• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2292-2295
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• 2001

In this paper, The control problem for a series DC motor is considered to adaptive fuzzy sliding-mode control scheme. Based on a nonlinear mathematical model of a series connected DC motor, instead of the combination of a nonlinear transformation and state feedback(feedback linearization) reduces the nonlinear control design. To demonstrate its effectiveness, an experimental study of this controller is presented. Two sets of fuzzy rule bases are utilized to represent the equivalent control input with unknown system functions of the main target. The membership functions of the THEN-part, which is used to construct a suitable equivalent control of SMC, are changed according to the adaptive law. With such a design scheme, we not only maintain the distribution of membership functions over state space but also reduce computing time considerably.

• Journal of Electrical Engineering and Technology
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• v.10 no.6
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• pp.2393-2405
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• 2015

This paper considers a decentralized multiple faults detection and isolation (FDI) scheme for reconfigurable manipulators. Inspired by their modularization property, a global sliding mode (GSM) based stable adaptive fuzzy decentralized controller is investigated for the system in fault free, while for the system suffering from multiple faults (actuator fault and sensor fault), the decentralized sliding mode observer (DSMO) is employed to detect their occurrence. Hereafter, the time and location of faults can be determined by a fault isolation scheme via a bank of DSMOs. Finally, the effectiveness of the proposed schemes in controlling, detecting and isolating faults is illustrated by the simulations of two 3-DOF reconfigurable manipulators with different configurations successfully.

• Proceedings of the KIEE Conference
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• 2009.04a
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• pp.74-76
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• 2009

In this paper, search method and sliding mode observer are developed for efficiency optimization of induction motor. The proposed control scheme consists of efficiency controller and adaptive backstepping controller. A search controller for which information of input of fuzzy controller is included in efficiency controller that uses a direct vector controlled induction motor. The search controller is based on the "Rosenbrock" method and finds the flux level at the minimum input power of induction motor. Once this optimal flux level has been determined, this information is utilized to update the rule base of a fuzzy controller A sliding mode observer is designed to estimate rotor flux and an adaptive backstepping controller is also used to compensate for mechanical uncertainties in the speed control of induction motor. Simulation results are presented to validate the proposed controller.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.13 no.1
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• pp.31-38
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• 1999

In this paper, we proposed a fuzzy sliding mode controller for a robot manipulator with passive joints. A robot manipulator with passive joints which is not equipped with actuators is a kind of underactuated systerms. The control of underactuated manipulators is more difficult than that of fully-actuated ones. Though the sliding mode control technique has a robust charocteristics to prrarreter uncertainties and external disturbances, the chattering phenomena becorne one of the major problems in application to the real plant. plant.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.781-787
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• 1999

In this note, we propose two methods of adaptive sliding mode control(SMC) schemes in which fuzzy systems(FS) are utilized to approximate the unknown system functions. In the first method, a FS is utilized to approximate the unknown function f of the nonlinear system $\chi$$^{(n)}$$\chi$＝f(equation omitted), t)＋b(equation omitted), t)u and the robust adaptive law is proposed to reduce the approximation errors between the true nonlinear function and fuzzy approximator, FS. In the second method, two FSs are utilized to approximate f and b, respectively. The robust control law is also designed. The stabilities of proposed control schemes are proved.

• Journal of the Korean Institute of Intelligent Systems
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• v.9 no.6
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• pp.605-614
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• 1999

This paper addresses analysis and design of a class of complex single-input single-output fuzzy control systems. In the proposed method, the fuzzy model, which represents the local dynamic behavior of the given nonlinear system, is utilized to construct the controller. The overall controller consists of the local compensators which compensate the local dynamic linear model and the feed-forward controller which is designed via sliding mode control theory. Therefore, the globally stable fuzzy controller is designed without finding a common Lyapunov matrix. and shows improved perfonnance and tracking results by taking the advantages of fuzzy-model-based control theory and sliding mode control theory. Furthennore, stability analysis is conducted not Ibr the fuzzy model but for the real underlying nonlinear system. Two numerical examples are included to show the effcctiveness and feasibility of the proposed fuzzy control method.

• ETRI Journal
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• v.40 no.5
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• pp.653-663
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• 2018

Patients with spinal cord injuries cannot move their limbs using their intact muscles. A suitable controller can be used to move their arms by employing the functional electrical stimulation method. In this article, a fuzzy exponential sliding-mode controller is designed to move a musculoskeletal human arm model to track an optimal trajectory in the sagittal plane. This optimal arm trajectory is obtained by developing a policy for the central nervous system. In order to specify the optimal trajectory between two points, two dynamic and static optimal criteria are applied simultaneously. The first dynamic objective function is defined to minimize the joint torques, and the second static optimization is offered to minimize the muscle forces at each moment. In addition, fuzzy logic is used to tune the sliding-surface parameter to enable an appropriate tracking performance. Simulation results are evaluated and compared with experimental data for upward and downward movements of the human arm.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.10a
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• pp.449-452
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• 1997

In this paper, we suggest a variable structure controller using the time-varying nonlinear sliding surface instead of the fixed sliding surface, which has been the robustness against parameter variations and extraneous disturbance during the reaching phase. As appling TS fuzzy algorithm to the regulation of the nonlinear sliding surface, the reaching time of the system trajectory is faster than the fixed method . This proposed scheme has better performance than the conventional method in reaching time parameter variation and extraneous disturbance. To demonstrate its performance, the proposed control algorithm is applied to a rotational inverted pendulum.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.110-110
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• 2000

In this paper, an antilock brake system (ABS) for commercial vehicles is studied by considering the design of a fuzzy Logic controller with pulse width modulation (PWM). PWM method is used for generating solenoid valve inputs in order to cope with the chattering problem caused by the conventional on/off control The sliding mode observer is designed to estimate the vehicle longitudinal velocity and it is used to calculate the wheel slip ratio. The effectiveness of the proposed control algorithm was validated by simulations performed with a nonlinear 14-DOF vehicle model including the dynamics of the brakes.

• Journal of the Korean Society for Precision Engineering
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• v.25 no.12
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• pp.89-99
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• 2008

In this paper, the position tracking control problem of the servo system with nonlinear dynamic friction is issued. The nonlinear dynamic friction contains a directly immeasurable friction state variable and the uncertainty caused by incomplete parameter modeling and its variations. In order to provide the efficient solution to these control problems, we propose the composite control scheme, which consists of the robust friction state observer, the FNN approximator and the approximation error estimator with sliding mode control. In first, the sliding mode controller and the robust friction state observer is designed to estimate the unknown internal state of the LuGre friction model. Next, the FNN estimator is adopted to approximate the unknown lumped friction uncertainty. Finally, the adaptive approximation error estimator is designed to compensate the approximation error of the FNN estimator. Some simulations and experiments on the servo system assembled with ball-screw and DC servo motor are presented. Results show the remarkable performance of the proposed control scheme. The robust friction state observer can successfully identify immeasurable friction state and the FNN estimator and adaptive approximation error estimator give the robustness to the proposed control scheme against the uncertainty of the friction parameters.