• Journal of Institute of Control, Robotics and Systems
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• v.7 no.12
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• pp.973-979
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• 2001

Sliding mode control guarantees robustness in the presence of modeling uncertainties and external disturbances. However, this can be obtained at the cost of high control activity that may lead to chattering As one way to alleviate this problem a boundary layer around sliding surface is typically used. In this case the selection of controller gain, control ban width and boundary layer thickness is a crucial problem for the trade-off between tracking error and chattering. The parameter tuning is usually done by trail-and-error in practice causing significant effort and time. An auto tuning method based on fuzzy rules is proposed in the paper in this method tracking error and chattering are monitored by performance indices and the controller tunes the design parameters intelligently in order to compromise both indices. To demonstrate the efficiency of the propose method a mass-spring translation system and a roboic control system are simulated and tested It is shown that the proposed algorithm is effective to facilitae the parameter tuning for sliding mode controllers.

• Transactions of the Korean Society of Automotive Engineers
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• v.21 no.2
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• pp.72-80
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• 2013

This study is to develop and evaluate an AFS and an ARS controllers to enhance lateral stability of a vehicle. A sliding mode control (SMC) and a fuzzy logic control (FLC) methods are applied to calculate the desired additional steering angle of AFS equipped vehicle or desired rear steer angle of ARS equipped vehicle. To validate AFS and ARS systems, an eight degree of freedom, nonlinear vehicle model and an ABS controllers are also used. Several road conditions are used to test the performances. The results showed that the yaw rate of the AFS and the ARS vehicle followed the reference yaw rate very well within the adhesion limit. However, the AFS improves the lateral stability near the limit compared with the ARS. Because the SMC and the FLC show similar vehicle responses, performance discrimination is small. On split-${\mu}$ road, the AFS and the ARS vehicle had enhanced the lateral stability.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.8
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• pp.735-743
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• 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 Korean Society for Noise and Vibration Engineering Conference
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• 2000.06a
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• pp.246-250
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• 2000

A distinctive feature in vibration control of a large civil infrastructure is the existence of large disturbances, such as wind, earthquake, and sea wave forces. Those disturbances govern the behavior of the structure, however, they cannot be precisely measured, especially for the case of wind-induced vibration control. The sliding mode fuzzy control (SMFC), which is of interest in this study, may use not only the structural response measurement but also the wind force measurement. Hence, an adaptive disturbance estimation filter is introduced to generate a wind force vector at each time instance based on the measured structural response and the stochastic information of the wind force. The structure of the filter is constructed based on an auto-regressive with auxiliary input model. A numerical simulation is carried out on a benchmark problem of a wind-excited building. The results indicate that the overall performance of the proposed SMFC is as good as the other methods and that most of the performance indices improve as the adaptive disturbance estimation filter is introduced.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.5
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• pp.640-647
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• 2007

This paper presents a joint controller for a humanoid robot based on genetic algorithm. h humanoid robot has basically instability during walking because it isn't fixed on the ground. Moreover nonlinearities of the joints increase its instability. If one of them isn't satisfied, the robot may fall down at the ground during walking. To attack one of those problems, joint controller is proposed. It can perform tracking control preciously and reduce the effect of nonlinearities by gear, limitation of the input voltage, coulomb friction and so on. This controller is based on fuzzy-sliding mode controller (FSMC) and compensator and control gains are searched by a proposed genetic algorithm. It can reduce the effect by nonlinearities. Also, to improve the tracking performance, the proposed controller has motion controller. From the given controller, a humanoid robot can moved more preciously. Here, all the processes are investigated through simulations and it is verified experimentally in a real joint system for a humanoid robot.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2000.04b
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• pp.365-370
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• 2000

A sliding mode fuzzy control (SMFC) algorithm is applied to design a controller for a benchmark problem on a wind- excited building. The structure is a 76-story concrete office tower with a height of 306 meters, hence the wind resistance characteristics are very important for the serviceability as well as the safety. A control system with an active tuned mass damper is assumed to be installed on the top floor. Since the structural acceleration is measured only at ,limited number of locations without measurement of the wind force, the structure of the conventional continuous sliding mode control may have the feed-back loop only. So, an adaptive least mean squares (LMS) filter is employed in the SMFC algorithm to generate a fictitious feed-forward loop. The adaptive LMS filter is designed based on the information of the stochastic characteristics of the wind velocity along the structure. A numerical study is carried out. and the performance of the present SMFC with the ,adaptive LMS filter is investigated in comparison with those of' other control, of algorithms such as linear quadratic Gaussian control, frequency domain optimal control, quadratic stability control, continuous sliding mode control, and H/sub ∞///sub μ/, control, which were reported by other researchers. The effectiveness of the adaptive LMS filter is also examined. The results indicate that the present algorithm is very efficient .

• Proceedings of the KIEE Conference
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• 2000.11d
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• pp.689-693
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• 2000

In this paper, we proposed a decoupled adaptive fuzzy sliding-mode control scheme in designing the SMC of a class of fourth-order nonlinear systems. These systems are decoupled the whole system into two second-order systems such that each subsystem has a separate control target expressed in terms of a sliding surface. Then, information from the secondary target conditions the main target, which, in turn, generates a control action to make both subsystem move toward their sliding surface. respectively, and 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 adaptive law, Under this design scheme, we not only maintain the distribution of membership functions over state space but also reduce considerably computing time, we apply the decoupled adaptive sliding-mode control to control a nonlinear inverted pendulum system and confirms the validity of the proposed approach.