• International Journal of Control, Automation, and Systems
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• v.4 no.2
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• pp.146-154
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• 2006

In this paper, we propose direct and indirect adaptive fuzzy sliding mode control approaches for a class of nonaffine nonlinear systems. In the direct case, we use the implicit function theory to prove the existence of an ideal implicit feedback linearization controller, and hence approximate it to attain the desired performances. In the indirect case, we exploit the linear structure of a Takagi-Sugeno fuzzy system with constant conclusion to establish an affine-in-control model, and therefore design an indirect adaptive fuzzy controller. In both cases, the adaptation laws of the adjustable parameters are deduced from the stability analysis, in the sense of Lyapunov, to get a more accurate approximation level. In addition to their robustness, the design of the proposed approaches does not require the upper bounds of both external disturbances and approximation errors. To show the efficiency of the proposed controllers, a simulation example is presented.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.55 no.4
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• pp.158-160
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• 2006

In this paper, a neuro-fuzzy observer system is designed using neuro-fuzzy system for speed control of AC servo motor. This neuro-fuzzy observer is proposed to with the problems occur in the Luenberger observer and sliding observer. The problems of Luenberger and sliding observer are to have to know the dynamics and internal parameters of the system. Performance of the neuro-fuzzy observer system has verified through the experiment with dynamometer load. It is shown that feasibility of the neuro-fuzzy observer is verified.

• 제어로봇시스템학회:학술대회논문집
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• 1999.10a
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• pp.173-176
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• 1999

This paper shows a self tuning fuzzy inference method by the genetic algorithm in the fuzzy-sliding mode control for a Polishing robot. Using this method, the number of inference rules and the shape of membership functions are determined by the genetic algorithm. The fuzzy outputs of the consequent part are derived by the gradient descent method. Also, it is guaranteed that .the selected solution become the global optimal solution by optimizing the Akaike's information criterion expressing the quality of the inference rules. It is shown by simulations that the method of fuzzy inference by the genetic algorithm provides better learning capability than the trial and error method.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2000.10a
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• pp.79-83
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• 2000

A sliding mode fuzzy control (SMFC) with disturbance estimator is applied to design a controller for the third generation benchmark problem on an wind-excited building. A distinctive feature in vibration control of 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. Since the structural accelerations are measured only at a limited number of locations without the measurement of the wind forces, the structure of the conventional control may have the feed-back loop only. General structure of the SMFC is composed of a compensation part and a convergent part. The compensation part prevents the system diverge, and the convergent part makes the system converge to the sliding surface. The compensation part uses not only the structural response measurement but also the disturbance measurement, so the SMFC has a feed-back loop and a feed-forward loop. To realize the virtual feed-forward loop for the wind-induced vibration control, disturbance estimation filter is introduced. the structure of the filter is constructed based on an auto regressive model for the stochastic wind force. This filter estimates the wind force at each time instance based on the measured structural responses and the stochastic information of the wind force. For the verification of the proposed algorithm, a numerical simulation is carried out on the benchmark problem of a wind-excited building. The results indicate that the present control algorithm is very efficient for reducing the wind-induced vibration and that the performance indices improve as the filter for wind force estimation is employed.

• Journal of the Korean Institute of Intelligent Systems
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• v.8 no.5
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• pp.21-28
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• 1998

This study develops 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. By appling TS fuzzy algorithm to the regulation of the rionlinear 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.

• Journal of Power Electronics
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• v.7 no.2
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• pp.159-173
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• 2007

In this paper, an intelligent sliding-mode position controller (ISMC) for achieving favorable decoupling control and high precision position tracking performance of permanent-magnet synchronous motor (PMSM) servo drives is proposed. The intelligent position controller consists of a sliding-mode position controller (SMC) in the position feed-back loop in addition to an on-line trained fuzzy-neural-network model-following controller (FNNMFC) in the feedforward loop. The intelligent position controller combines the merits of the SMC with robust characteristics and the FNNMFC with on-line learning ability for periodic command tracking of a PMSM servo drive. The theoretical analyses of the sliding-mode position controller are described with a second order switching surface (PID) which is insensitive to parameter uncertainties and external load disturbances. To realize high dynamic performance in disturbance rejection and tracking characteristics, an on-line trained FNNMFC is proposed. The connective weights and membership functions of the FNNMFC are trained on-line according to the model-following error between the outputs of the reference model and the PMSM servo drive system. The FNNMFC generates an adaptive control signal which is added to the SMC output to attain robust model-following characteristics under different operating conditions regardless of parameter uncertainties and load disturbances. A computer simulation is developed to demonstrate the effectiveness of the proposed intelligent sliding mode position controller. The results confirm that the proposed ISMC grants robust performance and precise response to the reference model regardless of load disturbances and PMSM parameter uncertainties.

• Journal of the Korean Institute of Intelligent Systems
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• v.6 no.2
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• pp.3-12
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• 1996

Sliding mode controller(SMC) is a simple but powerful nonlinear controller, because it guarantees the stability and the robustness. However, it leads to the high frequency chattering of the control input. Although the phenomenon can be avoided by introducing a thin boundary layer to the sliding surface, the method results in a steady state: error proportional to the boundary layer thickness. In this paper, we proposed a new sliding mode controller with self-tuning the thickness of a boundary layer. It uses a fuzzy rule base for tuning the thickness of a boundary layer. That is, the thickness is increased to some degree to reject a discontinuous control input at the initial state and then it is decreased as the states approaches to the steady states for improving the tracking performance. In order to assure the control performance, we perf'ormed the computer simulation using an inverted pendulum system as a controlled plant.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.10
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• pp.17-24
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• 1999

본 논문에서는 새로운 적응 퍼지 슬라이딩 모드제어 방법을 제시하였다. 제어기는 정확한 수확적인 모델이 없이도 점근적으로 시스템을 안정화시킬 수 있으며 적분항을 포함시킴으로서 정상상태에서의 오차를 좀 더 줄일 수가 있다. 직접구동모터는 감쇄기어가 없어서 부하나 외란 토크의 변화에도 모터 역학에 직접적으로 많은 영향을 줄 수가 있다. 제어기의 실제성능을 확인하기 위하여 불확실한 부하나 변소를 갖는 직접구동모터의 위치제어에 적용하였다.

• Proceedings of the KIEE Conference
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• 2002.07d
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• pp.2143-2145
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• 2002

This paper proposes the control problem of an inverted pendulum system based on adaptive fuzzy sliding mode. The universal approximating capability, learning ability, adaptation capability and disturbance rejection are collected in one control strategy. The proposed scheme does not require an accurate dynamic model and the joint acceleration measurement, yet it guarantees asymptotic trajectory tracking. Experimental results perform with an inverted pendulum to show the effectiveness of the approach.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.2 no.2
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• pp.146-152
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• 2002

Mold level control has been a major control task for continuous casting plants. The system involves nonlinearities such as stick-slip friction in the sliding gate, time-delay, friction force variations between molten steel and the inner wall of mold, and nozzle logging/unclogging. These complex problems should be solved to control mold level for steel cast. In this paper, we propose a neural fuzzy mold level control technique for solving these complex problems and give experiment studies to show the mold level control in continuous casting process.