• The Transactions of the Korean Institute of Electrical Engineers D
• /
• v.55 no.4
• /
• pp.154-157
• /
• 2006

This paper is proposed hybrid artificial intelligent(HAI) controller for high performance of induction motor drive. The design..of this algorithm based on fuzzy-neural network(FNN) controller that is implemented using fuzzy control and neural network. This controller uses fuzzy rule as training patterns of a neural network. Also, this controller uses the back-propagation method to adjust the weights between the neurons of neural network in order to minimize the error between the command output and actual output. A model reference adaptive scheme is proposed in which the adaptation mechanism is executed by fuzzy logic based on the error and change of error measured between the motor speed and output of a reference model. The control performance of the adaptive FNN controller is evaluated by analysis for various operating conditions. The results of experiment prove that the proposed control system has strong high performance and robustness to parameter variation, and steady-state accuracy and transient response.

• Proceedings of the KIEE Conference
• /
• 2001.07b
• /
• pp.1179-1181
• /
• 2001

For high performance induction motor drives such as mill drives, elevator, spindle drive, NC and so on, smart speed controls is usually required, that requires a precise current control. This paper is proposes design of fuzzy controller which makes use of the output voltage of the space vector PWM inverter. Also, proposes the performance fuzzy controller for high performance vector control of induction motor drive system. The performance of a fuzzy controller is compared with that of an PI controller in an internal loop. The validity of the proposed technique is confirmed by simulation results for induction motor drive system.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
• /
• 2009.10a
• /
• pp.355-358
• /
• 2009

This paper proposes efficiency optimization control of IPMSM drive using multi hybrid fuzzy controller(HFC). The design of the speed controller based on fuzzy-neural network that is implemented using fuzzy control and neural network. The design of the current based on HFC using model reference and the estimation of the speed based on neural network using ANN controller. In order to maximize the efficiency in such applications, this paper proposes the optimal control method of the armature current. The controllable electrical loss which consists of the copper loss and the iron loss can be minimized by the optimal control of the armature current. The minimization of loss is possible to realize efficiency optimization control for the proposed IPMSM The optimal current can be decided according to the operating speed and the load conditions. This paper considers the design and implementation of novel technique of high performance speed control for IPMSM using multi HFC. Also, this paper proposes speed control of IPMSM using HFC1, current control of HFC2-HFC3 and estimation of speed using ANN controller. The proposed control algorithm is applied to IPMSM drive system controlled HFC, the operating characteristics controlled by efficiency optimization control are examined in detail.

• 제어로봇시스템학회:학술대회논문집
• /
• 2000.10a
• /
• pp.233-233
• /
• 2000

Direct torque control (DTC) scheme provides a very quick torque response without the complex field-orientation block and inner current regulation loop. DTC is known as an appropriate scheme for high power induction motet drives because it can be used at lower switching frequency. There are two major drawbacks with the application of DTC schemes : one is large current harmonics due to flux drooping in a low speed range, the other is that the inverter switching frequency is varying according to motor parameters and operating speed. Switching devices in the power electronics drives should be supported for relatively high switching frequency. In this paper, a P-type fuzzy controller to realize the variable switching sector scheme and a PID-type fuzzy switching frequency regulator are adopted. A meaningful contribution of this paper is to propose a simple realization scheme of the fuzzy switching frequency regulator. Simulation results show the effectiveness of those propositions.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2001.04a
• /
• pp.578-581
• /
• 2001

In this paper, the development of a new group controller for high-speed elevator is carried out utilizing approach of an adaptive dual fuzzy logic. A goals of control are the minimization of waiting time, mean-waiting time and long-waiting time in a building. when a new hall call is generated, adaptive dual fuzzy controller evaluate traffic pattern and change appropriately the membership function of fuzzy rule base. Control for co-operation among elevators in group control algorithm are essential, and the most critical control function in group controller is a effective and proper hall call assignment of elevators. Thy group elevator system utilizing adaptive dual fuzzy control reveals a great deal of improvement on its performance.

• Journal of Institute of Control, Robotics and Systems
• /
• v.6 no.1
• /
• pp.35-41
• /
• 2000

This paper describes the design of fuzzy digital PID controller using a simplified indirect inference method. First, the fuzzy digital PID controller is derived from the conventional continuous-time linear digital PID controller,. Then the fuzzification, control-rule base, and defuzzification using SIM in the design of the fuzzy controller are discussed in detail. The resulting controller is a discrete-time fuzzy version of the conventional PID controller, which has the same linear structure, but are nonlinear functions of the input signals. The proposed controller enhances the self-tuning control capability, particularly when the process to be controlled is nonlinear. When the SIIM is applied the fuzzy inference results can be calculated with splitting fuzzy variables into each action component and are determined as the functional form of corresponding variables. So the proposed method has the capability of the high speed inference and adapting with increasing the number of the fuzzy input variables easily. Computer simulation results have demonstrated that the proposed method provides better control performance than the one proposed by D. Misir et al.

• Transactions of the Korean Society of Machine Tool Engineers
• /
• v.13 no.5
• /
• pp.110-117
• /
• 2004

In automatic welding process using a robot, seam tracking is one of the important parts. Sensor for seam tracking is divided broadly into two categories as non contact sensor and contact sensor. The arc sensor is one of the non contact sensors, and it can be applied in weaving arc and rotating arc welding process. In such the arc sensors, rotating arc sensor can be applied to high speed welding over tens of Hz. The decrease of self regulation by high rotating speed causes to improve accuracy and response of sensor. In this study, fuzzy controller was used to track the seam for the $CO_2$ arc welding which had unstable arc. It could be shown that the rotating arc sensor was better than the weaving arc sensor.

• Proceedings of the KIEE Conference
• /
• 1993.07b
• /
• pp.707-710
• /
• 1993

In this paper, we design the high accuracy speed controller of an induction motor by the Fuzzy control algorithms, which recently is invoking the remarkable interest. In order to improve the dynamic resposes such as the steady state error, the reaching tine and the overshoot, the adjustment techniques for optimization of three scale factors are presented. Comparing with conventional PID control, the usefulness of proposed Fuzzy controller will be proved by the simulations.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.20 no.3
• /
• pp.53-61
• /
• 2006

This paper is proposed adaptive fuzzy-neuro controller for high performance of induction motor drive. The design of this algorithm based on fuzzy-neural network controller that is implemented using fuzzy control and neural network. This controller uses fuzzy nile as training patterns of a neural network. Also, this controller uses the back-propagation method to adjust the weights between the neurons of neural network in order to minimize the error between the command output and actual output. A model reference adaptive scheme is proposed in which the adaptation mechanism is executed by fuzzy logic based on the error and change of error measured between the motor speed and output of a reference model. The control performance of the adaptive fuzzy-neuro controller is evaluated by analysis for various operating conditions. The results of experiment prove that the proposed control system has strong high performance and robustness to parameter variation, and steady-state accuracy and transient response.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.11 no.12
• /
• pp.2352-2360
• /
• 2007

Due to the friction characteristics of cylinders and the rail of a passenger car, in the elevator actuated with hydraulic systems, there exist dead zones, which can not be controlled by a PID controller. In this paper, the friction characteristics of a cylinder is examined, which may cause the abrupt increase of the acceleration in the zero-costing speed region. To overcome the drawbacks of a PID controlled hydraulic elevator system, a zooming fuzzy logic controller is designed and finally an improved hybrid fuzzy controller is proposed. The effectiveness of the proposed control scheme are shown by simulation and experimental results, which the proposed fuzzy hybrid control method yields good control performance not only in the zero-crossing speed region but also in the overall control region including steady-state region.