Name
Title | ||
|---|---|---|
A Novel Adaptive Jerk Control With Application to Large Workspace Tracking on a Flexure-Linked Dual-Drive Gantry |
Abstract | ||
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In this work, the design of a novel the flexure-linked dual-drive H-gantry is first introduced. Compared to conventional stacked
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tables, the advantages of this gantry are on decoupled
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actuation, better mechanical reliability, larger driving force, and shorter response time. However, after deriving its reduced-order dynamical model, it is found that the precision of the end-effector is significantly affected by the position dependent torque caused by the inter-parallel-axes driving forces on the fixed inertia frame and coupling forces from the pair of flexures. These form barriers that limit precision positioning and tracking performance over a large workspace. Thus, in the following part, a robust integral of signum of error (RISE) control with novel jerk adaptation is proposed on top of the standard proportional-integral-derivative (PID) and feedforward scheme. Compared with some prior RISE schemes with gain adaptation, the proposed scheme yields bounded robust gain in the presence of noisy velocity estimation. Real-time experiments on the actual testbed indicate that both improvement of motion precision and prevention of resonant mode excitation over a large workspace are successfully achieved in the proposed scheme. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/TIE.2018.2870391 | IEEE Transactions on Industrial Electronics |
Keywords | Field | DocType |
Force,Friction,Robustness,Torque,Couplings,End effectors | Torque,Coupling,PID controller,Workspace,Control theory,Jerk,Robustness (computer science),Inertia,Engineering,Feed forward | Journal |
Volume | Issue | ISSN |
66 | 7 | 0278-0046 |
Citations | PageRank | References |
1 | 0.37 | 0 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| nazir kamaldin | 1 | 7 | 1.60 |
| Si-Lu Chen | 2 | 89 | 15.74 |
| Chek-Sing Teo | 3 | 54 | 12.65 |
| Wei Lin | 4 | 79 | 14.50 |
| Kok Kiong Tan | 5 | 923 | 99.57 |