• Journal of Advanced Marine Engineering and Technology
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• v.30 no.2
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• pp.239-246
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• 2006

This paper describes the scheme of sliding mode control (SMC) to adopt the conventional slip frequency vector drives. The purpose of sliding mode control is to achieve an accurate, robustness of response for ac servomotor speed control. A sliding mode control design method is proposed for a speed control of an induction servomotor. The control law is composed of the variable structure component and the suppressed coefficients to suppress load disturbance and variation of external parameters. The proposed control scheme is simulated by the computer which is installed in an ideal ac servomotor. The simulation results show that the proposed design method has robustness and accuracy in the speed response by adjusting the suppressed coefficients for load disturbance and the motor mechanical parameter variation.

• Journal of Mechanical Science and Technology
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• v.15 no.9
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• pp.1240-1247
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• 2001

A robust control design scheme using well-developed SISO techniques is proposed for maglev vehicles that are inherently unstable MIMO systems. The proposed separate control method has basically two control loops: a stabilizing loop by a pole-placement technique, and a performance loop using a novel optimal LQ loop-shaping technique. This paper shows that the coupling terms involved in maglev vehicles with multimagnets should not be neglected but compensated for their stability and performance robustness. The robustness properties of the proposed control system are then evaluated under variations of vehicle masses and air gaps through a computer simulation. This paper also describes the reason why the proposed control technique can be suggested as a tool using only SISO techniques in controlling unstable MIMO systems such as maglev vehicles.

• International Journal of Control, Automation, and Systems
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• v.3 no.spc2
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• pp.288-295
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• 2005

In this paper a new adaptive, decentralized excitation control scheme proposed to enhance the transient stability of multimachine power systems is extensively analyzed with respect to its robustness and disturbance attenuation. As shown in the paper, both robustness and disturbance attenuation can be effectively improved by suitably selecting the design parameters of the proposed controller. Particularly, some simple rules for the selection of the control gains and the adaptation parameters are extracted which, as it is proven, may be essential for the system performance. Simulation tests on a two generator infinite bus power system absolutely confirm the theoretical results.

• KIEE International Transaction on Systems and Control
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• v.12D no.1
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• pp.43-50
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• 2002

In the recent years neural networks have fulfilled the promise of providing model-free learning controllers for nonlinear systems; however, it is very difficult to guarantee the stability and robustness of neural network control systems. This paper proposes an adaptive neural network control for robot manipulators based on the radial basis function netwo.k (RBFN). The RBFN is a branch of the neural networks and is mathematically tractable. So we adopt the RBFN to approximate nonlinear robot dynamics. The RBFN generates control input signals based on the Lyapunov stability that is often used in the conventional control schemes. The saturation function is also chosen as an auxiliary controller to guarantee the stability and robustness of the control system under the external disturbances and modeling uncertainties.

• The Pure and Applied Mathematics
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• v.30 no.2
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• pp.191-201
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• 2023

In this paper the control system described by Urysohn type integral equation is studied. It is assumed that control functions are integrally constrained. The trajectory of the system is defined as multivariable continuous function which satisfies the system's equation everywhere. It is shown that the set of trajectories is Lipschitz continuous with respect to the parameter which characterizes the bound of the control resource. An upper estimation for the diameter of the set of trajectories is obtained. The robustness of the trajectories with respect to the fast consumption of the remaining control resource is discussed. It is proved that every trajectory can be approximated by the trajectory obtained by full consumption of the control resource.

• Structural Engineering and Mechanics
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• v.21 no.2
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• pp.185-204
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• 2005

Variations in system parameters due to uncertainties may result in system performance deterioration. Uncertainties in modeling of structures are often considered to ensure that control system is robust with respect to response errors. Hence, the uncertain concept plays an important role in vibration control of the engineering structures. The paper discusses the robustness of the stability of vibration control systems with uncertain parameters. The vibration control problem of an uncertain system is approximated by a deterministic one. The uncertain parameters are described by interval variables. The uncertain state matrix is constructed directly using system physical parameters and avoided to use bounds in Euclidean norm. The feedback gain matrix is determined based on the deterministic systems, and then it is applied to the actual uncertain systems. A method to calculate the upper and lower bounds of eigenvalues of the close-loop system with uncertain parameters is presented. The lower bounds of eigenvalues can be used to estimate the robustness of the stability the controlled system with uncertain parameters. Two numerical examples are given to illustrate the applications of the present approach.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.303-306
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• 1996

We propose a robust tuning method of the quadratic criterion based iterative learning control(Q-ILC) algorithm for discrete-time linear batch system. First, we establish the frequency domain representation for batch systems. Next, a robust convergence condition is derived in the frequency domain. Based on this condition, we propose to optimize the weighting matrices such that the upper bound of the robustness measure is minimized. Through numerical simulation, it is shown that the designed learning filter restores robustness under significant model uncertainty.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.474-477
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• 1995

In this paper, the nonlinear model of axial electro-magnetic suspension(EMS) system is presented. The characteristic of attracyion force is analyzed by FEM. Some simulation is given to compare the sliding mode control based on the input-output linearization with the classical linear control using Taylor approximation. Real result of regulating control, transient response comparison, and robustness control with disturbance using the sliding mode method is presented.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.420-420
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• 2000

In this paper, we propose an adaptive controller using RBFN(radial basis function network) for robot manipulators The structure of the proposed controller consists of a RBFN and VSC-1 ike control. RBFN is used in order to approximate かon system, and VSC-like control to guarantee robustness On the basis of the Lyapunov stability theorem, we guarantee the stability for the total system. And the learning law of RBFN is established by the Lyapunov method, Finally, we apply the proposed controller to tracking control for a 2 link SCARA type robot manipulator.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.446-450
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• 1991

PID controller is popular but have defect inversing following reference input and noise elimination. Therefor, this paper focus on reducing rise time and robustness against noise. The result that is simulated with feedforward method and sliding mode show that rise time decrease and robustness increase.