• Journal of Advanced Marine Engineering and Technology
• /
• v.20 no.4
• /
• pp.11-19
• /
• 1996

Recently, fuzzy and neural network techniques have been successfully applied to control of complex and ill-defined system in a wide variety of areas, such as robot, water purification, automatic train operation system and automatic container crane operation system, etc. In this paper, we present a neuro-fuzzy controller which unifies both fuzzy logic and multi-layered feedforward neural networks. Fuzzy logic provides a means for converting linguistic control knowledge into control actions. On the other hand, feedforward neural networks provide salient features, such as learning and parallelism. In the proposed neuro-fuzzy controller, the parameters of membership functions in the antecedent part of fuzzy inference rules are identified by using the error backpropagation algorithm as a learning rule, while the coefficients of the linear combination of input variables in the consequent part are determined by using the least square estimation method. Finally, the effectiveness of the proposed controller is verified through computer simulation of an inverted pendulum system.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.8 no.1
• /
• pp.68-74
• /
• 2008

In this paper, a novel neural fuzzy control method is proposed to control nonlinear systems. A standard PD-like fuzzy controller is designed and used as a main controller for the system. Then a neural network controller is added to the reference trajectories to form a neural-fuzzy control structure and used to compensate for nonlinear effects. Two neural-fuzzy control schemes based on two well-known neural network control schemes, the feedback error learning scheme and the reference compensation technique scheme as well as the standard PD-like fuzzy control are studied. Those schemes are tested to control the angle and the position of the inverted pendulum and their performances are compared.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.21 no.3
• /
• pp.361-368
• /
• 1997

In order to eliminate position errors existing at the steady state in the motion control of robotic manipulators, a new fuzzy control algorithm is propeosed using three variables, position error, velocity error and integral of position errors as input variables of the fuzzy controller. Although the number of input variables of the fuzzy controller is increased from two to three, the number of fuzzy control rules is just increased by two. Three dimensional look-up table is used to reduce the computational time in real-time control, and a technique reducing the amount of necessary memory is introduced. Simulation and experimental studies show that the position errors at the steady state are decreased more than 90% compared to those of existing fuzzy controller when the proposed fuzzy controller is applied to the 2 axis direct drive SCARA robot manipulator.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.25 no.2
• /
• pp.103-112
• /
• 2011

This paper proposes a new fuzzy speed controller for the precise speed control of a permanent magnet synchronous motor(PMSM). The proposed control system needs the information of the angular acceleration instead of the load torque, so the third-order fuzzy acceleration observer estimates it. Moreover, the LMI conditions are derived for the existence of the fuzzy acceleration observer and fuzzy speed controller, and the gain matrices of the observer and controller are obtained. It is analytically proven that the proposed observer-based fuzzy speed regulator is exponentially stable. To evaluate the performance of the proposed control algorithm, experimental results as well as simulation results are provided under the conditions of motor parameter and load torque variations. Finally, it is clearly confirmed that the proposed control method can accurately control the speed of a PMSM.

• 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.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2000.11a
• /
• pp.157-160
• /
• 2000

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 high 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. The group elevator system utilizing adaptive dual fuzzy control reveals a great deal of improvement on its performance.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.5 no.3
• /
• pp.36-51
• /
• 1995

An approach to robot hybrid position/force control, which allows force manipulations to be realized without overshoot and overdamping while in the presence of unknown environment, is given in this paper. The manin idea is to used dynamic compensation for known robot parts and fuzzy compensation for unknown environment so as to improve system performance. The fuzzy compensation is implemented by using rule based fuzzy approach to identify the unknown environment. The establishment of proposed control system consists of following two stages. First, similar to the resovled acceleration control method, dynamic compensation and PD control based on known robot dynamics, kinematics and estimated environment stiffness is introduced. To avoid overshoot the whole control system is constructed with overdamping. In the second stage, the unknown environment stiffness is identified by using fuzzy reasoning, where the fuzzy compensation rules are obtained priori as the expression of the relationship betweenenvironment stiffness and system. Based on the simulation result, comparison between cases with or without fuzzy identifications are given, which illustrate the improvement achieced.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.12 no.2
• /
• pp.154-161
• /
• 2012

This article presents experimental studies of fuzzy logic application to control a two-wheel mobile robot(TWMR) system. The TWMR system is composed of two systems, an inverted pendulum system and a mobile robot system. Although linear controllers can stabilize the TWMR, fuzzy controllers are expected to have robustness to uncertainties so that the resulting performances are expected to be better. Nominal fuzzy rules are used to control balance and position of TWMR. Fuzzy logic is embedded on a DSP chip to control the TWMR. Balancing performances of the PID controller and the fuzzy controller under disturbances are compared through extensive experimental studies.

• Proceedings of the Computational Structural Engineering Institute Conference
• /
• 2004.04a
• /
• pp.409-416
• /
• 2004

An active modal-fuzzy control method using hydraulic actuators is presented for seismic response reduction. In the proposed control system, a new fuzzy controller designed in the modal space produces the desired active control force. This type controller has all advantages of the fuzzy control algorithm and modal approach. Since it is very difficult to select input variables used in fuzzy controller among an amount of state variables in the active fuzzy control system the presented algorithm adopts the modal control algorithm which is able to consider more easily information of all state variables in civil structures that are usually dominated by first few modes. In other words, all information of the whole structure can be considered in the control algorithm evaluated to reduce seismic responses and it can be efficient for especially civil structures. In addition, the presented algorithm is expected to magnify utility and performance caused by efficiency that the fuzzy algorithm can handle complex model more easily. An active modal-fuzzy control scheme is applied together with a Kalman filter and a low-pass filter to be applicable to real civil structures. A Kalman filter is considered to estimate modal states and a low-pass filter was used to eliminate spillover problem. The results of the numerical simulations far a wide amplitude range o f loading conditions and for historic earthquakes having various frequency components show that the proposed active modal-fuzzy control system can be beneficial in reducing seismic responses of civil structures.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.60 no.10
• /
• pp.1978-1983
• /
• 2011

BLDC motor is used in a wide variety of industrial and servo applications. Its features and advantages mainly consist in high value of torque/inertia ratio, high efficiency with speed range and high dynamic performance. This paper deals with the speed control of a trapezoidal type brushless DC motor using Fuzzy PI controller. The conventional PI controller has been widely used in industrial applications. If we select a optimal PI control gain, the PI controller shows very good control performance. But it is very difficult to find the optimal PI control gain. Fuzzy control does not need any model of plant and is basically adaptive and gives robust performance for plant parameter variation. Therefore the combinations of conventional PI controller and fuzzy controller seem to be very effective. This paper deals with PI controller with 4-rule based fuzzy controller. The proposed fuzzy PI controller increases the control performance of the conventional PI controller. Simulation and experimental results show that fuzzy PI controller has a good robustness regarding the improper tuned PI controller.