• Smart Structures and Systems
• /
• v.19 no.5
• /
• pp.577-585
• /
• 2017

In this paper, an adaptive fuzzy sliding mode controller (AFSMC) is designed to reduce dynamic responses of seismically excited structures. In the conventional sliding mode control (SMC), direct implementation of switching-type control law leads to chattering phenomenon which may excite unmodeled high frequency dynamics and may cause vibration in control force. Attenuation of chattering and its harmful effects are done by using fuzzy controller to approximate discontinuous part of the sliding mode control law. In order to prevent time-consuming obtaining of membership functions and reduce complexity of the fuzzy rule bases, adaptive law based on Lyapunov function is designed. To demonstrate the performance of AFSMC method and to compare with that of SMC and fuzzy control, a linear three-story scaled building is investigated for numerical simulation based on the proposed method. The results indicate satisfactory performance of the proposed method superior to those of SMC and fuzzy control.

• The Transactions of the Korean Institute of Electrical Engineers D
• /
• v.49 no.8
• /
• pp.407-414
• /
• 2000

This paper addresses the analysis and design of fuzzy control systems for a class of complex uncertain single-input single-output nonlinear systems. The proposed method represents the nonlinear system using a Takagi-Cugeno fuzzy model and construct a global fuzzy logic controller by blending all local state feedback controllers with a sliding mode controller. Unlike the commonly used parallel distributed compensation technique, we can design a global stable fuzzy controller without finding a common Lyapunov function for all local control systems, and can obtain good tracking performance by using sliding mode control theory. Furthermore, stability analysis is carried out not for the fuzzy model but for the real nonlinear system with uncertainties. Duffing forced oscillation sysmte is used as an example to show the effectiveness and feasibility of the proposed method.

• 제어로봇시스템학회:학술대회논문집
• /
• 2005.06a
• /
• pp.1516-1520
• /
• 2005

We proposed the indirect adaptive fuzzy model based sliding mode controller to control a nonaffine nonlinear systems. Takagi-Sugano fuzzy system is used to represent the nonaffine nonlinear system and then inverted to design the controller at each sampling time. Also sliding mode component is employed to eliminate the effects of disturbances, while a fuzzy model component equipped with an adaptation mechanism reduces modeling uncertainties by approximating model uncertainties. The proposed controller and adaptive laws guarantee that the closed-loop system is stable in the sense of Lyapunov and the output tracks a desired trajectory asymptotically.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2006.11a
• /
• pp.323-326
• /
• 2006

Rotational inverted pendulum is a typical under-actuated system. For its highly nonlinear characteristic, a sliding mode controller is chosen for its robustness against the system uncertainties. Tow fuzzy inference mechanisms are applied in this paper to reduce the chattering phenomenon. One is proposed to construct a time-varying sliding surface. Another one is used to obtain the minimum upper bound of the uncertainties. A comparison between the conventional sliding mode and the fuzzy sliding mode is shown by simulations.

• 제어로봇시스템학회:학술대회논문집
• /
• 2002.10a
• /
• pp.62.6-62
• /
• 2002

$\textbullet$ Introduction $\textbullet$ Problem Formulation $\textbullet$ Feedback Linearizing Controller Design $\textbullet$ Fuzzy System to Cancel System Uncertainty $\textbullet$ Adatptive Fuzzy Sliding Mode Controller Design $\textbullet$ Simulations $\textbullet$ Conclusions

• Proceedings of the IEEK Conference
• /
• 2002.07c
• /
• pp.1483-1486
• /
• 2002

In this paper, a new scheme of iterative loaming control of a robot manipulator is presented. The proposed method uses a fuzzy sliding mode controller(FSMC), which is designed based on the similarity between the fuzzy logic control(FLC) and the sliding mode control(SMC), for the feedback. With this, the proposed method makes possible fDr fast iteration and has advantages that no linear approximation is used for the derivation of the learning law or in the stability proof Full proof of the convergence of the fuzzy sliding base learning scheme Is given.

• Journal of Mechanical Science and Technology
• /
• v.15 no.3
• /
• pp.339-350
• /
• 2001

To overcome problems in tracking error related to the unmodeled dynamics in the high speed operation of industrial robots, many researchers have used sliding mode control, which is robust against parameter variations and payload changes. However, these algorithms cannot reduce the inherent chattering which is caused by excessive switching inputs around the sliding surface. This study proposes a fuzzy-sliding mode control algorithm to reduce the chattering of the sliding mode control by fuzzy rules within a pre-determined dead zone. Trajectory tracking simulations and experiments show that chattering can be reduced prominently by the fuzzy-sliding mode control algorithm compared to a sliding mode control with two dead zones, and the proposed control algorithm is robust to changes in payload. The proposed control algorithm is implemented to the SCARA (selected compliance articulated robot assembly) robot using a DSP (digital signal processor) for high speed calculations.

• Journal of Institute of Control, Robotics and Systems
• /
• v.16 no.8
• /
• pp.735-743
• /
• 2010

A new Fuzzy sliding mode controller is proposed to improve the cornering performance of the four wheel hybrid vehicles. The Fuzzy sliding mode control is applied for the control of rear motor and EHB (Electro-Hydraulic Brake) to improve the cornering performance. The modeling of the automobile is simplified that each of the two wheels is modeled as two degrees of freedom object and the friction coefficient between the wheel and the ground is assumed to be constant. The output of the Fuzzy sliding mode algorithm is the direct yaw moment for the rear wheels, which compensates for the slip angle. Through the simulations using ADAMS and MATLAB Simulink, the cornering performance of the proposed algorithm is compared to the conventional PID to show the superiority of the proposed algorithm. In the simulation experiments, the J-Turn and single lane change are used for each of the Fuzzy sliding mode algorithm and PID controller with the optimal gains which are tuned empirically.

• Proceedings of the KIPE Conference
• /
• 2000.07a
• /
• pp.624-627
• /
• 2000

An adaptive fuzzy sliding-mode control system which combines the merits of sliding-mode control the fuzzy inference mechanism and the adaptive algorithm is proposed. A fuzzy sliding-mode controller is investigated in which a simple fuzzy inference mechamism is used to estimate the upper bound of uncertainties., The fuzzy inference mechanism with centre adaptation of membership functions is investigated to estimate the optimal bound of uncertainties.

• 제어로봇시스템학회:학술대회논문집
• /
• 2000.10a
• /
• pp.284-284
• /
• 2000

In adaptive fuzzy control systems. fuzzy systems are used to approximate the unknown plant nonlinearities. Until now. most of the papers in the field of controller design for nonlinear system using fuzzy systems considers the affine system with fixed grid-rule structure based on system state availability. This paper considers observer-based nonlinear controller and dynamic fuzzy rule structure. Adaptive laws for fuzzy parameters for state observer and fuzzy rule structure are established so that the whole system is stable in the sense of Lyapunov.