Name
Title | ||
|---|---|---|
An Improved Single Neuron Adaptive PID Controller Based on Levenberg-Marquardt Algorithm. |
Abstract | ||
|---|---|---|
A new single neuron adaptive Proportional-Integral-Derivative (PID) controller based on Levenberg-Marquardt (LM) algorithm is presented in this paper. This new controller overcomes some drawbacks of the conventional single neuron adaptive PID controllers. There are two kinds of problems in traditional algorithms. Firstly, gradient descent algorithm is a one-order optimization method. Secondly, Newton iterative method costs much computing resource. For the improved controller, LM algorithm is applied, which combines steepest gradient descent and Gauss-Newton method. As a consequence, the convergence speed is increased and the control performance is greatly improved. The simulation results show that the control effect of this novel controller has strong robustness and good self-adaptation. © 2012 Springer-Verlag. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1007/978-3-642-31561-9_32 | BICS |
Keywords | Field | DocType |
adaptive,lm algorithm,pid control,single neuron | Convergence (routing),Control theory,Gradient descent,PID controller,Control theory,Iterative method,Computer science,Robustness (computer science),Levenberg–Marquardt algorithm | Conference |
Volume | Issue | ISSN |
7366 LNAI | null | 16113349 |
Citations | PageRank | References |
1 | 0.37 | 3 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tingting Hu | 1 | 63 | 11.93 |
| Yu-Feng Zhuang | 2 | 1 | 0.37 |
| Jin Yu | 3 | 41 | 6.25 |