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|Title:||Adaptive NN control for a class of discrete-time non-linear systems|
|Authors:||Ge, S.S. |
|Citation:||Ge, S.S., Lee, T.H., Li, G.Y., Zhang, J. (2003-03-10). Adaptive NN control for a class of discrete-time non-linear systems. International Journal of Control 76 (4) : 334-354. ScholarBank@NUS Repository. https://doi.org/10.1080/0020717031000073063|
|Abstract:||In this paper, adaptive neural network (NN) control is investigated for a class of single-input single-output (SISO) discrete-time unknown non-linear systems with general relative degree in the presence of bounded disturbances. Firstly, the systems are transformed into a causal state space description, adaptive state feedback NN control is presented based on Lyapunov's stability theory. Then, by converting the systems into a causal input-output representation, adaptive output feedback NN control is given. Finally, adaptive NN observer design and observer-based adaptive control are presented under the assumption of persistent excitation (PE). All the control schemes avoid the so-called controller singularity problem in adaptive control. By suitably choosing the design parameters, the closed-loop systems are proven to be semi-globally uniformly ultimately bounded (SGUUB). Simulation studies show the effectiveness of the newly proposed schemes.|
|Source Title:||International Journal of Control|
|Appears in Collections:||Staff Publications|
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