• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 1993.06a
• /
• pp.1270-1273
• /
• 1993

Fuzzy optimal control is considered. An optimal sequence of controls is sought best satisfying fuzzy constraints on the controls and fuzzy goals on the states (outputs), with a fuzzy system under control Control over a fixed and specified, implicitly specified, fuzzy, and infinite termination time is discussed. For computational efficiency a small number of reference fuzzy staters and controls is to be assumed by which fuzzy controls and stated are approximated. Optimal control policies reference fuzzy states are determined as a fuzzy relation used, via the compositional rule of inference, to derive an optimal control. Since this requires a large number of overlapping reference fuzzy controls and states implying a low computational efficiency, a small number of nonoverlapping reference fuzzy states and controls is assumed, and then interpolative reasoning is used to infer an optimal fuzzy control for a current fuzzy state.

• Proceedings of the KIPE Conference
• /
• 2011.11a
• /
• pp.285-286
• /
• 2011

Maximum Power Point Tracker (MPPT) is the big issue in generating power based on Wind Energy Conversion System. In case of unknown turbine characteristic, it is useful to implement MPPT based on fuzzy logic control. This kind of control is able to find the value of duty cycle to meet maximum power point at particular wind speed. There are many methods to develop MPPT based fuzzy logic controls. In this paper, two of the methods are compared both at low and high fluctuating wind speed.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 1993.06a
• /
• pp.945-948
• /
• 1993

• Journal of Electrical Engineering and Technology
• /
• v.7 no.4
• /
• pp.546-557
• /
• 2012

In Conventional Combined Vector and Direct Controls (VC-DTC) of induction motor, stator current is very rich in harmonic components. It leads to high torque ripple of induction motor in high and low speed region. To solve this problem, a control method based on the concept of fuzzy logic approach is used. The control scheme proposed uses stator current error as variable. Through the fuzzy logic controller rules, the choice of voltage space vector is optimized and then torque and speed are controlled successfully with a less ripple level in torque response, which improve the system's performance. Simulation results trough MATLAB/SIMULINK${(R)}$ software gave results that justify the claims.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.12 no.3
• /
• pp.238-244
• /
• 2012

A modeling of vision based robot formation control system using fuzzy logic controller and extended Kalman filter is presented in this paper. The main problems affecting formation controls using fuzzy logic controller and vision based robots are: a robot's position in a formation need to be maintained, how to develop the membership function in order to obtain the optimal fuzzy system control that has the ability to do the formation control and the noise coming from camera process changes the position of references view. In order to handle these problems, we propose a fuzzy logic controller system equipped with a dynamic output membership function that controls the speed of the robot wheels to handle the maintenance position in formation. The output membership function changes over time based on changes in input at time t-1 to t. The noises appearing in image processing change the virtual target point positions are handled by Extended Kalman filter. The virtual target positions are established in order to define the formations. The virtual target point positions can be changed at any time in accordance with the desired formation. These algorithms have been validated through simulation. The simulations confirm that the follower robots reach their target point in a short time and are able to maintain their position in the formation although the noises change the target point positions.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 1993.06a
• /
• pp.1414-1417
• /
• 1993

Wang and Medel proved (1991) that fuzzy systems with product inference, centroid defuzzification, and everywhere positive membership functions (in particular, Gaussians, Wang, 1992) are capable of approximating any real continuous control function on a compact set to arbitrary accuracy. Kosko (1992) proved that fuzzy systems, in which membership functions have compact support, and combination operation (V-operation) for rules is the sum, are also universal approximators. In this paper, we generalize this result of Kosko and prove that for any &- and V-operations, any defuzzification procedure, and any basic membership function with a compact support, the resulting fuzzy controls are universal approximators. Also, Wang's result is transfered to min-inference.

• Proceedings of the SAREK Conference
• /
• 2007.06a
• /
• pp.139-139
• /
• 2007

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.5 no.5
• /
• pp.931-940
• /
• 2001

In this paper, I propose Fuzzy Policing Mechanism(FPM) over ATM networks for the control of traffic which is unpredictable and bursty source. The FPM is consist of counter, subtracter and Fuzzy Logic Controller(FLC). The FLC is divided to fuzzifier, inference engine and defuzzifer The output of FLC inputs to the subtractor and it controls the counter. The counter works as a switch in transmission of cells. In simulation, I compared the FPM with the Leaky Bucket algorithm(LBM) in cell loss probability and performance characteristics. As a result, FPM gives lower cell loss probability than that of LBM and has good response behavior The FPM efficiently controls the transmission of packets which are variable traffic source and, it also has good selectivity.

• Proceedings of the KIPE Conference
• /
• 2001.10a
• /
• pp.380-383
• /
• 2001

The paper presents a cost effective and increased performance position servo system using the TMS320F240 digital signal processor (DSP) produced by Texas Instruments as microprocessor and Brushless Direct Current Motor (BLDCM) as executor. In order to make up for the drawback of conventional PID controls, the fuzzy PID is employed. The result of simulations and experiments has confirmed that the whole system is simple and reliable; the robustness of system is improved by using fuzzy PID.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2004.04a
• /
• pp.454-457
• /
• 2004

In this paper, control method proposed for effective speed control of the induction motor indirect vector control. For the induction motor drive, indirect vector control scheme that controls torque current and flux current of the stator current independently so that it can have improved dynamics. Also, neuro-fuzzy algorithm employed for torque current control in order to optimal speed control The proposed neuro-fuzzy algorithm can be applied to the precise speed control of an induction motor drive system or the field of any other power systems.