Name
Title | ||
|---|---|---|
Neural Adaptive Backstepping Control of a Robotic Manipulator With Prescribed Performance Constraint. |
Abstract | ||
|---|---|---|
This paper presents an adaptive neural network (NN) control of a two-degree-of-freedom manipulator driven by an electrohydraulic actuator. To restrict the system output in a prescribed performance constraint, a weighted performance function is designed to guarantee the dynamic and steady tracking errors of joint angle in a required accuracy. Then, a radial-basis-function NN is constructed to train the unknown model dynamics of a manipulator by traditional backstepping control (TBC) and obtain the preliminary estimated model, which can replace the preknown dynamics in the backstepping iteration. Furthermore, an adaptive estimation law is adopted to self-tune every trained-node weight, and the estimated model is online optimized to enhance the robustness of the NN controller. The effectiveness of the proposed control is verified by comparative simulation and experimental results with Proportional–integral-derivative and TBC methods. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/TNNLS.2018.2854699 | IEEE transactions on neural networks and learning systems |
Keywords | Field | DocType |
Manipulator dynamics,Adaptation models,Artificial neural networks,Adaptive systems,Backstepping | Control theory,Backstepping,Pattern recognition,Control theory,Computer science,Manipulator,Robustness (computer science),Artificial intelligence,Artificial neural network,Robot manipulator,Actuator | Journal |
Volume | Issue | ISSN |
30 | 12 | 2162-237X |
Citations | PageRank | References |
2 | 0.35 | 18 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Qing Guo | 1 | 10 | 3.93 |
| Yi Zhang | 2 | 3 | 2.73 |
| Branko G. Celler | 3 | 502 | 81.99 |
| S. Su | 4 | 23 | 4.87 |