Name
Title | ||
|---|---|---|
Event-Driven Nonlinear Discounted Optimal Regulation Involving a Power System Application. |
Abstract | ||
|---|---|---|
By employing neural network approximation architecture, the nonlinear discounted optimal regulation is handled under event-driven adaptive critic framework. The main idea lies in adopting an improved learning algorithm, so that the event-driven discounted optimal control law can be derived via training a neural network. The stability guarantee and simulation illustration are also included. It is h... |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/TIE.2017.2698377 | IEEE Transactions on Industrial Electronics |
Keywords | Field | DocType |
Optimal control,Cost function,Biological neural networks,Power system stability,Adaptive systems,Stability analysis | Mathematical optimization,Optimal control,Nonlinear system,Discounting,Computer science,Adaptive system,Control theory,Electric power system,Control engineering,Learning rule,Artificial neural network,Lyapunov approach | Journal |
Volume | Issue | ISSN |
64 | 10 | 0278-0046 |
Citations | PageRank | References |
5 | 0.37 | 20 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ding Wang | 1 | 1870 | 68.16 |
| Haibo He | 2 | 3653 | 213.96 |
| Xiangnan Zhong | 3 | 346 | 16.35 |
| Derong Liu | 4 | 181 | 6.71 |