• Journal of Institute of Control, Robotics and Systems
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• v.10 no.4
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• pp.304-311
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• 2004

In this paper we present a technique of discrete-time sliding mode controller design for assigning eigenvalues of sliding mode and determining a convergence rate to sliding surface. First the sliding mode coefficient is designed via Ackermann s formula. Then a linear controller is designed to enforce sliding mode such that the resulting closed loop yields the desired eigenvalues. As we use a linear control instead of nonlinear control, chattering is nearly eliminated. Simulation and experimental results are included to show the effectiveness of the proposed method for Laser Marking System.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2290-2292
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• 2000

Robustness characteristics to the modelling imprecision and some disturbances could be achieved in sliding mode control. However, there are drawbacks such as discontinuous control and chattering. Recently, many researches have been developing to solve such the problems. In sliding mode control, overall control input could be divided into two parts which are equivalent control input and sliding mode control input. Sliding mode control input is a function of the switching surfaces and can be designed with their linear combinations. In this paper, the sliding mode control input is designed by TSK fuzzy model. The proposed method gives the continuous sliding control input and reject the chattering phenomenon.

• Smart Structures and Systems
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• v.11 no.3
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• pp.315-329
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• 2013

The construction of an experimental nonlinear structural model with little cost and unlimited repeatability for vibration control study represents a challenging task, especially for material nonlinearity. This paper reports the design, analysis and vibration control of a nonlinear structural experiment platform with adjustable hinges. In our approach, magnetorheological rotary brakes are substituted for the joints of a frame structure to simulate the nonlinear material behaviors of plastic hinges. For vibration control, a separate magnetorheological damper was employed to provide semi-active damping force to the nonlinear structure. A dynamic neural network was designed as a state observer to enable the feedback based semi-active vibration control. Based on the dynamic neural network observer, an adaptive fuzzy sliding mode based output control was developed for the magnetorheological damper to suppress the vibrations of the structure. The performance of the intelligent control algorithm was studied by subjecting the structure to shake table experiments. Experimental results show that the magnetorheological rotary brake can simulate the nonlinearity of the structural model with good repeatability. Moreover, different nonlinear behaviors can be achieved by controlling the input voltage of magnetorheological rotary damper. Different levels of nonlinearity in the vibration response of the structure can be achieved with the above adaptive fuzzy sliding mode control algorithm using a dynamic neural network observer.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1414-1417
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• 2003

In this paper, sliding mode controller for discrete-time nonlinear systems with uncertainties and disturbances are proposed. The concept of time-delay control (TDC) which consists of estimating the uncertain dynamics of the system through past observations of the system response is used. The proposed controller guarantees that the closed-loop system states are globally uniformly ultimately bounded (GUUB). It is also shown that the closed-loop system states are globally uniformly asymptotically stable (GUAS) if uncertainties are constant.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1492-1495
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• 1996

In this paper, an approach to autopilot design based on the robust nonlinear dynamic inversion method is proposed. Both unknown parameters and uncertainty bounds are estimated and parameter estimates are used in the fast inversion. Furthermore, to get more robustness slow inversion is incorporated with MRAC(Model Reference Adaptive Control) and sliding mode control where the estimates of uncertainty bounds are used. The proposed method is applied to the pitch autopilot design of a missile system and excellent performance is shown via computer simulation.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.284-284
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• 2000

In adaptive fuzzy control systems. fuzzy systems are used to approximate the unknown plant nonlinearities. Until now. most of the papers in the field of controller design for nonlinear system using fuzzy systems considers the affine system with fixed grid-rule structure based on system state availability. This paper considers observer-based nonlinear controller and dynamic fuzzy rule structure. Adaptive laws for fuzzy parameters for state observer and fuzzy rule structure are established so that the whole system is stable in the sense of Lyapunov.

• Proceedings of the KIEE Conference
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• 1998.07c
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• pp.967-969
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• 1998

In this paper, the proposed controller is obtained by combining the nonlinear feedback linearization-sliding mode controller (NFL-SMC) with the full order observer (FOO) and eliminates the need to measure all the state variables in the conventional NFL-SMC.

• Proceedings of the KIEE Conference
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• 2004.07d
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• pp.2236-2238
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• 2004

This paper proposes the self-recurrent wavelet neural network (SRWNN) observer based sliding mode control (SMC) method for nonlinear systems. Unlike the classical SMC, we assume that all states of nonlinear systems are not measured and design the SRWNN observer to measure the states of nonlinear systems. The SRWNN in the observer is used for approximating the observer system's gain. To generate the control input for controlling the nonlinear system, the measured states are used. The sliding surface with a boundary layer is defined to remove the chattering of the control input. Simulation result to show the effectiveness of the SRWNN observer is presented.

• Proceedings of the KIEE Conference
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• 1998.11b
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• pp.526-529
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• 1998

In this paper, we proposed a nonlinear sliding mode controller to regulate the swinging angle of Overhead Crane System. Roughly speaking, the controller is designed to regulate an output(the swing angle) while providing internal stability. It is difficult to apply many of standard nonlinear control design techniques. In contrast to control that use a command generator and possibly a time-varying feedback, our control law is simple autonomous nonlinear controller. We analyze the stability of the closed-loop system using an $L_2$ Sliding surface conditions approach on a nonlinear feedback linearization of the system about the desired periodic orbit. One can easily extend this approach to analyze the robustness of the control system with respect to disturbances and parameter variations.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.8
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• pp.467-472
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• 2000

A three-level decoupled sliding mode controller is developed to achieve asymptotic stability for a class of sixth-order nonlinear systems. The sixth-order system is decoupled into three subsystems according to the structure of the whole system. Each subsystem has a separate control target in the form of a sliding surface. The information of the third sliding surface is transferred to the second one through an intermediate variable and the information of the second sliding surface is transferred to the first one through another intermediate variable. Consequently, the controller designed on the basis of the first sliding surface can make three subsystems move toward their sliding surfaces, respectively. The three-level decoupled sliding mode controller is applied to the double-inverted pendulum problem where the zero stable states are required.