We formulate a predictor-based controller for a high-DOF manipulator to compensate a time-invariant input delay during a pick-and-place task. Robot manipulators are widely used in tele-manipulation systems on the account of their reliable, fast, and precise motions while they are subject to large delays. Using common control algorithms on such delay systems can cause not only poor control performance, but also catastrophic instability in engineering applications. Therefore, delays need to be compensated in designing robust control laws. As a case study, we focus on a 7-DOF Baxter manipulator subject to three different input delays. First, delay-free dynamic equations of the Baxter manipulator are derived using the Lagrangian method. Then, we formulate a predictor-based controller, in the presence of input delay, in order to track desired trajectories. Finally, the effects of input delays in the absence of a robust predictor are investigated, and then the performance of the predictor-based controller is experimentally evaluated to reveal robustness of the algorithm formulated. Simulation and experimental results demonstrate that the predictor-based controller effectively compensates input delays and achieves closed-loop stability.
Adaptive Control of a Two-Link Robot Using Batch Least-Square Identifier
We design a regulation-triggered adaptive controller
for robot manipulators to efficiently estimate unknown
parameters and to achieve asymptotic stability in the presence of
coupled uncertainties. Robot manipulators are widely used in
telemanipulation systems where they are subject to model and
environmental uncertainties. Using conventional control
algorithms on such systems can cause not only poor control
performance, but also expensive computational costs and
catastrophic instabilities. Therefore, system uncertainties need to
be estimated through designing a computationally efficient
adaptive control law. We focus on robot manipulators as an
example of a highly nonlinear system. As a case study, a 2-DOF
manipulator subject to four parametric uncertainties is
investigated. First, the dynamic equations of the manipulator are
derived, and the corresponding regressor matrix is constructed
for the unknown parameters. For a general nonlinear system, a
theorem is presented to guarantee the asymptotic stability of the
system and the convergence of parameters’ estimations. Finally,
simulation results are discussed for a two-link manipulator, and
the performance of the proposed scheme is thoroughly evaluated.
- Editors:
- Liu, Tengfei; Ou, Yan.
- Publication Date:
- NSF-PAR ID:
- 10199780
- Journal Name:
- IEEECAA journal of automatica sinica
- Volume:
- 8
- Issue:
- 1
- Page Range or eLocation-ID:
- 86-93
- ISSN:
- 2329-9266
- Sponsoring Org:
- National Science Foundation
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Accepted Manuscript1.0
- Publisher's Version of Record
- https://doi.org/10.1109/JAS.2020.1003459
