• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.7
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• pp.615-620
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• 2001

This paper addresses the design of sliding model fuzzy-model-based controller using genetic algorithms. In general, the construction of fuzzy logic controllers has difficulties for the lack of systematic design procedure. To release this difficulties, the sliding model fuzzy-model-based controllers was presented by authors. In this 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. Although, the stability and the performance is guaranteed by the proposed method, some design parameters have to be chosen by the designer manually. This problem can be solved by using genetic algorithms. The proposed method tunes the parameters of the controller, by which the reasonable accuracy and the control effort is achieved. The validity and the efficiency of the proposed method are verified through simulations.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.6
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• pp.752-758
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• 2004

In this paper, we proposed an adaptivefuzzy sliding control algorithm using gradient descent method to reduce chattering phenomenon which is viewed in variable control system. In design of FLC, fuzzy control rules are obtained from expert's experience and intuition and it is very difficult to obtain them. We proposed an adaptive algorithm which is updated by consequence part parameter of control rules in order to reduce chattering phenomenon and simultaneously to satistfy the sliding mode condition. The proposed algorithm has the characteristics which are viewed in conventional VSC, e.g. insensitivity to a class of disturbance, parameter variations and uncertainties in the sliding mode. To demonstrate its performance, the proposed control algorithm is applied to an inverted pendulum system. The results show that both alleviation of chattering and performance are achieved.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.8
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• pp.639-648
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• 2002

The stewart platform manipulator is a manipulator that has the closed-loop structure with an upper plate end-effector and a base frame. The stewart platform manipulator has the merit of high working accuracy and high stiffness compared with a serial manipulator. However, this is a complex structure, so controllability of the system is not so good. In this paper, we introduce a new robust motion control algorithm using partial state feedback for a class of nonlinear systems in the presence of modelling uncertainties and external disturbances. The major contribution of this work introduces the development and design of robust observer for the state and the perturbation, which is integrated into a variable structure controller(VSC) structure. The combination of controller/observer improves the control performance, because of the robust routine called sliding mode control with sliding perturbation observer(SMCSPO). Simulation and experiment are performed to apply to the manipulator. And their results show a high accuracy and a good performance.

• Journal of Mechanical Science and Technology
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• v.15 no.5
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• pp.580-591
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• 2001

This paper proposes a fuzzy-sliding mode control which is designed by a self tuning fuzzy inference method based on a genetic algorithm. Using the method, the number of inference rules and the shape of the membership functions of the proposed fuzzy-sliding mode control are optimized without the aid of an expert in robotics. The fuzzy outputs of the consequent part are updated by the gradient descent method. It is further guaranteed that the selected solution becomes the global optimal solution by optimizing Akaikes information criterion expressing the quality of the inference rules. In order to evaluate the learning performance of the proposed fuzzy-sliding mode control based on a genetic algorithm, a trajectory tracking simulation of the polishing robot is carried out. Simulation results show that the optimal fuzzy inference rules are automatically selected by the genetic algorithm and the trajectory control result is similar to the result of the fuzzy-sliding mode control which is selected through trial error by an expert. Therefore, a designer who does not have expert knowledge of robot systems can design the fuzzy-sliding mode controller using the proposed self tuning fuzzy inference method based on the genetic algorithm.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.822-825
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• 1993

A fuzzy logic controller derived from the variable structure control (VSC) theory is designed. Unlike the conventional design of the fuzzy controller, we do not fuzzify the error and the rate of error, but fuzzify the sliding surface. After the fuzzy sliding surface is introduced, the fuzzy rules are defined based on the sliding control theory. It will be shown this sliding mode fuzzy controller is a kind of VSC that introduces the boundary layer in the switching surface and that the control input is continuously approximated in the layer. As a result we can guarantee the stability and the robustness by the help of VSC, which were difficult to insure in the past fuzzy controllers. Simulation results for the inverted pendulum will show the validity.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.26 no.2
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• pp.357-364
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• 2002

A new chattering free sliding made control is proposed for robot manipulators. The control input is derived from the reaching law and the Lyapunov stability criteria, which is only composed of continuous terms. It has a chattering free characteristics and a concise farm. In implementing procedures, no change of equations is needed. Thus, it does not degrade the original merits of the sliding mode control. And it is applied to a 2-link SCARA robot manipulator. It is shown that the proposed control has good trajectory tracking performance compared with the PD control and the conventional sliding mode control which uses the boundary layer concept.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.10a
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• pp.150-155
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• 1998

Sliding mode control is a powerful control methodology for the control of uncertain systems. However, it and its variations have some disadvantages such as chattering and imprecise tracing performance. A novel scheme of the sliding mode control is presented for the accurate tracking control of the uncertain systems. The fuzzy logic-baced control law maintaining stability and consistent performance in the face of modeling imprecise is derived and simulation results showing its effectiveness are presented.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.1
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• pp.112-117
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• 2004

This paper suggests the design and analysis of the fuzzy sliding mode control for a nonlinear system using Takagi-Sugeno(T-S) fuzzy model. In this control scheme, identifying procedure that the input gain matrices in a T-S fuzzy model are manipulated into the same one is needed. The input disturbances generated in the identifying procedure are resolved by incorporating the disturbance treatment method of the conventional sliding mode control. The proposed control strategy can also treat the input disturbances that can not be linearized in the linearization procedure of T-S fuzzy modeling. Design example for the nonlinear system, an inverted pendulum on a cart, demonstrates the utility and validity of the proposed control scheme.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.8
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• pp.38-46
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• 2002

A new semi-continuous sliding mode control is proposed for electromagnetic suspension systems. The control input is derived from the reaching law and the Lyapunov stability criteria, which is composed of continuous terms and low switching term. It has a low switching gain and chattering fee characteristics. It is shown by the computer simulation that the proposed control has good tracking performance and robustness compared with the classical sliding mode control.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.12 no.1
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• pp.47-52
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• 2012

This paper focuses on discrete-time sliding mode control with SIIM fuzzy adaptive switching gain. The adaptive switching gain is calculated using the simplified indirect inference fuzzy logic. Two fuzzy inputs are the normal distance from the present state trajectory to the switching function and the distance from the present state trajectory to the equilibrium state. The fuzzy output $f_{out}$(k) out f k is used to adjust the speed the adaptation law depending on the location of the state trajectory. The simulation results showed that the proposed method had no chattering in case of uncertain parameter without disturbance. Moreover the convergent rate of the switching gain was faster and more stable even in case of disturbance.