Model-based control with quantitative feedback theory

A form of robust model-based control for a robotic arm is proposed and experimentally evaluated. The model-based with quantitative feedback theory (MBQFT) technique replaces the proportional-derivative feedback loop with a controller design based on pseudocontinuous time analog quantitative feedback...

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Bibliographic Details
Main Authors: Bossert, D.E., Lamont, G.B., Leahy, M.B., Horowitz, I.M.
Format: Conference Proceeding
Language:English
Subjects:
Adaptive control
Difference equations
Feedback loop
Payloads
PD control
Proportional control
Robot control
Robust control
Robustness
Uncertainty
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Summary:A form of robust model-based control for a robotic arm is proposed and experimentally evaluated. The model-based with quantitative feedback theory (MBQFT) technique replaces the proportional-derivative feedback loop with a controller design based on pseudocontinuous time analog quantitative feedback theory. MBQFT design produces a feedback controller that can be implemented by a series of simple backwards difference equations. MBQFT high-speed tracking accuracy was experimentally evaluated on the first three links of a PUMA-560. This robust technique increased tracking accuracy by up to a factor of four over the model-based controller performance baseline. The MBQFT tracking performance was robust to both unmodeled drive system dynamics and payload uncertainty. The nonheuristic nature of MBQFT design and tuning should allow application to a wide range of manipulators.< >
DOI:10.1109/ROBOT.1990.126308