Adaptive Nonlinear Model Predictive Control Design of a Flexible-Link Manipulator with Uncertain Parameters 
  
作者Fabian Schnelle;  Peter Eberhard
期刊名称Acta Mechanica Sinica
2017
摘要This paper presents a novel adaptive nonlinear model predictive control design for trajectory tracking of flexible-link manipulators consisting of feedback linearization, linear model predictive control and Unscented Kalman Filtering. Reducing the nonlinear system to a linear system by feedback linearization simplifies the optimization problem of the model predictive controller significantly, which however is no longer linear in the presence of parameter uncertainties and can potentially lead to an undesired dynamical behaviour. An Unscented Kalman Filter is used to approximate the dynamics of the prediction model by an online parameter estimation, which leads to an adaptation of the optimization problem in each time step and thus, to a better prediction and an improved input action. Finally, a detailed fuzzy-arithmetical analysis is performed in order to quantify the e ect of the uncertainties on the control structure and to derive robustness assessments. The control structure is applied to a serial manipulator with two flexible links containing uncertain model parameters and acting in threedimensional space.
关键词Model predictive control;  feedback linearization; Unscented Kalman Filter;  flexible-link manipulator; fuzzy-arithmetical analysis
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