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Identification of frictional effects and structural dynamics for improved control of hydraulic manipulators

University of British Columbia

Frictional terms and structural dynamics play an important role in achieving high quality performance of hydraulic manipulators. This thesis is mainly concerned with the identification of these effects and compensation thereof through control, for two different industrial applications. The first application pertains to a Cartesian electrohydraulic manipulator of a prototype fish processing machine which has been developed in the Industrial Automation Laboratory. Both modelbased and observer-based approaches to friction estimation are investigated for this basic system. In the first approach, a friction model is used that is linear in parameters, and the friction is assumed to be a fixed function of velocity. The model parameters and the object mass are determined by applying the least squares estimation procedure to experimental data. A combination of Coulomb, viscous, and Stribeck components are observed in the identified friction model. In the second approach, a modified version of an available nonlinear observer is used for real-time estimation of the friction parameter. Convergence rate of the observer is analyzed and an approximate algorithm is developed for choosing its gains. Next, a novel technique is developed for friction-compensated tracking control of the manipulator. The technique incorporates the estimated frictional force in an acceleration feedback control law. Specifically, the model-based approach to friction estimation results in a fixed friction compensation algorithm and the observer-based approach to friction estimation results in an adaptive friction compensation algorithm. Experimental investigations show that the technique that is presented in this thesis considerably improves tracking performance of the manipulator. The second application is a mini excavator system which is a typical example of the humanoperated mobile hydraulic machines. A new technique is presented in this thesis for indirect measurement of the joint torques of the backhoe links using load pin force sensors. Also, to be able to control the link motions electronically, the original pilot stage is modified by using on/off solenoid valves that are operated with DPWM (Differential-Pulse-Width-Modulation) current signals. Modeling and identification of the modified pilot stage is studied in the thesis in detail. According to the experimental results, the designed switching pilot system has a reliable performance that is linear. After the instrumentation phase, experiments are carried out with the mini excavator to determine the mass and inertia-related parameters of the links. To estimate the six mass-related (gravitational) parameters, sensor outputs are recorded in various static poses of the manipulator. The least squares estimation procedure is then applied to the decoupled form of the torque equations. The validation tests which we have carried out verify that the identified parameters can be used to estimate the static joint torques, with a good accuracy. An efficient algorithm is then developed for real-time estimation of the bucket load under static conditions. Experimental results show that the bucket load can be estimated at an accuracy level of 5%. To study the structural dynamics of the system, the Euler-Lagrange equations are derived for the manipulator. The structural (dynamic) parameters are defined using these equations. It is shown in this thesis that the six gravitational parameters are a subset of the nine dynamic parameters. Joint friction coefficients are then added to the parameter set. Finally, the combination of the dynamic parameters and friction coefficients are estimated from the identification data that is obtained by simultaneous movement of the links. The results are consistent with those of the static experiments. In this research, it is found that the friction inside the actuator seals is quite significant. It follows that the joint torques can be measured more accurately by using load pins instead of pressure sensors.

Thesis/Dissertation

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2009-04-03

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http://hdl.handle.net/2429/6805

Electrical and Computer Engineering

University of British Columbia

UBCV

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