• Transactions of the Korean Society of Machine Tool Engineers
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• v.18 no.1
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• pp.50-58
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• 2009

For precise tracking control of a servo system with nonlinear friction, a robust friction compensation scheme is presented in this paper. The nonlinear friction is difficult to identify the friction parameters exactly through experiments. Friction parameters can be also varied according to contact conditions such as the variation of temperature and lubrication. Thus, in order to overcome these problems and obtain the desired position tracking performance, a robust adaptive back-stepping control scheme with a dual friction observer is developed. In addition, to estimate lumped friction uncertainty due to modeling errors, a DEKF recurrent neural network and adaptive reconstructed error estimator are also developed. The feasibility of the proposed control scheme is verified through the experiment fur a ball-screw system.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.59 no.2
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• pp.163-172
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• 2010

A robust positioning control system has been studied using a friction parameter observer and a recurrent fuzzy neural network based on the sliding model. To estimate a nonlinear friction parameters of the LuGre friction model, a dual friction model-based observer is introduced. In addition, an approximating method for a system uncertainty has been developed using a recurrent fuzzy neural network technique to improve positioning performance. Experimental results have been presented to validate the performance of a proposed intelligent compensation scheme.

• Transactions on Control, Automation and Systems Engineering
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• v.4 no.4
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• pp.311-318
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• 2002

Two adaptive nonlinear friction compensation schemes are proposed for second-order nonlinear mechanical systems with a partially known nonlinear dynamic friction model to achieve asymptotic position and velocity tracking. The first scheme has auxiliary filtered states so that a simple open-loop observer can be used. The second one has a dual-observer structure to estimate two different nonlinear aspects of the friction state. Conditions for the parameter estimates to converge to the true parameter values are presented. Simulation results are utilized to show control performance and to demonstrate the convergence of the parameter estimates to their true values.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.1
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• pp.202-208
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• 2014

Friction force on robot systems is highly nonlinear and especially disturbs precise control of the robots at low speed. This paper deals with the dynamic friction compensation problem of a well-known one-link benchmark robot system. We consider the LuGre model because the model can successfully represent dynamic characteristics and various effects of friction phenomenon. The proposed controller is constructed as two parts. An adaptive controller based on dual observers is used to estimate and compensate the dynamic friction. In order to attenuate the friction estimation error and other disturbances, PI observer is additionally designed. Through the computer simulations with the benchmark system, this paper first examines the effects of nonlinear dynamic friction on the control performance of the benchmark robot system. Next, it is shown that the control performance against the dynamic friction is improved by using the proposed controller.

• Journal of the Semiconductor & Display Technology
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• v.6 no.1 s.18
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• pp.31-36
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• 2007

Effect of coulomb friction and backlash on the single loop position control has been studied for the precision position control. We have showed the limit cycle on the single loop system which used a ball screw that had the backlash. Also, we have made an inner loop with a classical velocity and torque controller which was forcing the current of d axis to be zero by using a permanent-magnet synchronous motor and composed the outer loop with linear encoder for sensing a position of the loader. Also, we have used least squares fit(LSF) observer for reducing noise when we got velocity from position outputs. We have shown a good result by using the dual loop through simulation and experiment.