• International Journal of Automotive Technology
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• v.7 no.2
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• pp.167-172
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• 2006

A design of controller for vehicle dynamic control(VDC) and its implementation on the real vehicle were introduced. The controller has been designed using a three-degrees-of-freedom(3DOF) yaw plane vehicle, and the control algorithm was implemented on the vehicle by control prototyping system dSPACE. A hybrid control algorithm, which makes full use of the advantages of robust and fuzzy control, was adopted in the control system. Field test results show that the performance of the vehicle handling dynamics with hybrid controller is improved obviously compared to that without VDC and with simple robust controller on skiddy roads(friction coefficients lower than 0.3).

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.23 no.7
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• pp.29-40
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• 2009

This paper proposes a modeling and controller design approach for a hybrid wind power generation system that considers a fixed wind-turbine and a dump load. Since operating conditions are kept changing, it is challenge to design a control for reliable operation of the overall system To consider variable operating conditions, Takagi-Sugeno (TS) fuzzy model is taken into account to represent time-varying system by expressing the local dynamics of a nonlinear system through sub-systems, partitioned by linguistic rules. Also, each fuzzy model has uncertainty. Thus, in this paper, a modem nonlinear control design technique, the sliding mode nonlinear control design, is utilized for robust control mechanism In the simulation study, the proposed controller is compared with a proportional-integral (PI) controller. Simulation results show that the proposed controller is more effective against disturbances caused by wind speed and load variation than the PI controller, and thus it contributes to a better quality wind-hybrid power generation system.

• Journal of the Korean Society of Industry Convergence
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• v.19 no.3
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• pp.101-108
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• 2016

I propose a hybrid fuzzy controller with a look-up table to improve the performance of the FARMA(Fuzzy Auto-regressive Moving Average) fuzzy controller. The hybrid structure of the proposed method is composed of a fuzzy controller with a look-up table of the PD type and the FARMA fuzzy controller. The proposed method improves poor performance due to the lack of I/O data to calculate predictive output and shows robust performance over the FARMA fuzzy controller when a incorrect Dmax value is selected by trial and error. I executed some computer simulations on the regulation problem of an inverted pendulum system and compared the results with those of the FARMA fuzzy controller.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.3
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• pp.372-377
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• 2011

This paper propose the robust stability algorithm for controlling a hybrid magnetic bearing system. The control object in the magnetic bearing system enables the rotor to rotate without any physical contact by using magnetic force. Generally, the system dynamics of the magnetic bearing system has severe nonlinearity and uncertainty so that it is not easy to obtain the control objective. For solving these problems, we propose the fuzzy modelling and robust control algorithm for hybrind magnetic bearing system. The sufficient conditions for robust controller are obtained in terms of solutions to linear matrix inequalities (LMIs). Simulation results for HMB are demonstrated to visualize the feasibility of the proposed method.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.18 no.1
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• pp.90-102
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• 2009

In this paper, a tracking control problem for a mechanical servo system with nonlinear dynamic friction is treated. The nonlinear friction model contains directly immeasurable friction state and the uncertainty caused by incomplete modeling and variations of its parameter. In order to provide the efficient solution to these control problems, we propose a hybrid control scheme, which consists of a robust friction state observer, a RFNN estimator and an approximation error estimator with sliding mode control. A sliding mode controller and a robust friction state observer is firstly designed to estimate the unknown infernal state of the LuGre friction model. Next, a RFNN estimator is introduced to approximate the unknown lumped friction uncertainty. Finally, an adaptive approximation error estimator is designed to compensate the approximation error of the RFNN estimator. Some simulations and experiments on the mechanical servo system composed of ball-screw and DC servo motor are presented. Results demonstrate the remarkable performance of the proposed control scheme.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.10a
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• pp.111-116
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• 1998

This paper proposes a robust control using a sliding mode controller and a fuzzy controller. Having the excellent transient response, the sliding mode controller has the poor steady state response, but the fuzzy controller has a good steady state reponse. A proposed controller combined these controllers has the quick response at the initial condition without the errors. The proposed robust nonlinear controller takes the advantage of the fuzzy controller and is the rapid and the stable response in conditions that the sliding mode controller keeps the errors at the steady state. The performance of proposed method is proved by simulation of the inverted pendulum.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.29B no.10
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• pp.59-68
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• 1992

In this paper, we proposed coordinator description and ambiguity on the hybrid controller for position/force control of robot manipulator. When the hybrid controller is desiged based on the PID control conception, the parameter sharing problem must be considered. However, selection problem of coordinate system on n-DOF robot manipulator control is unsolved. Moreover, contact force on object and change of shape make another problems. And it is very difficult to figure out the accurate mathematical model of manipulator on account of ambiguity and nonlinearity of actuator. Therfore, we design a new hybrid controller, FPID(Fuzzy PID). For verifying the validity of the controller, we tried computer simulation of this system. As a result, we can get remarkable improvement of overdamping and overshooting. Also we can solve compicance problem effectively. Furthermore, ambiguity problem is solved by adding control knowledge based compensator. So robust controller can be acheived, too.

• Journal of Electrical Engineering and Technology
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• v.4 no.4
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• pp.499-509
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• 2009

Electric vehicles (EV) are developing fast during this decade due to drastic issues on the protection of environment and the shortage of energy sources, so new technologies allow the development of electric vehicles (EV) by means of electric motors associated with static converters. The proposed propulsion system consists of two induction motors (IM) that ensure the drive of the two back driving wheels. The electronic differential system ensures the robust control of the vehicle behavior on the road. It also allows controlling, independently, every driving wheel to turn at different speeds in any curve. This paper presents the study of an hybrid Fuzzy-sliding mode control (SMC) strategy for the electric vehicle driving wheels, stability improvement, in which the fuzzy logic system replace the discontinuous control action of the classical SMC law. Our electric vehicle fuzzy-sliding mode control's simulated in Matlab SIMULINK environment, the results obtained present the efficiency of the proposed control with no overshoot, the rising time is perfected with good disturbances rejections comparing with the classical control law.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.7
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• pp.31-41
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• 1993

In this paper, a fuzzy adaptive controller is proposed for the process with large delay time and unmodelled dynamics. The fuzzy adaptive controller consists of self tuning controller and fuzzy tuning part. The self tuning controller is designed with the continuous time GMV (generalized minimum variance) using emulator and weighted least square method. It is realized by the hybrid method. The controller has robust characteristics by adapting the inference rule in design parameters. The inference processing is tuned according to the operating point of the process having the nonlinear characteristics considering the practical application. We review the characteristics of the fuzzy adaptive controller through the simulation. The controller is applied to practical electric furnace. As a result, the fuzzy adaptive controller shows the better characteristics than the simple numeric self tuning controller and the PI controller.

• Journal of Power System Engineering
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• v.10 no.4
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• pp.159-164
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• 2006

In recent, the marine engine of a large size is being realized a lower speed, longer stroke and a small number of cylinders for the energy saving. Consequently the variation of rotational torque became larger than former days because of the longer delay-time in fuel oil injection process and an increased output per cylinder. It was necessary that algorithms have enough robustness to suppress the variation of the delay-time and the parameter perturbation. This paper shows the structure of hybrid F-NFC against the delay-time and the perturbation of engine parameter as modeling uncertainties, and the design of the robust speed controller by hybrid F-NFC for the engine. And, The Parameter values of linear equation are determined by RC-GA for F-NFS. The hybrid F-NFC is combined the F-NFC and PID controller for filling up each.