Adaptive output feedback NN control of a class of discrete-time MIMO nonlinear systems with unknown control directions.
In this paper, adaptive neural network (NN) control is investigated for a class of block triangular multiinput-multioutput nonlinear discrete-time systems with each subsystem in pure-feedback form with unknown control directions. These systems are of couplings in every equation of each subsystem, and different subsystems may have different orders. To avoid the noncausal problem in the control design, the system is transformed into a predictor form by rigorous derivation. By exploring the properties of the block triangular form, implicit controls are developed for each subsystem such that the couplings of inputs and states among subsystems have been completely decoupled. The radial basis function NN is employed to approximate the unknown control. Each subsystem achieves a semiglobal uniformly ultimately bounded stability with the proposed control, and simulation results are presented to demonstrate its efficiency.
Li
Yanan
Y
National University of Singapore Graduate School for Integrative Sciences and Engineering, National University of Singapore, Singapore 119613. hit.li.yn@gmail.com
Yang
Chenguang
C
Ge
Shuzhi Sam
SS
Lee
Tong Heng
TH
D000465:Algorithms; D001185:Artificial Intelligence; D003198:Computer Simulation; D005246:Feedback; D008962:Models, Theoretical; D017711:Nonlinear Dynamics; D012815:Signal Processing, Computer-Assisted