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Path-invariant and time-optimal motion control for industrial robots

University of British Columbia

This thesis presents practical methods for planning and control to improve the motion performance of industrial robots. Particular attention is given to the commercial six degrees-of-freedom articulated robot with a low-cost generic controller. A comparative study of motion control methods demonstrated that both smooth trajectory planning and filtering techniques, when combined with a traditional Proportional-Derivative control, are limited in achievable performance due to reduced accelerations (smooth trajectory) or large path-distortions (filtering technique). Instead, faster and more accurate motion is achieved with a low-order trajectory, namely, trapezoidal velocity profile, with feedforward control design based on an elastic model. The key component that makes the latter approach more appealing is the delay-free dynamic input shaper embedded in the feedforward control. Following the results from the comparative study, two innovations are proposed to satisfy the path-invariant and time-optimal motion. First, an online time-optimal trapezoidal velocity profile planned along multiple path segments is presented. The trajectory can be planned for arbitrary boundary conditions and path curvatures with only four system-dynamics computations per path segment. Next, a novel control method based on the flexible joint dynamic model is proposed to achieve high tracking performance for the proposed trajectory. The proposed nonlinear multivariable control can place the closed-loop poles arbitrarily with only position and velocity feedback. Real-world experiments with commercial industrial robots are carried out to validate the presented methods.

Text

2017-04-20

Attribution-NonCommercial-NoDerivatives 4.0 International

http://hdl.handle.net/2429/61295

Mechanical Engineering

University of British Columbia

UBCV

http://creativecommons.org/licenses/by-nc-nd/4.0/