• Journal of Advanced Marine Engineering and Technology
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• v.24 no.1
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• pp.104-111
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• 2000

It is very difficult to maintain the desired tank level without any overflow or any shortage in a dangerous shemical plant and in a cooling one. Futhermore, because its dynamics are very complicate and nonlinear, it is impossible to realize the precise control using the accurate mathematical model which can be applied to the various peration modes. Nonetheless, the sliding mode controller(SMC) is known as having the robust variable structures for the nonlinear control system with the parametric perturbations and with the rapid disturbances. But the adaptive tuning algorithms for their parameters are not satisfactory. Therefore, in this paper, a Real Variable Elitist Genetic Algorithm based Sliding Mode Controller (RVEGA SMC) for the precise control of the coupled tank level was tried. The SMC's switching parameters were optimized easily and rapidly by RVEGA. The simulation results showed that the tank level could be satisfactorily controlled without and overshoot and any steady-state error by the proposed RVEGA SMC.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.25-25
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• 2000

This paper presents a design method of sliding mode control (SMC) for single input linear systems with mismatched uncertainties. We define a virtual state based on the controllable canonical form of the nominal system. And we define a sliding surface for the augmented system with a virtual state. This sliding surface makes it possible to use SMC technique with various types of controllers. In this paper, we construct a controller that combines SMC with robust controller. We design a robust controller for the system with only mismatched uncertainties using a form of linear matrix inequality (LMI). We make a virtual state from this robust control input and the states of the nominal system. And we design a sliding mode controller that stabilizes the overall closed-loop system.

• Proceedings of the Korean Society of Marine Engineers Conference
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• 2002.05a
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• pp.239-244
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• 2002

Even though, tanks are used at the many industry plants, it is very difficult to control the tank level without any overflow and shortage; moreover, cause of its complication of dynamics and nonlinearity, it's impossible to realize the accurate control using the mathematical model which can be applied to the various operation modes. However, the sliding mode controller(SMC) is known as having the robust variable structures for the nonlinear control systems with the parametric perturbations and with the sudden disturbances, but the auto-tuning of parameters was a problem. Therefore, in this paper, a Genetic Algorithm based Sliding Mode Controller (GA-SMC) for the precise control of the coupled tank level was tried. GA optimized the SMCs switching parameters easily and rapidly. The simulation results are shown that the tank level could be satisfactorily controlled with less overshoot and steady-stale error by the proposed GA-SMC.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2672-2674
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• 2000

In this paper. feedback linearization and the sliding mode control(SMC) are used together for uncertain nonlinear system. An advantage of feedback linearization technique is to make linear control theories can be used for nonlinear system and the SMC have the robustness. But the dynamics of the SMC has the dynamics lower order than that of the original system. Therefore the linear control theory can not be used with the SMC. The novel sliding surface of the SMC can have the dynamics of the nominal non linear system controlled by the feedback linearization. The proposed method can be used for the control of induction motors.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1424-1429
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• 2003

In this paper, the design method of sliding mode control (SMC) system for SISO linear system is discussed. First, we consider the similarity between the design method of sliding mode hyper plane using the strict positive realness and the characteristics of zeros of feedback system and the design method of simple adaptive control. Based on such a consideration, we propose the new design method of SMC system using parallel dynamic compensator. As a result, SMC system can be constructed only with the derivative of output signal for controlled plant. The performance of SMC system designed by proposed method is confirmed through the numerical example.

• Journal of Power Electronics
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• v.15 no.3
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• pp.753-762
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• 2015

This paper presents a nonlinear sliding mode control (SMC) scheme with a variable damping ratio for interior permanent magnet synchronous motors (IPMSMs). First, a nonlinear sliding surface whose parameters change continuously with time is designed. Actually, the proposed SMC has the ability to reduce the settling time without an overshoot by giving a low damping ratio at the initial time and a high damping ratio as the output reaches the desired setpoint. At the same time, it enables a fast convergence in finite time and eliminates the singularity problem with the upper bound of an uncertain term, which cannot be measured in practice, by using a simple adaptation law. To improve the efficiency of a system in the constant torque region, the control system incorporates the maximum torque per ampere (MTPA) algorithm. The stability of the nonlinear sliding surface is guaranteed by Lyapunov stability theory. Moreover, a simple sliding mode observer is used to estimate the load torque and system uncertainties. The effectiveness of the proposed nonlinear SMC scheme is verified using comparative experimental results of the linear SMC scheme when the speed reference and load torque change under system uncertainties. From these experimental results, the proposed nonlinear SMC method reveals a faster transient response, smaller steady-state speed error, and less sensitivity to system uncertainties than the linear SMC method.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.10
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• pp.1327-1334
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• 1999

The stabilization control of ball-beam system is difficult because of its nonlinearity and structural unstability. Futhermore, a series of classical methods such as the PID and the full state feedback controller(FSFC) based on the local linearizations have narrow stabilizable regions. At the same time, the fine tunings of their gain parameters are also troublesome. Therefore, in this paper, three improved design techniques of stabilization controller for a ball-beam system were proposed. These parameter tuning methods in the double PID controller(DPIDC), the FSFC and the a sliding mode controller(SMC) were dependent upon the Real Value Elitist Genetic Algorithm (RVEGA). Finally, by applying the DPIDC, the FSFC and the Real Variable Elitist Genetic Algorithm based Sliding Mode Control(RVEGA SMC) to the stabilizations of a ball-beam system, the performances of the RVEGA SMC technique were showed to be superior to those of two other type controllers.

• Journal of IKEEE
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• v.23 no.2
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• pp.628-635
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• 2019

This paper proposes sliding mode control (SMC) method for improvement of dynamic response for IPMSM based on DTC with constant switching frequency. DTC with constant switching frequency method consists of PI torque controller and triangular comparator for constant torque error status. It has the poor dynamic response compared to conventional DTC. This paper proposes improvement method of dynamic response of DTC with constant switching frequency by using SMC. Simulation results confirm the effectiveness of the proposed method.

• Structural Engineering and Mechanics
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• v.26 no.4
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• pp.377-392
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• 2007

A discrete sliding mode control (SMC) method based on hybrid model of neural network and nominal model is proposed to reduce the vibration of flexible structures, which is a robust active controller developed by using a sliding manifold approach. Since the thick boundary layer will reduce the virtue of SMC, the multilayer feed-forward neural network is adopted to model the uncertainty part. The neural network is trained by Levenberg-Marquardt backpropagation. The design objective of the sliding mode surface is based on the quadratic optimal cost function. In course of running, the input signal of SMC come from the hybrid model of the nominal model and the neural network. The simulation shows that the proposed control scheme is very effective for large uncertainty systems.

• 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.