• Transactions of the Korean Society of Machine Tool Engineers
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• v.18 no.1
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• pp.90-102
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• 2009

In this paper, a tracking control problem for a mechanical servo system with nonlinear dynamic friction is treated. The nonlinear friction model contains directly immeasurable friction state and the uncertainty caused by incomplete modeling and variations of its parameter. In order to provide the efficient solution to these control problems, we propose a hybrid control scheme, which consists of a robust friction state observer, a RFNN estimator and an approximation error estimator with sliding mode control. A sliding mode controller and a robust friction state observer is firstly designed to estimate the unknown infernal state of the LuGre friction model. Next, a RFNN estimator is introduced to approximate the unknown lumped friction uncertainty. Finally, an adaptive approximation error estimator is designed to compensate the approximation error of the RFNN estimator. Some simulations and experiments on the mechanical servo system composed of ball-screw and DC servo motor are presented. Results demonstrate the remarkable performance of the proposed control scheme.

• Proceedings of the KIPE Conference
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• 1998.10a
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• pp.768-773
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• 1998

The speed control of SRM(Switched Reluctance Motor) needs the accurate position and speed data of rotor. This information is generally provided by a shaft encoder or resolver. In some cases, the environment is which the motor operates may cause difficulties in maintaining the satisfactory position detection performance. Therefore, the elimination of the position and speed sensor has gained wide attention. In this paper, a new algorithm for estimation of rotor position and speed is described for the SRM drives. This method uses is nonlinear adaptive observer using the MRAS(Model Reference Adaptive System). The observer is proved by Lyapunov Stability Theory. This algorithm was implemented with a TMS320C31 DSP. Experiment results prove that the observer is able to estimate the speed and position with a little errors.

• Journal of the Korean Society of Safety
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• v.13 no.1
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• pp.54-63
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• 1998

This paper proposes a theoretical analysis of a closed loop adaptive speed control system for control the inverter driven permanent magnet synchronous motor(PMSM). This control system utilizes a mechanically sensorless state observer for the generation of all controller feedback information. The observer processes measurements of stator frame voltage and current to produce estimates of rotor position and speed and rotor frame currents. It is shown that the identity observer, when properly formulated, has the same linearized error dynamics as the extended kalman filter(EKF). Consequently, it is shown that the gains within the identity observer can be designed in a manner identical to that of the EKF. In this way, the designability of the nonlinear observer is assured, as is the optimality of its performance for small errors. A sequence of simulation are performed and they demonstrate the successful performance.

• Smart Structures and Systems
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• v.6 no.1
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• pp.1-16
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• 2010

This paper presents a novel smart MEMS accelerometer which employs a hybrid control algorithm and an estimator. This scheme is realized by adding a sliding-mode controller to a conventional PID closed loop system to achieve higher stability and higher dynamic range and to prevent pull-in phenomena by preventing finger displacement from passing a maximum preset value as well as adding an adaptive nonlinear observer to a conventional PID closed loop system. This estimator is used for online estimation of the parameter variations for MEMS accelerometers and gives the capability of self testing to the system. The analysis of convergence and resolution show that while the proposed control scheme satisfies these criteria it also keeps resolution performance better than what is normally obtained in conventional PID controllers. The performance of the proposed hybrid controller investigated here is validated by computer simulation.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.50 no.1
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• pp.31-37
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• 2001

A robust adaptive technique for the longitudinal control of a platoon of automated vehicles is presented. A nonlinear model is used to represent the dynamics of each vehicle within the platoon. The external disturbances such as wind gust and a disturbance term due to engine transmission variations and so on are considered. The state observer is used to avoid direct measurement of the relative velocity or acceleration between the controlled and leading vehicles or the controlled vehicles's acceleration. The proposed controller guarantees to recover platoon stability in operation even if a speed dependent spacing policy is adopted, which incorporates a constant time headway in addition to the constant distance. It is shown that the proposed observer is exponentially stable, and the at the robust adaptive controller is stable. The simulation results demonstrate excellent tracking even in the presence of disturbances.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.49 no.11
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• pp.763-770
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• 2000

The speed and position information of the rotor are required in the speed control of SRM(Switched Reluctance Motors). This information is generally provided by shaft encoder or resolver. It is weak in the dusty, high temperature, and EMI environment. Consequntly, much attention has been given to SRM control for eliminationating the position and speed sensors. In this paper, a new estimation algorithm for the rotor position and speed for SRM drives is described. The algorithm is implemented by the sliding mode observer. The stability and robustness of the sliding observer for the parameter variations of the SRM are proved by variable structure control theory. Speed control of the SRM is accomplished by the estimated speed and position. Experiment results verify that the mode observer is able to estimate the speed and position well.

• International Journal of Control, Automation, and Systems
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• v.4 no.4
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• pp.414-427
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• 2006

This paper presents an adaptive feedback linearization control scheme for induction motors with simultaneous variation of rotor and stator resistances. Two typical modeling techniques, rotor flux model and stator flux model, have been developed and successfully applied to the controller design and adaptive observer design, respectively. By using stator fluxes as states, over-parametrization in adaptive control can be prevented and control strategy can be developed without the need of nonlinear transformation. It also decrease the relative degree for the flux modulus by one, thereby, yielding, a simple control algorithm. However, when this method is used for flux observer, it cannot guarantee the convergence of flux. Similarly, the rotor flux model may be appropriate for observers, but it is not so for adaptive controllers. In addition, if these two existing methods are merged into overall adaptive control system, it brings about structural complexies. In this paper, we did not use these two modeling methods, and opted for the airgap flux model which takes on only the positive aspects of the existing rotor flux model and stator flux model and prevents structural complexity from occuring. Through theoretical analysis by using Lyapunov's direct method, simulations, and actual experiments, it is shown that stator and rotor resistances converge to their actual values, flux is well estimated, and torque and flux are controlled independently with the measurements of rotor speed, stator currents, and stator voltages. These results were achieved under the persistent excitation condition, which is shown to hold in the simulation.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.506-506
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• 2000

To improve control performance of a non-linear system, many other researches have used the sliding mode control algorithm. The sliding mode controller is known to be robust against nonlinear and unmodeled dynamic terms. However. this algorithm raises the inherent chattering caused by excessive switching inputs around the sliding surface. Therefore, in order to solve the chattering problem and improve control performance, this study has developed the sliding mode controller with a perturbation estimator using the observer-based fuzzy adaptive network generates the control input for compensating unmodeled dynamics terms and disturbance. And, the weighting parameters of the fuzzy adaptive network are updated on-line by adaptive law in order to force the estimation errors to converge to zero. Therefore, the combination of sliding mode control and fuzzy adaptive network gives rise to the robust and intelligent routine. For evaluating control performance of the proposed approach. tracking control simulation is carried out for the hydraulic motion simulator which is a 6-degree of freedom parallel manipulator.

• Proceedings of the KIPE Conference
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• 2003.11a
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• pp.186-189
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• 2003

This paper is proposed to position and speed control of interior permanent magnet synchronous motor(IPMSM) drive without mechanical sensor. A gopinath observer is used for the mechanical state estimation of the motor. The observer was developed based on nonlinear model of IPMSM, that employs a d-q rotating reference frame attached to the rotor, A gopinath observer is implemented to compute the speed and position feedback signal. The validity of the proposed scheme is confirmed by various response characteristics.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.53 no.8
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• pp.500-508
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• 2004

This paper presents a new sensorless vector control system for high performance induction motor drives fed by a matrix converter with non-linearity compensation and disturbance observer. The nonlinear voltage distortion that is caused by commutation delay and on-state voltage drop in switching device is corrected by a new matrix converter modeling. The lumped disturbances such as parameter variation and load disturbance of the system are estimated by the radial basis function network (RBFN). An adaptive observer is also employed to bring better responses at the low speed operation. Experimental results are shown to illustrate the performance of the proposed system.