Friction compensation for an industrial hydraulic robot

Dept. of Autom. Control, Los Andes Univ., Merida
IEEE control systems (Impact Factor: 2.09). 03/1999; 19(1):25 - 32. DOI: 10.1109/37.745763
Source: IEEE Xplore


A model based friction compensation scheme using a novel dynamical
friction model was implemented on an industrial Schilling Titan II
hydraulic robot. Off-line estimation of parameters was carried out,
using the results of two kinds of experiments. These experiments were
done independently at each joint. A nonlinear PI type controller was
used in the inner torque loop to improve its performance. The complete
control scheme has shown to substantially improve the position precision
in regulation and tracking. Higher precision applications can be
performed by the hydraulic robot with this controller

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Available from: Guillaume Morel, Mar 20, 2015
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    • "However, more precise friction compensation cannot be expected due to insufficient representation of friction property in this method. Generally, the friction compensation using adaptive control and friction observer [6] [7] [8] [9] and friction feed-forward control [10] are the model-based control method that controller and/or observer contain the identified friction parameters. Thus, these compensation schemes will be very effective if the friction parameters are exactly identified and the operating conditions are clean and stable. "
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    ABSTRACT: A robust positioning control scheme has been developed using friction parameter observer and recurrent fuzzy neural networks based on the sliding mode control. As a dynamic friction model, the LuGre model is adopted for handling friction compensation because it has been known to capture sufficiently the properties of a nonlinear dynamic friction. A developed friction parameter observer has a simple structure and also well estimates friction parameters of the LuGre friction model. In addition, an approximation method for the system uncertainty is developed using recurrent fuzzy neural networks technology to improve the precision positioning degree. Some simulation and experiment provide the verification on the performance of a proposed robust control scheme.
    Journal of Mechanical Science and Technology 04/2012; 26(4). DOI:10.1007/s12206-012-0213-1 · 0.84 Impact Factor
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    • "The second method is the real time estimation scheme for nonlinear friction coefficients, which is called as the adaptive friction control scheme. This method can actively cope with the variation of the nonlinear friction, which has been proved and studied through experiments (Canudas de Wit, 1997)(Lischinsky, 1999)(Ha, 2000)(Tan, 1999). However, to generate the adaptation rules for the friction coefficients based on the LuGre friction model, a detailed mathematical approach is required. "
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    ABSTRACT: To improve position tracking performance of servo systems, a position tracking control using adaptive back-stepping control(ABSC) scheme and recurrent fuzzy neural networks(RFNN) is proposed. An adaptive rule of the ABSC based on system dynamics and dynamic friction model is also suggested to compensate nonlinear dynamic friction characteristics. However, it is difficult to reduce the position tracking error of servo systems by using only the ABSC scheme because of the system uncertainties which cannot be exactly identified during the modeling of servo systems. Therefore, in order to overcome system uncertainties and then to improve position tracking performance of servo systems, the RFNN technique is additionally applied to the servo system. The feasibility of the proposed control scheme for a servo system is validated through experiments. Experimental results show that the servo system with ABS controller based on the dual friction observer and RFNN including the reconstruction error estimator can achieve desired tracking performance and robustness.
    Fuzzy Logic - Controls, Concepts, Theories and Applications, 03/2012; , ISBN: 978-953-51-0396-7
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    • "Concerning hydraulic machinery, when the LuGre model is used as a friction compensator to control an arm with rotary motors [18] 1 or a prismatic cylinder (as in [22]), the 1 Estimating friction torques is only part of the problem in hydraulic machines. The other part concerns how to apply those torques at the joints. "
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    ABSTRACT: Operational space control has a number of de- sirable characteristics but is sensitive to model accuracy. For heavy machines the dynamics are difficult to model due to their friction and dynamic coupling, thus making full compensation imprecise. This work presents an approach in which a simplified model gives partial compensation via an open-loop feedforward input, pre-calculated in forward simulation. In this way, effects that are difficult to compensate for can be partially corrected without causing instability. Since the reference trajectory is known a priori, dynamic model parameters are tuned in its neighbourhood, reducing the burden of global modelling. The feasibility and performance of this approach is shown experimentally via improved free motion tracking of an exca- vator arm. This framework further supports efforts for direct impedance control between bucket tip and soil.
    2011 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2011, San Francisco, CA, USA, September 25-30, 2011; 01/2011
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