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Disturbance attenuation and rejection for systems with nonlinearity via DOBC approach. (English) Zbl 1078.93030
Summary: In this paper the disturbance attenuation and rejection problem is investigated for a class of MIMO nonlinear systems in the disturbance-observer-based control (DOBC) framework. The unknown external disturbances are supposed to be generated by an exogenous system, where some classic assumptions on disturbances can be removed. Two kinds of nonlinear dynamics in the plants are considered, respectively, which correspond to the known and unknown functions. Design schemes are presented for both the full-order and reduced-order disturbance observers via LMI-based algorithms. For the plants with known nonlinearity it is shown that the full-order observer can be constructed by augmenting the estimation of disturbances into the full-state estimation, and the reduced-order ones can be designed by using of the separation principle. For the uncertain nonlinearity, the problem can be reduced to a robust observer design problem. By integrating the disturbance observers with conventional control laws, the disturbances can be rejected and the desired dynamic performances can be guaranteed. If the disturbance also has perturbations, it is shown that the proposed approaches are infeasible and further research is required in the future. Finally, simulations for a flight control system is given to demonstrate the effectiveness of the results.

MSC:
93B51 Design techniques (robust design, computer-aided design, etc.)
93C73 Perturbations in control/observation systems
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References:
[1] H? Optimal Control and Related Minimax Design Problems. Birkhauser: Boston, 1995.
[2] Nonlinear Control Systems. Springer: Berlin, 1995.
[3] Stabilisation of Nonlinear Uncertain Systems. Springer: Berlin, 1998.
[4] Nonlinear Control Design: Geometric, Adaptive and Robust. Prentice-Hall: Englewood Cliffs, NJ, 1995. · Zbl 0833.93003
[5] Nonlinear Dynamical Control Systems (3rd edn). Springer: Berlin, 1996.
[6] Applied Nonlinear Control. Prentice-Hall: Englewood Cliffs, NJ, 1991.
[7] Nakao, Proceedings of the IEEE International Conference on Robotics and Automation pp 326– (1987)
[8] Li, International Journal of Control 58 pp 537– (1993)
[9] Chan, IEEE Transactions on Industrial Electronics 42 pp 487– (1995)
[10] Robust learning control for robot manipulators based on disturbance observer. Proceedings of IEEE IEC’96, 1996; 1276-1282.
[11] Bickel, ASME Journal of Dynamic Systems, Control and Measurement 121 pp 41– (1999)
[12] Oh, IEEE/ASME Transactions on Mechatronics 4 pp 133– (1999)
[13] DOB control for dynamic nonlinear systems with disturbances: a survey and comparisons. Proceedings of CACSCUK’01, Nottingham, U.K., 2001; 105-110.
[14] Chen, IEEE Transactions on Industrial Electronics 47 pp 932– (2000)
[15] Chen, ASME Journal of Dynamic Systems, Control and Measurement 125 pp 114– (2003)
[16] Chen, Journal of Guidance, Control and Dynamics 26 pp 161– (2003)
[17] Nonlinear PID predictive control of two-link robotic manipulators. Proceedings of the IFAC Symposium on Robot Control, Vienna, Austria, 2000; 217-222.
[18] Zheng, IEEE Transactions on Automatic Control 45 pp 1997– (2000)
[19] Guo, IEE Proceedings Part D: Control Theory Application 149 pp 226– (2002)
[20] Petersen, Automatica 22 pp 397– (1986)
[21] Aircraft Dynamics and Automatic Control. Princeton University Press: Princeton, 1976.
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