• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.614-619
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• 2004

The line-of-sight (LOS) stabilization system is a precision electro-mechanical gimbals assembly for rejecting vibration to isolate the load from its environment and point toward the target in a desired direction. This paper describes the design of gimbals system to reject the disturbance and to improve stabilization. To generate movement commands for the actuators in the stabilization system, the control system uses a sensor of angular rotation. The controller is a DSP with transducer and actuator interfaces. Unknown parameters of the gimbals are estimated using the signal compression method. The cross-correlation coefficient between the impulse response from the assumed model and the one from model of the gimbals is used to obtain the better estimation. And SMCPE (sliding mode control with perturbation estimation) is used to control the gimbals. SMCPE provides robustness of the control against the modeling deficiencies and unknown disturbances. In order to compare the performance of SMCPE with the classical SMC, a sample test result is presented.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1997.04a
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• pp.428-433
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• 1997

This paper presents a new control strategy for the position and force control of flexible manipulators. The governing equation of motion of a two-link flexible manipulator which features piezoceramic actuators bonded on each flexible beam is derived via Hamilton's principle. The control torque of the motor to command desired position and force is determined by a sliding mode controller on the basis of the rigid-mode dynamics. In the controller formulation, the sliding mode controller with perturbation estimation(SMCPE) is adopted to determine appropriate control gains. The SMCPE is then incorporated with the fuzzy technique to mitigate inherent chattering problem while maintaining the stability of the system. A set of fuzzy parameters and control rules are obtained from a relation between estimated perturbation and actual perturbation. During the commanded motion, undesirable oscillation is actively suppressed by applying feedback control voltages to the piezoceramic actuators. These feedback voltages are also determined by the SMCPE. Consequently, accurate force and position control of a two-link flexible manipulator are achieved. Computer simulations are undertaken in order to demonstrate the effectiveness of the proposed control methodology.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.10a
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• pp.95-95
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• 2003

• Journal of the Korean Society for Precision Engineering
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• v.23 no.1 s.178
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• pp.121-128
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• 2006

This paper deals with the application of enhanced perturbation estimation (SMCEPE) to sliding mode control of a dynamic system in the presence of perturbations including external disturbances, unpredictable parameter variations, and unstructured dynamics. Compared to conventional sliding mode control (SMC) and sliding mode control with perturbation estimation (SMCPE), the proposed one can offer robust control performances under serious control conditions, such as fast dynamic perturbations and slow loop-closure speeds, without a priori knowledge on upper bounds of perturbations. The perturbation estimator in SHCEPE also has more adaptability owing to the fractional-order hold technique. The effectiveness and superiority of the proposed control strategy are demonstrated by a series of simulations on the position tracking control of a two-link robot manipulator.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.30 no.8 s.251
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• pp.880-888
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• 2006

This paper presents the sliding mode control with the perturbation estimator for a nonlinear control system in the presence of perturbations including external disturbances, unpredictable parameter variations, ana unstructured dynamics. The proposed perturbation estimator is based on the Recursive Linear Smoothed Newton predictive algorithm so that it is effective to attenuate an undesired noise in high frequency band and to predict the present perturbation signal from the previous ones. Compared to conventional sliding mode control (SMC) and sliding mode control with perturbation estimation (SMCPE) introduced by Elmali and Olgac, the control algorithm proposed in this study can offer better tracking control performances and more feasible estimation characteristics. The effectiveness and superiority of the proposed control strategy are demonstrated by a series of simulations on the position tracking control of a simple two-link robot manipulator subject to velocity feedback signals including white noises.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.1120-1124
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• 2005

We reviewed controllers with a time delay estimation in this paper. Time delay control (TDC) and sliding mode control (SMC) are well known robust control schemes. Basically, the TDC has a main characteristic called a time delay estimation from which we can estimate the total uncertainty of a system. . The TDC causes the stick-slip in the case of systems with a friction. The so-called TDCSA which are short for TDC with switching action was developed to reduce the stick-slip. The TDC has the additional switching action term in the TDC structure. In the other hand, the SMC dose not have a time delay estimation but instead it can estimate the system uncertainty through the switching action. The SMC has a difficulty to estimate the total uncertainty of a system because it does not have a time delay estimation. In order to solve the difficulty, some control schemes were developed. Among them, we need to focus our attention on two control schemes: SMCPE and SMCTE, which are short for sliding mode control with a perturbation estimation and sliding mode control with a time delay estimation, respectively. In this paper, we analyzed and compared the characteristic of above three controllers. Even though the motives for the development of three control schemes are different, three control schemes have much in common in terms of their controller structures.