Robust Adaptive Neural Network Control for a Class of Uncertain MIMO Nonlinear Systems With Input Nonlinearities
Nanjing University of Aeronautics and Astronautics · National University of Singapore
Abstract
In this paper, robust adaptive neural network (NN) control is investigated for a general class of uncertain multiple-input-multiple-output (MIMO) nonlinear systems with unknown control coefficient matrices and input nonlinearities. For nonsymmetric input nonlinearities of saturation and deadzone, variable structure control (VSC) in combination with backstepping and Lyapunov synthesis is proposed for adaptive NN control design with guaranteed stability. In the proposed adaptive NN control, the usual assumption on nonsingularity of NN approximation for unknown control coefficient matrices and boundary assumption between NN approximation error and control input have been eliminated. Command filters are presented…
Citation impact
- FWCI
- 67.08
- Percentile
- 100%
- References
- 48
Authors
3Topics & keywords
- Backstepping
- Control theory (sociology)
- Adaptive control
- Artificial neural network
- Nonlinear system
- Robust control
- MIMO
- Computer science