• Journal of Power Electronics
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• v.7 no.2
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• pp.159-173
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• 2007

In this paper, an intelligent sliding-mode position controller (ISMC) for achieving favorable decoupling control and high precision position tracking performance of permanent-magnet synchronous motor (PMSM) servo drives is proposed. The intelligent position controller consists of a sliding-mode position controller (SMC) in the position feed-back loop in addition to an on-line trained fuzzy-neural-network model-following controller (FNNMFC) in the feedforward loop. The intelligent position controller combines the merits of the SMC with robust characteristics and the FNNMFC with on-line learning ability for periodic command tracking of a PMSM servo drive. The theoretical analyses of the sliding-mode position controller are described with a second order switching surface (PID) which is insensitive to parameter uncertainties and external load disturbances. To realize high dynamic performance in disturbance rejection and tracking characteristics, an on-line trained FNNMFC is proposed. The connective weights and membership functions of the FNNMFC are trained on-line according to the model-following error between the outputs of the reference model and the PMSM servo drive system. The FNNMFC generates an adaptive control signal which is added to the SMC output to attain robust model-following characteristics under different operating conditions regardless of parameter uncertainties and load disturbances. A computer simulation is developed to demonstrate the effectiveness of the proposed intelligent sliding mode position controller. The results confirm that the proposed ISMC grants robust performance and precise response to the reference model regardless of load disturbances and PMSM parameter uncertainties.

• International Journal of Control, Automation, and Systems
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• v.6 no.6
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• pp.960-967
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• 2008

This paper shows that design of a robustly stable repetitive control system is equivalent to that of a feedback control system for an uncertain linear time-invariant system satisfying the well-known robust performance condition. Once a feedback controller is designed to satisfy the robust performance condition, the feedback controller and the repetitive controller using the performance weighting function robustly stabilizes the repetitive control system. It is also shown that we can obtain a steady-state tracking error described in a simple form without time-delay element if the robust stability condition is satisfied for the repetitive control system. Moreover, using this result, a sufficient condition is provided, which ensures that the least upper bound of the steady-state tracking error generated by the repetitive control system is less than or equal to the least upper bound of the steady-state tracking error only by the feedback system.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.1955-1957
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• 2001

This paper propose the design method of robust tracking controller for nonlinear TS fuzzy system with uncertainties. The robust tracking controller design is presented by constraint of robust stability for nonlinear system. A sufficient condition of the robust stability is presented by LMI(Linear Matrix Inequality) soltuion in the sense of Lyapunov for TS fuzzy system with uncertainties. The effectiveness of the proposed robust tracking con design is demonstrated through a numerical simulatio.

• Smart Structures and Systems
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• v.9 no.4
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• pp.373-392
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• 2012

Tracking control of systems with variable stiffness hysteresis using a gain-scheduled (GS) controller is developed in this paper. Variable stiffness hysteretic system is represented as quasi linear parameter dependent system with known bounds on parameters. Assuming that the parameters can be measured or estimated in real-time, a GS controller that ensures the performance and the stability of the closed-loop system over the entire range of parameter variation is designed. The proposed method is implemented on a spring-mass system which consists of a semi-active independently variable stiffness (SAIVS) device that exhibits hysteresis and precisely controllable stiffness change in real-time. The SAIVS system with variable stiffness hysteresis is represented as quasi linear parameter varying (LPV) system with two parameters: linear time-varying stiffness (parameter with slow variation rate) and stiffness of the friction-hysteresis (parameter with high variation rate). The proposed LPV-GS controller can accommodate both slow and fast varying parameter, which was not possible with the controllers proposed in the prior studies. Effectiveness of the proposed controller is demonstrated by comparing the results with a fixed robust $\mathcal{H}_{\infty}$ controller that assumes the parameter variation as an uncertainty. Superior performance of the LPV-GS over the robust $\mathcal{H}_{\infty}$ controller is demonstrated for varying stiffness hysteresis of SAIVS device and for different ranges of tracking displacements. The LPV-GS controller is capable of adapting to any parameter changes whereas the $\mathcal{H}_{\infty}$ controller is effective only when the system parameters are in the vicinity of the nominal plant parameters for which the controller is designed. The robust $\mathcal{H}_{\infty}$ controller becomes unstable under large parameter variations but the LPV-GS will ensure stability and guarantee the desired closed-loop performance.

• Proceedings of the KIEE Conference
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• 1988.11a
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• pp.80-83
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• 1988

In this paper a robust control law is presented which stabilezes overall system via pole reassignment and loop-shaping. A robust adaptive controller is designed combining this robust control law and a robust estimator.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1448-1451
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• 1997

In this paper, a speed control of nin-servo induction motor is considered. In this case, it is difficult to satisfy precise control performance. SO H.inf. robust controller is designed for this problem by usign polynomial approach and Youla parameterization.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.11a
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• pp.188-190
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• 2000

This paper proposed design of robust fuzzy controller for nonlinear systems in the presence of parametric uncertainties. In the design procedure, we represent the nonlinear system using Takagi-Sugeno fuzzy model. A sufficient condition of the robust stability is presented in the sense of Lyapunov for the TSK fuzzy model with uncertainties. Finally, the effectiveness of proposed controller has been through a result of numerical simulation.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.139-144
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• 1993

In this paper, a robust reduced order adaptive controller is proposed based on Internal Model Control(IMC) structure for stochastic linear stable systems. The concept of gain margin is utilized to make the adaptive IMC controller robust. We prove the stability of the proposed adaptive IMC system for stable plants under the assumption that upper bounds for system orders are known. Simulation results show that the proposed method has good performance and stability robustness.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.477-481
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• 1993

The aim of this paper is to analyze via computer simulation the robust performance of TDF(Two Degree of Freedom) H.$_{\infty}$ controller for uncertain systems having parameter uncertainty. We apply the TDF H$_{\infty}$ controller to autopilot design. We evaluate the robust performance of the TDF H$_{\infty}$ controller for uncertain systems and present the guaranteed bound of robust performance via computer simulation.on.

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.177-182
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• 1989

In this paper a new adaptive control algorithm is derived, with the unknown manipulator and payload parameters being estimated online. In practice, we may simplify the algorithm by not explicity estimating all unknown parameters. Further, the controller must be robust to residual time-varying disturbance, such as striction or torque ripple. Also, the reference model is a simple douple integrator and the acceleration input for robot manipulator consists of a proportion and derivative controller for trajectory tracking purposes. The validity of this control is confirmed in simulation where two-link robot manipulator shows the robust performances in spite of the existing nonlinear interaction and unknown parametrictings