• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 1997.11a
• /
• pp.234-238
• /
• 1997

This paper describes the tip force control of a flexible minature arm. The arm is driven by the torques generated by the cells, and the endpoint of the arm is controlled so that it moves in synchrony with the fluctuation of the target and maintains a constant distance to the surface of the traget.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.5 no.1
• /
• pp.83-87
• /
• 2005

This paper deals with the design and evaluation of the robust controller for a synchronous generator excitation system to improve the steady state and transient stability. The nonlinear characteristics of the system is treated as model uncertainties, and then the robust control techniques are introduced into the power system stability design to take into account these uncertainties at the controller design stage. The performance of the designed controller is examined by extensive non-linear time domain simulation. It is shown that the performance of the robust controller is superior to that of the conventional PI controller. This paper also proposes an improved digital exciter control system for a synchronized generator using a digitally designed controller with database. Results show that the proposed control system manifests excellent control performance compared to existing control systems. It has also been confirmed that it is easy for the proposed control system to implement digital control.

• Journal of Institute of Control, Robotics and Systems
• /
• v.13 no.5
• /
• pp.399-405
• /
• 2007

This paper deals with the controller for a stable walking of a humanoid robot using genetic algorithm. A humanoid robot has instability during walking because it isn't fixed on the ground, and its nonlinearities of the joints increase its instability. If controller isn't robust, the robot may fall down at the ground during walking because of its nonlinearities. To solve this problem, robust controller is required to reduce the effect of nonlinearities and to gain the good tracking performance. In this paper, motion controller that is based on fuzzy-sliding mode controller is proposed. This controller can remove the effect of the saturation by limitation of the input voltage. It also includes compensator for reducing the effect of the nonlinearity by backlash and PI controller improving the tracking performance. In here, genetic algorithm is used for searching the optimal gains of the controller. From the given controller, a humanoid robot can moved more preciously. All the processes are investigated through simulations and are verified experimentally in a real joint system for a humanoid robot.

• Journal of the Institute of Electronics Engineers of Korea SC
• /
• v.42 no.6
• /
• pp.77-82
• /
• 2005

This paper is proposed fuzzy neural network(FNN) and artificial neural network(ANN) based on the vector controlled induction motor drive system. The hybrid combination of fuzzy control and neural network will produce a powerful representation flexibility and numerical processing capability. Also, this paper is proposed control and estimation of speed of induction motor using fuzzy and neural network. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The error between the desired state variable and the actual one is back-propagated to adjust the rotor speed, so that the actual state variable will coincide with the desired one. The back propagation mechanism is easy to derive and the estimated speed tracks precisely the actual motor speed. This paper is proposed the experimental results to verify the effectiveness of the new method.

• 제어로봇시스템학회:학술대회논문집
• /
• 2003.10a
• /
• pp.371-376
• /
• 2003

In general, the electronic forklift driven by DC motor drive system is used in the industrial field. Classically, the DC motor is controlled by speed control using proportion control method, by output torque following the load on the plane like a manual operation. But in the industrial field, the electronic forklift is demanded the robust drive mode. Some cases of the mode, there are trouble in torque and speed control following slope capacity. The control is sensitive concerning with slope angle and output speed, various control method is studied for stability of speed control. We apply speed controller for the self-tuning using DSP(TMS320F240) as main controller for high speed processor, embody dynamic characteristic of control compared the PI control to the fuzzy control.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2000.11a
• /
• pp.497-505
• /
• 2000

퍼지 논리 제어기(FLC)는 복잡한 프로세스와 비선형 프로세스와 비선형 프로세스에 사용되기 위해 연구되어져왔다. PI형 퍼지 제어기는 가장 보편적이고 실용적이다. 그러나 종래의 PI형 퍼지 제어기들은 큰 불감대를 가진 시스템이나 비선형 시스템에 대해 큰 오버슛과 과도한 발진으로 인해 불안정하다. 본 논문에서는 PI형 퍼지 제어기에서 제어 입력의 축적에 의해 야기된 오버슛을 제거하기 위한 관점에서, 두 개의 퍼지 제어기를 사용하여 좋은 성능을 이루기 위해, 직접적인 성능치로부터가 아니라, 현재의 프로세스 경향에만 의존하여, 조정하는 제어동작들을 발생하는 자기 동조 메카니즘을 사용하였다. 시뮬레이션 결과, 비선형 프로세스뿐만 아니라 선형의 다양한 형태를 갖는 프로세스에서 제안된 PI형 퍼지 제어기가 종래의 제어기의 성능을 능가한다는 것을 보여준다.

• Journal of Power Electronics
• /
• v.8 no.3
• /
• pp.280-290
• /
• 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
• /
• 2008.10b
• /
• pp.77-78
• /
• 2008

This paper presents to control speed of induction motors with uncertainties. We use an adaptive backstepping controller with fuzzy neural networks(FNNs) and model reference adaptive system(MRAS) at Indirect vector control method. The adaptive backstepping controller using FNNs can control speed of induction motors even we have a minimum of information. And this controller can be used to approximate most of uncertainties which are derived from unknown motor parameters, load torque such as disturbances. MRAS estimates to rotor resistance and also can find optimal flux to minimize power losses of Induction motor. Indirect vector PI current controller is used to keep rotor flux constant without measuring or estimating the rotor flux. Simulation and experiment results are verified the effectiveness of this proposed approach.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
• /
• 2005.05a
• /
• pp.461-466
• /
• 2005

This paper presents a new speed control scheme of the spindle induction motor (IM) using fuzzy-logic control in fold weakening region. The implementation of the proposed FLC-based spindle IM are investigated and compared to those obtained from the conventional PI controller based drive system, we have confirmed good simulation and experimental results at different dynamic operating conditions such as sudden change in command speed, step change, etc.

• Proceedings of the IEEK Conference
• /
• 1998.06a
• /
• pp.901-904
• /
• 1998

In this paper, we describes PID-neural network controller for the rotary inverted pendulum. PID control is applied to many fields but has some problems in nonlinear system due to a variation of parameter. So, we should desing the controller which is adjusted PI parameters by the neural network which is learned by backpropagation algorithm. And we show that on-line control is possible through the PID-neural network controller. The angle of the pendulum is controlled and then the position of the rotating arm is also controlled to maintain with in the set point. Measurement of the pendulum angle is obtained using a potentionmeter. The objective of the experiment is to design a PID-neural network control system that positions the arm as well as maintains the ivnerted pendulum vertical. Finally, we describe the actual experiment system and confirm the experimental results.