Name
Title | ||
|---|---|---|
Composite adaptive locally weighted learning control for multi-constraint nonlinear systems. |
Abstract | ||
|---|---|---|
•Barrier functions are introduced to tackle state constraints and asymmetric control saturation.•A serial-parallel estimation model is designed to construct the prediction errors.•A composite adaptive LWL NN is designed to approximate system uncertainties.•The use of command filters decreases computational complexity of the backstepping control. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1016/j.asoc.2017.09.011 | Applied Soft Computing |
Keywords | Field | DocType |
Barrier Lyapunov function,Neural network,Control saturation,State constraint,Locally weighted learning | Nonlinear system,Control theory,State variable,Artificial intelligence,Artificial neural network,Trajectory,Formal proof,Lyapunov function,Backstepping,Mathematical optimization,Machine learning,Mathematics,Tracking error | Journal |
Volume | ISSN | Citations |
61 | 1568-4946 | 4 |
PageRank | References | Authors |
0.41 | 20 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tairen Sun | 1 | 41 | 3.81 |
| Yongping Pan | 2 | 50 | 4.64 |
| Chenguang Yang | 3 | 2213 | 138.71 |