• Proceedings of the KIEE Conference
• /
• 2006.07b
• /
• pp.925-926
• /
• 2006

This paper presents a sensorless speed control of an interior permanent magnet synchronous motor using an adaptive integral binary observer and fuzzy logic controller. In view of composition with a main loop regulator and an auxiliary loop regulator, the binary observer has a property of the chattering alleviation in the constant boundary layer. However, the steady state estimation accuracy and robustness are dependent upon the width of the constant boundary. In order to improve the steady state performance of the binary observer, the binary observer is formed by adding extra integral dynamics to the switching hyperplane equation. Also, because the conventional fixed gain PI controller are very sensitive to step change of command speed, parameter variations and load disturbance, the fuzzy logic controller is used to compensate a fixed gain PI controller. Therefore, a gain PI is fixed and the IPMSM is drived at another speed region. The effectiveness of the proposed the adaptive integral observer and the fuzzy logic controller are confirmed by experimental results.

• Journal of Electrical Engineering and Technology
• /
• v.13 no.1
• /
• pp.451-459
• /
• 2018

This work presents an approach for modeling of electric vehicle considering the vehicle dynamics, drive train, rotational wheel and load dynamics. The system is composed of IPMSM (Interior Permanent Magnet Synchronous Motor) coupled with the wheels through a drive train. Generally, IPMSM is controlled by ordinary PID controllers. Performance of the ordinary PID controller is not satisfactory owing to the difficulties of optimal gain selections. To overcome this problem, a new type of fuzzy logic gain tuner for PID controllers of IPMSM is required. Therefore, in this paper fuzzy logic based gain tuning method for PID controller is proposed and compared with some previous control techniques for the better performance of electric vehicle with an optimal balance of acceleration, speed, travelling range, improved controller quality and response. The model was developed in MATLAB/Simulink, simulations were carried out and results were observed. The simulation results have proved that the proposed control system works well to remove the transient oscillations and assure better system response in all conditions.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2007.11a
• /
• pp.341-344
• /
• 2007

This paper proposes an alternative robust adaptive high-gain fuzzy observer design scheme and its application to synchronization of chaotic systems. The structure of the proposed observer is represented by Takagi-Sugeno fuzzy model and has the integrator of the estimation error. This improves the performance of high-gain observer and makes the proposed observer robust against noisy measurements, uncertainties and parameter perturbations as well. Using Lyapunov stability theory, an adaptive law is derived and the stability of the proposed observer is analyzed. Some simulation result is given to present the validity of theoretical derivations and the performance of the proposed observer.

• Proceedings of the KIEE Conference
• /
• 1993.11a
• /
• pp.299-303
• /
• 1993

There can be two methods in control systems: one is to use a linear controller, the other is to use a nonlinear controller. The PID controller and the fuzzy controller can be said to belong the linear and the nonlinear controller respectively. In this paper, a new hybrid controller which is consist of the linear PID controller of which the gain is tuned and the nonlinear self tuning fuzzy controller is proposed. In the PID controller, an algorithm which parameterizes the proportional, the intergral, and the derivative gain as a single parameter is used to improve the performance of the PID controller. In the self tuning fuzzy controller, an algorithm which changes the shape of the triangle membership function and changes the scaling factor which is multiplied to the error and the error change. The evaluation of the performance of the suggested algorithm is carried on by the simulation for the Rhino XH-2 robot manipulator with 5 links revolute joints.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.3 no.2
• /
• pp.146-156
• /
• 2003

Nonlinear dynamic 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, PID 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 PID controller has to be manually tuned by trial and error. This paper suggests control approaches by immune fuzzy for the nonlinear control system inverted pendulum, through computer simulation. This paper defines relationship state variables $x,\dot{x},{\theta},\dot{\theta}$ using immune fuzzy and applied its results to stability.

• Journal of Power Electronics
• /
• v.11 no.6
• /
• pp.819-823
• /
• 2011

This paper presents a fuzzy PD speed control scheme for the robust speed tracking of a permanent magnet synchronous motor (PMSM). Motivated by the common control engineering knowledge that transient performance can be improved if the P gain is big and the D gain is small in the beginning, a linearizing control scheme with a fuzzy PD controller is proposed. The global system stability is analyzed and the proposed control algorithm is implemented using a TMS320F28335 DSP. Simulation and experimental results are given to verify the effectiveness of the proposed method.

• The Transactions of the Korean Institute of Electrical Engineers B
• /
• v.54 no.8
• /
• pp.395-401
• /
• 2005

This paper presents Hybrid PI(HBPI) controller of induction motor drive using fuzzy control. In general, PI controllers used in computer numerically controlled machines process fixed gain. They may perform well under some operating conditions, but not all. To increase the robustness of fixed gain PI controller, HBPI controller proposes a new method based self tuning PI controller. HBPI 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 induction motor are presented to show the effectiveness of the proposed gam tuner. And this controller is better than the fixed gains one in terms of robustness, even under great variations of operating conditions and load disturbance.

• 제어로봇시스템학회:학술대회논문집
• /
• 1993.10a
• /
• pp.1072-1075
• /
• 1993

To design a fuzzy controller for DC servo-motor, a systematic procedure is proposed. Fuzzy rule base is simply designed through utilizing both the PID gain and the pole-zero cancelation. The results of simulation show that the control system has good performances.

• Proceedings of the KIEE Conference
• /
• 2004.11c
• /
• pp.114-116
• /
• 2004

The temperature profile control issue in the resistive welder for the electronic parts is discussed. The average current of the welder tip depends on the phase(on-time) of the AC power and the tip temperature maintains or increases/decreases depending on the integral of the current square and heat loss, The basic PID control algorithm with thermo-couple feedback is difficult to track the temperature profile for various parts and optimal gain changes much. So constant gain PID algorithm is not enough to cover various electronic parts welding and a Fuzzy-PID automatic gain tuning algorithm is devised and added to conventional PID algorithm and this hybrid control architecture is implemented and the experimental results are shown.

• 제어로봇시스템학회:학술대회논문집
• /
• 2001.10a
• /
• pp.48.5-48
• /
• 2001

The resulting stabilizing controller in this paper consists of the disturbance estimator and the gain scheduled controller. The disturbance estimator tracks the unknown external disturbance and its derivative information in the closed-loop control system using fuzzy logic based adaptation law. Moreover, the gains of the stabilizing controller are appropriately scheduled according to the estimated values. Furthermore, since the estimation law is combined with the stabilizing controller in the closed control loop, it asymptotically minimizes the estimation error. In order to conrm the usefulness of the proposed control scheme, it is applied to the magnetic suspension systems.