Journal ArticleDOI
Direct Adaptive Neural Control for a Class of Uncertain Nonaffine Nonlinear Systems Based on Disturbance Observer
Mou Chen,Shuzhi Sam Ge +1 more
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TLDR
Both state feedback and output feedback direct adaptive controls can guarantee semiglobal uniform boundedness of the closed-loop system signals as rigorously proved by Lyapunov analysis.Abstract:
In this paper, the direct adaptive neural control is proposed for a class of uncertain nonaffine nonlinear systems with unknown nonsymmetric input saturation. Based on the implicit function theorem and mean value theorem, both state feedback and output feedback direct adaptive controls are developed using neural networks (NNs) and a disturbance observer. A compounded disturbance is defined to take into account of the effect of the unknown external disturbance, the unknown nonsymmetric input saturation, and the approximation error of NN. Then, a disturbance observer is developed to estimate the unknown compounded disturbance, and it is established that the estimate error converges to a compact set if appropriate observer design parameters are chosen. Both state feedback and output feedback direct adaptive controls can guarantee semiglobal uniform boundedness of the closed-loop system signals as rigorously proved by Lyapunov analysis. Numerical simulation results are presented to illustrate the effectiveness of the proposed direct adaptive neural control techniques.read more
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Barrier Lyapunov functions for Nussbaum gain adaptive control of full state constrained nonlinear systems
Yan-Jun Liu,Shaocheng Tong +1 more
TL;DR: Two theorems are provided to show that all the signals in the closed-loop system are bounded, the outputs are driven to follow the reference signals and all the states are ensured to remain in the predefined compact sets.
Journal ArticleDOI
The elements of real analysis (2nd edition), by Robert G. Bartle. Pp xv, 480. £10. 1976. SBM 0 471 05464 X (Wiley)
TL;DR: A Glimpse at Set Theory: The Topology of Cartesian Spaces and the Functions of One Variable.
Journal ArticleDOI
Adaptive control-based Barrier Lyapunov Functions for a class of stochastic nonlinear systems with full state constraints
TL;DR: It is proved that all the signals in the closed-loop system are semi-global uniformly ultimately bounded (SGUUB) in probability, the system output is driven to follow the reference signals, and all the states are ensured to remain in the predefined compact sets.
Journal ArticleDOI
Dynamic Surface Control Using Neural Networks for a Class of Uncertain Nonlinear Systems With Input Saturation
TL;DR: The problem of explosion of complexity inherent in the conventional backstepping method is avoided and the ultimately bounded convergence of all closed-loop signals is guaranteed via Lyapunov analysis.
Journal ArticleDOI
Adaptive Neural Network Control of a Marine Vessel With Constraints Using the Asymmetric Barrier Lyapunov Function
Wei He,Zhao Yin,Changyin Sun +2 more
TL;DR: This paper considers the trajectory tracking of a marine surface vessel in the presence of output constraints and uncertainties, and an asymmetric barrier Lyapunov function is employed to cope with the output constraints.
References
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Journal ArticleDOI
Sliding mode control for a class of non-affine nonlinear systems
TL;DR: In this paper, a rotor supported by a pair of magnetic bearings is introduced as a nonlinear system which is designed as a sequence of linear time-varying (LTV) systems and iterated for each time.
Proceedings ArticleDOI
Adaptive tracking control of a class of non-affine plants using dynamic feedback
TL;DR: This paper proposes a systematic procedure for adaptive tracking control design for a class of nonlinear plants that are nonaffine in the control input that is based on differentiating the original state equation so that the derivative of the controlinput appears linearly and is used as the new control variable.
Proceedings ArticleDOI
Fuzzy adaptive linearizing control for non-affine systems
TL;DR: The aim of this paper is to examine the feedback linearization technique for unknown non affine-in-control systems using an adaptive Takagi-Sugeno fuzzy system and the results show that the closed-loop control structure stability is guaranteed using Lyapunov analysis.
Journal ArticleDOI
Adaptive variable structure state estimation for uncertain systems with persistently bounded disturbances
Huai-Ning Wu,Peng Shi,Peng Shi +2 more
TL;DR: In this paper, an adaptive state estimator design methodology for nonlinear systems with unknown nonlinearities and persistently bounded disturbances is proposed, and the existence condition of the adaptive estimators is provided in terms of linear matrix inequality (LMI).
Journal ArticleDOI
RBFN-based decentralized adaptive control of a class of large-scale non-affine nonlinear systems
TL;DR: For a class of large-scale decentralized nonlinear systems with strong interconnections, a radial basis function neural network (RBFN) adaptive control scheme is proposed and the result of simulation validates the effectiveness of the proposed scheme.