Three forms of robust model-based control were experimentally evaluated. Algorithm evaluation was motivated by a requirement for controllers with good high speed tracking accuracy in uncertain payload environments. The test case was a PUMA-560 operating over the standard test suite. The tracking performance of the robust algorithms was compared, with and without payload, to that of a non-adaptive model-based controller with fixed PD feedback. The model-based controllers were made robust by; addition of an auxiliary input term, replacing the PD feedback with a feedback loop based on Quanitative Feedback Theory (QFT), or a n adaptive feedforward compensator based on Lyapunov theory. Experimental evaluation provided valuable insight into the potential and limitations of each method. All three techniques improved the tracking performance of the manipulator. Superior overall performance, computational simplicity, and a mathematically rigorous design and tuning procedure make the model-based controller with QFT feedback the algorithm of choice.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.