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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Proceedings ArticleDOI
Observer based backstepping control for a three degree of freedom model helicopter
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TL;DR: An observer based backstepping control method is applied to the attitude control of a three degree of freedom (3DOF) model helicopter with unknown external disturbance and modeling uncertainties.
Proceedings ArticleDOI
Stable indirect adaptive HONN control for a class of non affine SISO nonlinear systems
TL;DR: In this article, adaptive neural tracking control for uncertain SISO non-affine systems in general form is presented, where the Taylor series expansion is employed to transform the systems into a block-triangular affine form in the neighborhood of the ideal unknown control law.
Proceedings ArticleDOI
Nonlinear Disturbance Observer based Sliding Mode Control for a Class of Uncertain Nonaffine Nonlinear Systems
Zhongjuan Li,Lingling Yang +1 more
TL;DR: In this article, the sliding mode tracking control is proposed for a class of uncertain non-affine nonlinear systems via the nonlinear disturbance observer (NDOB), based on the Taylor expansion method, the affine system is approximated to facilitate the desired control design.
Proceedings ArticleDOI
On Controller Design for Unknown Nonlinear Systems with Prescribed Performance and Input Constraints
Pankaj Mishra,Pushpak Jagtap +1 more
TL;DR: In this article , the authors considered the tracking control problem for an unknown control-affine nonlinear system with time-varying bounded disturbance subjected to a prescribed performance and input constraints.
References
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Journal ArticleDOI
A nonlinear disturbance observer for robotic manipulators
TL;DR: The global exponential stability of the proposed disturbance observer (DO) is guaranteed by selecting design parameters, which depend on the maximum velocity and physical parameters of robotic manipulators.
Journal ArticleDOI
Disturbance observer based control for nonlinear systems
TL;DR: This work presents a general framework for nonlinear systems subject to disturbances using disturbance observer based control (DOBC) techniques and develops a nonlinear disturbance observer for disturbances generated by an exogenous system.
Journal ArticleDOI
Adaptive tracking control of uncertain MIMO nonlinear systems with input constraints
TL;DR: The auxiliary design system is introduced to analyze the effect of input constraints, and its states are used to adaptive tracking control design, and the closed-loop semi-global uniformly ultimate bounded stability is achieved via Lyapunov synthesis.
Journal ArticleDOI
Adaptive neural control of uncertain MIMO nonlinear systems
Shuzhi Sam Ge,Cong Wang +1 more
TL;DR: Adapt neural control schemes are proposed for two classes of uncertain multi-input/multi-output (MIMO) nonlinear systems in block-triangular forms that avoid the controller singularity problem completely without using projection algorithms.
Journal ArticleDOI
Brief paper: Adaptive dynamic surface control of nonlinear systems with unknown dead zone in pure feedback form
Tao Zhang,Shuzhi Sam Ge +1 more
TL;DR: It is proved that the proposed design method is able to guarantee semi-global uniform ultimate boundedness of all signals in the closed-loop system, with arbitrary small tracking error by appropriately choosing design constants.