• Journal of the Korean Society for Aviation and Aeronautics
• /
• v.26 no.3
• /
• pp.48-54
• /
• 2018

This paper deals with a development of a quad-rotor for a hovering attitude control. First, a rotational dynamics are derived to design an attitude controller. The attitude controller is based on PI (Proportional-Integral) controller. For a stable attitude control, an anti-windup method applies to the PI attitude controller. Additionally, a complementary filter is used to obtain more reliable attitude. Gain values of the attitude controllers based on the anti-windup method are obtained through tests. Finally, the quad-rotor with the anti-windup based PI attitude controller is developed and a hovering attitude control flight tests are performed. As a result, the developed quad-rotor is capable of stable hovering.

• The Transactions of the Korean Institute of Electrical Engineers
• /
• v.43 no.2
• /
• 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.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.17 no.3
• /
• pp.355-367
• /
• 2007

This paper proposes a design method of the PI(Proportional-Integral)+D(Derivative) controller using self-tuning of the design variables and controller gains. The used fuzzy PI+D controller is the approximated conventional continuos time linear PI+D controller and the used fuzzification method is the fuzzy single tone and the adapted defuzzification method is the simplified tenter of gravity. Fuzzy estimation result would be calculated in the other function elements from the classified fuzzy variables and the result determined by the design variables decides the controller gains. As a result, the proposed method shows the capability of the high speed tuning and can be applied to the case of input variables with many fuzzy partitions and also can bring out the advantage to reduce the reconstruction(digital sampling reconstruction) error. Most simulation results show that this controller makes much bettor efficiency and improvement by using design variables and controller gains.

• Proceedings of the KIEE Conference
• /
• 2007.04c
• /
• pp.91-93
• /
• 2007

This paper presents multi-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, fred gain PI controller, Multi-PI controller proposes a new method based fuzzy and neural-network. Multi-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. And this controller is better than the fixed gains one in terms of robustness, even under great variations of operating conditions and load disturbance.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.7 no.3
• /
• pp.117-120
• /
• 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
• /
• 2005.04a
• /
• pp.191-193
• /
• 2005

This paper presents Hybrid PI controller of IPMSM drive using fuzzy adaptive mechanism(FAM) control. To increase the robustness, fixed gam PI controller, Hybrid PI controller proposes a new method based self tuning PI controller. Hybrid 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. And this controller is better than the fixed gains one in terms of robustness, even under great variations of operating conditions and load disturbance.

• Journal of international Conference on Electrical Machines and Systems
• /
• v.3 no.4
• /
• pp.367-373
• /
• 2014

The most common current controller for the Switched Reluctance Motor (SRM) is the hysteresis controller. This method, however, suffers from such drawbacks as variable switching frequency, consequent audible noise and high current ripple. These disadvantages make this controlling method undesirable for many applications. The alternative solution is the PI controller. Since the fixed gain PI current controller can only be optimized for one operating point, and on the other hand, SR motor is highly nonlinear, PI controller gain should be adjusted according to incremental inductance. This paper presents a novel method for PI current controller gain adaptation which is simple and yields a good performance. The proposed controller has been implemented on a test bench using a eZdsp F28335 board. The performance of the current controller has been investigated in both simulation and experimental tests using a four-phase 8/6 4KW SRM drive system.

• Journal of the Institute of Electronics Engineers of Korea SC
• /
• v.45 no.6
• /
• pp.102-107
• /
• 2008

We propose an autotuning algorithm for PI controller with unknown plant. The proposed algorithm uses a saturation function and time delay element as a test signal. Since the integral element of PI controller reduces a phase margin in the closed loop system, the closed loop system could be resulted in unstable with PI controller. To avoid unstable in the closed loop system with PI controller, the proposed algorithm identifies one point information in the 3rd quadrant of Nyquist plot with a time delay element. The proposed method improves an accuracy of one point identified information with one saturation function. We demonstrate a performance of the proposed method via a simulation.

• Journal of Electrical Engineering and Technology
• /
• v.12 no.1
• /
• pp.78-90
• /
• 2017

This paper presents the design of closed loop controllers operating a single-phase AC-DC three-level converter for improving power quality at AC mains. Closed loop inhibits outer voltage controller and inner current controller. Simulations of three level converter with three different voltage and current controller combinations such as PI-Hysteresis, Fuzzy-Hysteresis and Fuzzy tuned PI-Hysteresis are carried out in MATLAB/Simulink. Performance parameters such as input power factor and source current total harmonic distortion (THD) are considered for comparison of the three controller combinations. The fuzzy-tuned PI voltage controller with hysteresis current controller combination provides a better result, with a source-current THD of 0.93% and unity power factor without any source side filter for the three level converter. For load variations of 25% to 100%, a THD of less than 5% is obtained with a maximum value of only 1.67%. Finally, the fuzzy-tuned PI voltage with hysteresis controller combination is implemented in a Xilinx Spartan-6 XC6SLX25 FPGA board for experimental validation of power quality enhancement. A prototype 100 W, 0-24-48 V as output converter is considered for the testing of controller performance. A source-current THD of 1.351% is obtained in the experimental study with a power factor near unity. For load variations of 25% to 100%, the THD is found to be less than 5%, with a maximum value of only 2.698% in the experimental setup which matches with the simulation results.

• Journal of the Institute of Electronics Engineers of Korea SC
• /
• v.44 no.2 s.314
• /
• pp.24-31
• /
• 2007

This paper presents self tuning PI(STPI) controller of IPMSM drive using neural network. In general, PI controller in computer numerically controlled machine process fixed gain. They may perform well under some operating conditions, but not all. To increase the robustness of fixed gain PI controller, STPI controller proposes a new method based neural network. STPI controller is developed to minimize overshoot, rise time and settling time following sudden parameter changes such as speed, load torque and inertia. Also, this paper is proposed speed control of IPMSM using neural network and estimation of speed using artificial neural network(ANN) controller. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The results on a speed controller of IPMSM are presented to show the effectiveness of the proposed gain 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.