacy), and F(false) membership functions. These membership functions are grouped on the universe of discourse with the neutrosophic set approach. These methods were tested on three-dimensional (3-D) position-tracking control application of a spherical robot manipulator in the MATLAB Simulink. In all tests, reference trajectory was defined for movements of all axes of the robot manipulator. According to the results of the study, when the moment of inertia of the rotor is changed, less overshoot ratio and less oscillation are obtained in the neutrosophic fuzzy-PID controller. Thus, our suggested method is seen to be more robust than the fuzzy-PID controllers.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2003년도 ICCAS
• /
• pp.2258-2263
• /
• 2003

This paper presents the design and development of an optimal fuzzy logic controller (FLC) for a laser tracking system. An optimal intelligent fuzzy logic controller was founded on integral criterion of the fuzzy models and three-dimensional fuzzy control. Research had been also concentrated on the methods for multivariable fuzzy models for the purposes of real-time process. Simulation results have shown remarkable tracking performance of this fuzzy PID controller.

• 제어로봇시스템학회논문지
• /
• 제12권3호
• /
• pp.221-226
• /
• 2006

In this paper, we study an approach to design a Fuzzy PI controller in HVDC(High Voltage Direct Current) system. In the rectifier of traditional HVDC system, turning on, turning off, triggering and protections of thyristors have lots of problems that can make the dynamic instability and cannot damp the dynamic disturbance efficiently. In order to solve the above problems, we adapt Fuzzy PI controller for the fire angle control of rectifier. The performance of the Fuzzy PI controller is sensitive to the variety of scaling factors. The design procedure dwells on the use of evolutionary computing(Genetic Algorithms, GAs). Then we can obtain factors of the Fuzzy PI controller by Genetic Algorithms. A comparative study has been performed between Fuzzy PI controller and traditional PI controller, to prove the superiority of the proposed scheme.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2005년도 ICCAS
• /
• pp.1496-1499
• /
• 2005

In this paper, we applied step motor drive using a fuzzy logic control based on PID controller. A designed this controller's purpose is improved robust and autonomous characteristic in which the variation of external load affects plant parameter. Therefore, in this paper, using a fuzzy logic control based on PID controller of two fuzzy-PI and fuzzy-D is obtained decremental overshoot and a special response quality.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 1999년도 하계학술대회 논문집 B
• /
• pp.510-512
• /
• 1999

In this paper, we present a method for the analysis and design of fuzzy controller for nonlinear systems. In the design procedure, we represent the dynamics of nonlinear systems using a Takagi-Sugeno fuzzy model and formulate the controller rules, which shares the same fuzzy sets with the fuzzy system, using parallel distributed compensation method. Then, after the feedback gain of each local state feedback controller is obtained using the existing optimal pole-placement scheme, we construct an overall fuzzy logic controller by blending all local state feedback controller. Finally, the effectiveness and feasibility of the proposed fuzzy-model-based controller design method has been evaluated through an inverted pendulum system.

• 제어로봇시스템학회논문지
• /
• 제7권6호
• /
• pp.509-517
• /
• 2001

To deal with non-linearities and time-varying characteristics of hydraulic systems, in this paper, the neuro-fuzzy controller has been introduced. This controller does not require and accurate mathematical model for the nonlinear factor. In order to solve general fuzzy inference problems, the input membership function and fuzzy reasoning rules are used for determining the controller parameters. These parameters are determined by using the learning algorithm. The control performance of the neuro-fuzzy controller is evaluated through a series of experiments for the various types of inputs while applying disturbances to the hydraulic system. The performance of this controller was compared with those of PID and PD controllers. From these results, We observe be said that the position tracking performance of neuro-fuzzy is better those of PID and PD controllers.

• 전기학회논문지
• /
• 제59권10호
• /
• pp.1797-1802
• /
• 2010

This paper proposes a new fuzzy speed controller based on the Takagi-Sugeno fuzzy method to achieve a robust speed control of a permanent magnet synchronous motor(PMSM). The proposed controller requires the information of the load torque, so the second-order load torque observer is used to estimate it. The LMI condition is derived for the existence of the proposed fuzzy speed controller, and the LMI parameterization to calculate the gain matrices of the controller is provided. It is proven that the augmented control system including the fuzzy speed controller and the load torque observer is exponentially stable. To evaluate the performance of the proposed fuzzy speed controller, the simulation and experimental results are presented under motor parameter and load torque variations. Finally, it is clearly verified that the proposed control method can be used to accurately control the speed of a permanent magnet synchronous motor.

• 대한전기학회논문지
• /
• 제43권2호
• /
• pp.233-243
• /
• 1994

Generally, fuzzy PI controller that regulates the gains using fuzzy algorithm shows high performance in speed response. However, it has some problems to the load inertia variation, because the change of speed error(CE) is in a fixed range. As load inertia increases, CE is decreased and the usuage of fuzzy table is limited. Therefore, the output of the fuzzy controller has a limited range. This paper proposes an improved fuzzy PI controller. To reduce the speed overshoot, we adapt a control method that selects a proper CE range with respect to the load inertia variation. The proposed controller is applied to the vector controlled system with 2.2kW induction motor. Some simulation and experimental results are exhibited. With these results, we can easily find that proposed PI controller is more robust than the conventional fuzzy PI controller against the load inertia variation.

• 한국지능시스템학회:학술대회논문집
• /
• 한국퍼지및지능시스템학회 1993년도 Fifth International Fuzzy Systems Association World Congress 93
• /
• pp.1207-1210
• /
• 1993

There is an opinion of regarding a simple fuzzy logic controller as a kind of Variable Structure Controller in recent years. The opinion may provide an analytical basis which describes the robustness to uncertainty and the stability of a fuzzy logic controller. So in this paper, a fuzzy logic controller based on the Variable Structure System with is designed for a robot manipulator which is a class of complex, nonlinear system with uncertainty. Fuzzy control rules, membership shape of the I/O variables of the fuzzy logic controller are designed for guaranteeing the stability of an overall control system. From a computer simulation of dynamic control of a two link robot manipulator, the design procedure of the fuzzy logic controller is validated.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 2007년도 제38회 하계학술대회
• /
• pp.1009-1010
• /
• 2007

This paper presents Fuzzy-Neuro PI controller of IPMSM drive using fuzzy and neural-network. In general, PI controller in computer numerically controlled machine process fixed gain. To increase the robustness, fixed gain PI controller, Fuzzy-Neuro PI controller proposes a new method based fuzzy and neural-network. Fuzzy-Neuro PI controller is developed to minimize overshoot and settling time following sudden parameter changes such as speed, load torque, inertia, rotor resistance and self inductance. The results on a speed controller of IPMSM are presented to show the effectiveness of the proposed gain tuner.