期刊
IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS
卷 54, 期 1, 页码 764-786出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TIA.2017.2763584
关键词
Feedback linearization; H(infinity)control; Lyapunov stability; nonlinear disturbance observer (NDO); permanentmagnet linear synchronous motor (PMLSM); self-organizing recurrent wavelet neural network; XY table
This paper proposes an adaptive nonlinear disturbance observer (ANDO) for identification and control of a two-axis motion control system driven by two permanent-magnet linear synchronous motors servo drives. The proposed control scheme incorporates a feedback linearization controller (FLC), a new double-loop self-organizing recurrentwavelet neural network (DL-SORWNN) controller, a robust controller, and an H-infinity controller. First, an FLC is designed to stabilize the XY table system. Then, a nonlinear disturbance observer (NDO) is designed to estimate the nonlinear lumped parameter uncertainties that include the external disturbances, cross-coupled interference, and frictional force. However, the XY table performance is degraded by the NDO error due to parameter uncertainties. To improve the robustness, the ANDO is designed to attain this purpose. In addition, the robust controller is designed to recover the approximation error of the DLSORWNN, while the H-infinity controller is specified such that the quadratic cost function is minimized and the worst-case effect of the NDO error must be attenuated below a desired attenuation level. The online adaptive control laws are derived using the Lyapunov stability analysis and H-infinity control theory, so that the stability of the ANDO can be guaranteed. The experimental results show the improvements in disturbance suppression and parameter uncertainties, which illustrate the superiority of the ANDO control scheme.
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