A globally uniformly ultimately bounded adaptive robust control approach to a second-order nonlinear motion system with input saturation

Yun Hong, Purdue University

Abstract

Control input saturation is an important practical problem to control engineers. This research focuses on the synthesis of nonlinear adaptive robust controller with saturated actuator authority for a linear motor drive system, which is subject to parametric uncertainties and uncertain nonlinearities such as input disturbance as well. Globally uniformly ultimately bounded (GUUB) stability with limited control efforts is achieved by breaking down the overall uncertainties to state-linearly-dependent uncertainties (such as viscous friction) and bounded nonlinearities (such as coulomb friction, cogging force and etc.) and treating them with different strategies. Furthermore, a guaranteed transient performance and final tracking accuracy can be obtained by incorporating the well-developed adaptive robust control strategy and effective parameter identifier. Asymptotic output tracking is also achieved in the presence of parametric uncertainties only. Meanwhile, in contrast to the existing saturated control structures that are designed based on a set of transformed coordinates, the proposed saturated controller is carried out in the actual system states, which have clear physical meanings. This makes it much easier and less conservative to select the design parameters to meet the dual objective of achieving GUUB stability with limited control efforts for rare emergency cases and the local high-bandwidth control for high performance under normal running conditions. The proposed control strategy is designed under the assumption that the moving mass is known and then extended to the case where the moving mass is unknown and online estimated. Real-time experimental results are obtained to illustrate the effectiveness of the saturated adaptive robust control law.^ The other focus of this work is on the dynamic friction compensation. Micro and nano-technologies need precision machines that can produce motion accuracy down to nano-meter range. The objective of this research is to present an advanced adaptive robust control approach with dynamic friction compensation to achieve nanometer level positioning accuracy for nano-manipulation type applications. In addition, the proposed control strategy is applied on a linear motor drive system with a position measurement resolution less than 1 nanometer. Simulation results will be presented to demonstrate the ultra precision motion that can be achieved with the proposed method.^

Degree

Ph.D.

Advisors

Bin Yao, Purdue University.

Subject Area

Engineering, Mechanical

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