Neural Network-Based Adaptive Dynamic Surface Control for a Class of Uncertain Nonlinear Systems in Strict-Feedback Form
National University of Singapore · Chinese University of Hong Kong
Abstract
The dynamic surface control (DSC) technique was developed recently by Swaroop et al. This technique simplified the backstepping design for the control of nonlinear systems in strict-feedback form by overcoming the problem of "explosion of complexity." It was later extended to adaptive backstepping design for nonlinear systems with linearly parameterized uncertainty. In this paper, by incorporating this design technique into a neural network based adaptive control design framework, we have developed a backstepping based control design for a class of nonlinear systems in strict-feedback form with arbitrary uncertainty. Our development is able to eliminate the problem of "explosion of complexity" inherent in the…
Citation impact
- FWCI
- 49.49
- Percentile
- 100%
- References
- 20
Authors
2Topics & keywords
- Backstepping
- Control theory (sociology)
- Nonlinear system
- Strict-feedback form
- Adaptive control
- Parameterized complexity
- Computer science
- Artificial neural network
- Peace, Justice and strong institutions