• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.11
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• pp.1620-1627
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• 2017

In this paper, we design an observer-based $H_{\infty}$ fuzzy controller for interval type-2 Takagi-Sugeno (T-S) fuzzy systems under imperfect premise matching. The designed observer-based controller can effectively estimate the state of the system and make fuzzy system satisfy the $H_{\infty}$ disturbance attenuation performance. Using the slack matrix, the derived stabilization condition is expressed in terms of a linear matrix inequality. Finally, the effectiveness of the proposed method is verified through a simulation example.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.1732-1733
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• 2011

This paper presents observer-based controller design for interval type-2 fuzzy system with staircase membership approximation. In type-2 fuzzy case, membership function is itself fuzzy set itself. Thus, type-2 fuzzy system can deal with parametric uncertainties of nonlinear system by capturing the uncertainties in membership function. Likewise, stabilization condition of type-2 fuzzy system is derived from quadratic Lyapunov function, and it goes to linear matrix inequality. Furthermore, in this paper, to relax the conservativeness of stabilization condition, staircase membership function approximating method is applied. Observer-based control method is adopted to control system which has some unmeasurable states. To prove suitability of our proposed method, numerical example is presented.

• Journal of Power Electronics
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• v.15 no.3
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• pp.730-740
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• 2015

This paper presents model reference adaptive system speed estimators based on Type-1 and Type-2 fuzzy logic controllers for the speed sensorless direct torque and flux control of an induction motor drive (IMD) using space vector pulse width modulation. A Type-1 fuzzy logic controller (T1FLC) based adaptation mechanism scheme is initially presented to achieve high performance sensorless drive in both transient as well as in steady-state conditions. However, the Type-1 fuzzy sets are certain and cannot work effectively when a higher degree of uncertainties occurs in the system, which can be caused by sudden changes in speed or different load disturbances and, process noise. Therefore, a new Type-2 FLC (T2FLC) - based adaptation mechanism scheme is proposed to better handle the higher degree of uncertainties, improve the performance, and is also robust to different load torque and sudden changes in speed conditions. The detailed performance of different adaptation mechanism schemes are performed in a MATLAB/Simulink environment with a speed sensor and sensorless modes of operation when an IMD is operates under different operating conditions, such as no-load, load, and sudden changes in speed. To validate the different control approaches, the system is also implemented on a real-time system, and adequate results are reported for its validation.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.7
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• pp.622-631
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• 2001

This paper presents a fuzzy modified PID controller that uses linear fuzzy inference method. In this structure, the proportional and derivative gains vary with the output of the system under control. 2-input PD type fuzzy controller is designed to obtain the varying gains. The proposed fuzzy PID structure maintains the same performance as the same performance as the general-purpose linear PID controller, and enhances the tracking performance over a wide range of input. Numerical simulations and experimental results show the effectiveness of the fuzzy PID controller in comparison with the conventional PID controller.

• Journal of the Institute of Convergence Signal Processing
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• v.6 no.2
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• pp.89-94
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• 2005

In this paper, we propose a fuzzy PID controller of new method. There are two problems in absolute digital PID controller. First, much calculation time need for obtain the sum of data at each period. Second, this is problem need much memory because to storage every data at the before period. We use the speed type PID digital controller to improvement such problems. In the propose controller doesn't use without adjustment the crisp output error and we doesn't use nile tables in the fuzzy inference process at the forward stage fuzzifier. We inference output member ship function by using the relation and range of two variable of PID gain parameters. We can obtained desired results through the simulation and a experiment of the hydraulic servo motor control system.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.2
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• pp.302-312
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• 1994

In this study, a fuzzy theory is introduced to control the cross-sectional strip shape in cold rolling. A fuzzy controller is developed based on the production data and the operational knowledge. The cold rolled products are characterized into several types based on their irregularities. For each type of irregular strip shape, fuzzy controller calculates the changes of bender forces of work and intermediate rolls using fuzzy control algorithm. To simulate the continuous shape control, fuzzy controller is linked with emulator which is developed using neural network. The developed fuzzy controller and emulator simulate the cold rolling process until the irregularities converge to the tolerable range to produce unifrom cross-sectional strip shape. The results from this simulation are reasonable for various irregular strip shapes.

• Journal of Power System Engineering
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• v.2 no.2
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• pp.47-54
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• 1998

Underwater robotic vehicles(URVs) have been an important tool for various underwater tasks such as pipe-lining, data collection, hydrography mapping, construction, maintenance and repairing of undersea equipment, etc because they have greater speed, endurance, depth capability, and safety than human divers. As the use of such vehicles increases, the vehicle control system is one of the most critical subsystems to increase autonomy of the vehicle. The vehicle dynamics are nonlinear and their hydrodynamic coefficients are often difficult to estimate accurately. It is desirable to have an intelligent vehicle control system because the fixed-parameter linear controller such as PID may not be able to handle these changes promptly and result in poor performance. In this paper we described and analyzed a new type of fuzzy model-based controller which is designed for underwater robotic vehicles and based on Takagi-Sugeno-Kang(TSK) fuzzy model. The proposed fuzzy controller: 1) is a nonlinear controller, but a linear state feedback controller in the consequent of each local fuzzy control rule; 2) can guarantee the stability of the closed-loop fuzzy system; 3) is relatively easy to implement. Its good performance as well as its robustness to parameter changes will be shown and compared with those of the PID controller by simulation.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.3 no.2
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• pp.166-172
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• 2003

The dynamics of the DDWMR depends on the velocity difference of the two driving wheels. And which is known as a type of non-holonomic equation. By this reason, the treatment of DDWMR had become difficult and conservative. In this paper, the differential-driving wheeled mobile robot is considered. The Takaki-Surgeno fuzzy model and a control method for DDWMR is presented. The suggested controller has three control elements. The first element is fuzzy state feedback designed for eliminating the dependence of time-varying parameter. The second element is weighting controller which is designed for good frequency response. The third controller is PI-controller which is designed for good command following and robustness with un-modeled dynamics. In order for achieving the performance objective, the design of controller is based on the loop-shaping algorithm.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.1
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• pp.35-42
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• 1998

This paper presents the introduction of Pseudo-2 axes robot module and its GA-based fuzzy control implementation. Pseudo-2 axes robot module which use a single motor and controller for driving 2 joints of a robot mechanism, is devised towards a lower priced robot with its degree of freedom maintained GA-based Fuzzy controller is considered for the better control implementation of the developed system than the conventional PID controller. Here. the scaling factors of the membership function with high fitness values are selected using a genetic algorithm for a pulse-type input trajectory. The obtained controller also shows better trajectory tracking performance than a PID controller.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.479-483
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• 1992

This paper defines the relationship between PI type fuzzy control system and conventional PI control system, and discusses the relationship of parameters and control action in fuzzy controller. The tuning algorithm that updates ouput variable scaling factor of fuzzy controller is proposed .The proposed sheme is applied to the simulations of 2 selected dynamical plants. The simulation results show that the controller is effective in controlling dynamical plants.