Adaptive Finite-time Tracking Control for One-link Manipulator with Funnel Boundary Constraints

The problem of adaptive finite-time tracking control for one-link manipulator with funnel boundary constraints is investigated. In order to converge the output tracking error to the prescribed funnel boundary constraints in a finite period of time, a modified funnel boundary variable is introduced, and the original error model is transformed into a new one which is introduced to design the controller. Theory analysis demonstrates the system is semi-global practical finite-time stable(SGPFS), and the output tracking error can also be forced into the prescribed funnel boundary region. Different from the conventional prescribed performance control(PPC), the proposed method overcomes the problem of the singularity that exists in design of backstepping method, and guarantees that all the signals of the closed-loop system are SGPFS, at the same time, the output tracking error can converge to the the given funnel boundary constraints. A simulation example shows that the proposed approach is effective.

[1]  Wei Xing Zheng,et al.  Nonsmooth stabilization of a class of nonlinear cascaded systems , 2012, Autom..

[2]  Jing Zhang,et al.  Adaptive Neural Network Finite-Time Output Feedback Control of Quantized Nonlinear Systems , 2018, IEEE Transactions on Cybernetics.

[3]  Ming Chen,et al.  Adaptive fuzzy funnel control for a class of strict feedback nonlinear systems , 2017, Neurocomputing.

[4]  Chen Li.  Robust and adaptive composite control ofspace manipulator system with uncertain parameters , 2004 .

[5]  Tsuyoshi Murata,et al.  {m , 1934, ACML.

[6]  Wei Wang,et al.  Decentralized backstepping adaptive output tracking of large-scale stochastic nonlinear systems , 2017, Science China Information Sciences.

[7]  Yu Tang,et al.  Terminal sliding mode control for rigid robots , 1998, Autom..

[8]  L X Wang,et al.  Fuzzy basis functions, universal approximation, and orthogonal least-squares learning , 1992, IEEE Trans. Neural Networks.

[9]  Qiang Wen-yi,et al.  Study on Neural Network Adaptive Control Method for Uncertain Space Manipulator , 2010 .

[10]  Yuanqing Xia,et al.  Attitude stabilization of rigid spacecraft with finite‐time convergence , 2011 .

[11]  Wei Lin,et al.  Global finite-time stabilization of a class of uncertain nonlinear systems , 2005, Autom..

[12]  Wei Lin,et al.  Non-Lipschitz continuous stabilizers for nonlinear systems with uncontrollable unstable linearization , 2001 .

[13]  G. G. Stokes.  "J." , 1890, The New Yale Book of Quotations.

[14]  Eugene P. Ryan,et al.  Tracking with Prescribed Transient Behavior for Nonlinear Systems of Known Relative Degree , 2007, SIAM J. Control. Optim..

[15]  Xin Chen,et al.  Adaptive Tracking Control for A Class of Nonlinear Systems With a Fuzzy Dead-Zone Input , 2015, IEEE Transactions on Fuzzy Systems.

[16]  Jun Fu,et al.  Global finite-time stabilisation of a class of switched nonlinear systems , 2015, Int. J. Syst. Sci..

[17]  Eugene P. Ryan,et al.  Tracking control with prescribed transient behaviour for systems of known relative degree , 2006, Syst. Control. Lett..

[18]  M. MendelJ.,et al.  Fuzzy basis functions , 1995 .

[19]  Safi Eldeen,et al.  Etc. , 2020, Journal of Christian nursing : a quarterly publication of Nurses Christian Fellowship.