2010.12.20Adaptive Fuzzy Tracking Control for a Class of Uncertain.pdf (232.93 kB)
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Adaptive fuzzy tracking control for a class of uncertain MIMO nonlinear systems using disturbance observer

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journal contribution
posted on 12.12.2012, 13:59 by Mou Chen, Wen-Hua Chen, Qing-Xian Wu
In this paper, the adaptive fuzzy tracking control is proposed for a class of multi-input and multioutput (MIMO) nonlinear systems in the presence of system uncertainties, unknown non-symmetric input saturation and external disturbances. Fuzzy logic systems (FLS) are used to approximate the system uncertainty of MIMO nonlinear systems. Then, the compound disturbance containing the approximation error and the time-varying external disturbance that cannot be directly measured are estimated via a disturbance observer. By appropriately choosing the gain matrix, the disturbance observer can approximate the compound disturbance well and the estimate error converges to a compact set. This control strategy is further extended to develop adaptive fuzzy tracking control for MIMO nonlinear systems by coping with practical issues in engineering applications, in particular unknown non-symmetric input saturation and control singularity. Within this setting, the disturbance observer technique is combined with the FLS approximation technique to compensate for the effects of unknown input saturation and control singularity. Lyapunov approach based analysis shows that semi-global uniform boundedness of the closed-loop signals is guaranteed under the proposed tracking control techniques. Numerical simulation results are presented to illustrate the effectiveness of the proposed tracking control schemes.



  • Aeronautical, Automotive, Chemical and Materials Engineering


  • Aeronautical and Automotive Engineering


CHEN, M., CHEN, W-H. and WU, Q-X., 2014. Adaptive fuzzy tracking control for a class of uncertain MIMO nonlinear systems using disturbance observer. Science China Information Sciences, 57 (1), pp 1-13.


© Science China Press and Springer-Verlag


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This article was published in the journal, Science China Information Sciences [© Science China Press and Springer-Verlag]. The definitive version is available at: http://dx.doi.org/10.1007/s11432-012-4695-3