Adaptive neural DSC for stochastic nonlinear constrained systems under arbitrary switchings

This paper proposes an adaptive neural dynamic surface control scheme for a class of strict-feedback stochastic nonlinear systems with guaranteed predefined performance under arbitrary switchings. First, by utilizing the prescribed performance control, the prescribed tracking control performance can...

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Bibliographic Details
Published in:Nonlinear dynamics 2017-12, Vol.90 (4), p.2531-2544
Main Authors: Si, Wenjie, Dong, Xunde
Format: Article
Language:English
Subjects:
Adaptive control
Automotive Engineering
Classical Mechanics
Constraints
Control
Control systems design
Controllers
Dynamical Systems
Engineering
Feedback control
Liapunov functions
Mechanical Engineering
Neural networks
Nonlinear systems
Original Paper
Parameterization
Stochastic systems
Subsystems
Switching theory
Tracking control
Vibration
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Summary:This paper proposes an adaptive neural dynamic surface control scheme for a class of strict-feedback stochastic nonlinear systems with guaranteed predefined performance under arbitrary switchings. First, by utilizing the prescribed performance control, the prescribed tracking control performance can be ensured with unknown initial errors, and input constraints are achieved by employing a continuous differentiable asymmetric saturation model. Second, RBF neural networks are used to handle unknown nonlinear functions and stochastic disturbances, and the dynamic surface control technique is used to avoid the problem of ‘explosion of complexity’ in control design. At last, by combining the common Lyapunov function method with the backstepping design principle, a common adaptive neural controller is constructed. The designed controller overcomes the problem of the over-parameterization and further alleviates the computational burden. Under the proposed common adaptive controller, all the signals in the closed-loop system are four-moment (or two-moment) semi-globally uniformly ultimately bounded, and the prescribed transient and steady tracking control performance are guaranteed under arbitrary switchings. The arbitrary switching behaviors among two and three subsystems are performed to demonstrate and verify the effectiveness of the proposed method.
ISSN:0924-090X
1573-269X
DOI:10.1007/s11071-017-3821-6