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Robust Nonlinear Model Predictive trajectory free control of biped robots based on nonlinear disturbance observer

Mohsen Parsa, Mohammad Farrokhi

Year
2010
Citations
13

Abstract

This paper employs nonlinear disturbance observer for robust Nonlinear Model Predictive Control (NMPC) of biped robots. The NMPC is used in order to imitate some properties of human walking, which is optimal and uses some basic goals and constraints, yielding safe and stable walking. Since there may be some uncertainties in the dynamics or parameters variations in the biped model, the controller robustness is also considered. However, the NMPC is a model based controller; this characteristic reduces the effectiveness of the NMPC based controlling. In order to overcome this shortcoming of the NMPC, the nonlinear disturbance observer (NDO) will be used to robustify the proposed controller against dynamic uncertainties in the biped robot and rejecting external disturbances. Simulation results reveal better performance of the nonlinear-disturbance-observer-based NMPC as compared to the previously reported NMPC controllers.

Keywords

Control theory (sociology)Robustness (evolution)Nonlinear systemModel predictive controlComputer scienceTrajectoryNonlinear modelRobotController (irrigation)Robust control

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