• Journal of Institute of Control, Robotics and Systems
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• v.7 no.7
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• pp.597-604
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• 2001

Recently, the study of the moving sliding mode in the variable structure control is in progress ac-tively. The conventional time-invariant sliding model control can\`t guarantee the sliding mode in the reaching phase, which is robust against the uncertainty. But with the time-varying method, the controller makes the states track the desired trajectories and keeps the sliding mode. Nevertheless, the piecewise continuous method of the past still has the reaching mode. Thus we propose the continuously moving sliding surface by the fuzzy algorithm. The proposed algorithm is made of the fuzzy rule considering both the error and the error velocity, and may apply to the entire phase plane without sacrificing sliding mode. Especially the proposed scheme can rotate tot he slope-decreasing direction, needless to say rotating to the slope-increasing direction. For showing that the proposed controller guarantees the sliding model and ensures the robustness, we apply the proposed method to the two-link robot manipulator simulation.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.227-231
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• 2004

In this paper, a robust Sliding Mode Variable Structure (SMVS) controller is designed for Active Queue Management (AQM). This type of controller is insensitive to noise and variance of the parameters, thus it is suitable to time varying network systems. Simulation results conform the robust performance of SMVS controller against the disturbance. At the same time, a complete comparison between SMVS and PI controllers is made. The conclusion is that both transient and steady state performance of SMVS controller is better than that of PI one.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.249-252
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• 1996

The inverted pendulum system is mechanical system which can handle the modern control theory and practical applications. In theoretical field, it is used as the experimental device identifying the effects of control method and in applicative field. There are difficulties in designing or linearizing the practical controller because it is so sensitive to the parameter variation and has the highly non-linear characteristic. In this paper, we suggested the systems which compensate the non-linearity throughout the internal control method and designed controller which is robust to the parameter variation using sliding mode.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.225-225
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• 2000

We propose the hybrid robust controller for TDC(Time Delay Control) and SMC(Sliding Mode Control) method. TDC and SMC deal with the time-varying system parameters, unknown dynamics and unexpected disturbance. This controller is applied to follow the desired reference model for the uncertain time-varying overhead crane. The control performance is evaluated through simulation. The theoretical results indicate That the proposed controller shows excellent performance to an overhead crane with the uncertain time-varying parameters and disturbance.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.8
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• pp.1874-1882
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• 2015

In this paper, robust backstepping controller for IPMSM is proposed based on the PID integral sliding mode control. Because of the unmatching condition of load, the sliding mode control is difficult to be used for IPMSM without backstepping. However, the backstepping control has the difficulty of deriving error dynamics which is derived by differentiating the previous input. This difficulty is avoided by adopting PID as a nominal controller for the integral sliding mode control. The proposed controller can be achieved easily by adding integral sliding controller to the conventional PID controller.

• Journal of Power Electronics
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• v.12 no.5
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• pp.769-777
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• 2012

In this paper, a new development in the time optimal control theory in sliding mode control systems for multi-quadrant buck converters with a variable load is presented. In general, the closed-loop time optimal control system is applied to multi-quadrant buck converters for output regulation, so that an optimal switching surface is obtained. Moreover, an adjusted optimal sliding mode controller is suggested which adjusts the controller parameters to give an optimal switching surface. In addition, a description of the transient response of the closed-loop system is proposed and used to damp any output or input disturbances in minimum time. Numerical simulations and experimental results are employed to demonstrate that the output regulation time and transient performances of dc/dc converters using the proposed technique are improved effectively when compared to the classical sliding mode control method.

• Transactions of the Korean Society of Automotive Engineers
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• v.8 no.2
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• pp.92-101
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• 2000

The objective of this paper is to design the controller for longitudinal vehicle following which makes the vehicle follow the lead vehicle and keeps a safety distance without human driver operation. This paper presents a sliding mode control algorithm for the ACC system. The controller is based on three sliding surfaces. Each surface plays an individual control-deviation control, throttle control and brake control. In addition to sliding mode control, we propose some additional schemes to enhance controller performance. The first one is a gear shift-down controller which makes tractive force increase with a change of gear ratio. The other is a predictive correction method which reduces slinky effect.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.999-1004
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• 2005

An algorithm for a hybrid controller consists of a sliding mode control part and a fuzzy logic part which ar purposely for nonlinear systems. The sliding mode part of the solution is based on "eigenvalue/vector"-type controller is used as the backstepping approach for tracking errors. The fuzzy logic part is a Mamdani fuzzy model. This is designed by applying sliding mode control (SMC) method to the dynamic model. The main objective is to keep the update dynamics in a stable region by used SMC. After that the plant behavior is presented to train procedure of adaptive neuro-fuzzy inference systems (ANFIS). ANFIS architecture is determined and the relevant formulation for the approach is given. Using the error (e) and rate of error (de), occur due to the difference between the desired output value (yd) and the actual output value (y) of the system. A dynamic adaptation law is proposed and proved the particularly chosen form of the adaptation strategy. Subsequently VSC creates a sliding mode in the plant behavior while the parameters of the controller are also in a sliding mode (stable trainer). This study considers the ANFIS structure with first order Sugeno model containing nine rules. Bell shaped membership functions with product inference rule are used at the fuzzification level. Finally the Mamdani fuzzy logic which is depends on adaptive neuro-fuzzy inference systems structure designed. At the transferable stage from ANFIS to Mamdani fuzzy model is adjusted for the membership function of the input value (e, de) and the actual output value (y) of the system could be changed to trapezoidal and triangular functions through tuning the parameters of the membership functions and rules base. These help adjust the contributions of both fuzzy control and variable structure control to the entire control value. The application example, control of a mass-damper system is considered. The simulation has been done using MATLAB. Three cases of the controller will be considered: for backstepping sliding-mode controller, for hybrid controller, and for adaptive backstepping sliding-mode controller. A numerical example is simulated to verify the performances of the proposed control strategy, and the simulation results show that the controller designed is more effective than the adaptive backstepping sliding mode controller.

• Journal of Ocean Engineering and Technology
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• v.23 no.2
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• pp.1-7
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• 2009

This paper presents a sliding mode controller based on Ackermann's formula and applies it to stabilizing a two-wheeled mobile inverted pendulum in equilibrium. The mobile inverted pendulum is a system with an inverted pendulum on a mobile cart. The dynamic modeling of the mobile inverted pendulum was established under the assumptions of a cart with no slip and a pendulum with only planar motion. The proposed sliding mode controller was based upon a class of nonlinear systems whose nonlinear part of the modeling can be linearly parameterized. The sliding surface was obtained in an explicit form using Ackermann's formula, and then a control law was designed from reachability conditions and made the sliding surface attractive to the equilibrium state of the mobile inverted pendulum. The proposed controller was implemented in a Microchip PIC16F877 micro-controller. The developed overall control system is described. The simulation and experimental results are presented to show the effectiveness of the modeling and controller.

• Journal of Power Electronics
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• v.10 no.5
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• pp.505-517
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• 2010

In this paper, an intelligent sliding-mode speed controller for achieving favorable decoupling control and high precision speed tracking performance of permanent-magnet synchronous motor (PMSM) drives is proposed. The intelligent controller consists of a sliding-mode controller (SMC) in the speed feed-back loop in addition to an on-line trained wavelet-neural-network controller (WNNC) connected in parallel with the SMC to construct a robust wavelet-neural-network controller (RWNNC). The RWNNC combines the merits of a SMC with the robust characteristics and a WNNC, which combines artificial neural networks for their online learning ability and wavelet decomposition for its identification ability. Theoretical analyses of both SMC and WNNC speed controllers are developed. The WNN is utilized to predict the uncertain system dynamics to relax the requirement of uncertainty bound in the design of a SMC. A computer simulation is developed to demonstrate the effectiveness of the proposed intelligent sliding mode speed controller. An experimental system is established to verify the effectiveness of the proposed control system. All of the control algorithms are implemented on a TMS320C31 DSP-based control computer. The simulated and experimental results confirm that the proposed RWNNC grants robust performance and precise response regardless of load disturbances and PMSM parameter uncertainties.