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Robustified control of a multivariable robot

Abstract : This paper presents the application of several advanced control techniques to a nonlinear strongly coupled multivariable robot. The main difficulties come from the flexibility of the mechanical chain, but also from the lack of joints sensors. In a first stage, a state-feedback linear quadratic (LQG) technique and a model predictive control (MPC) are designed using optimal observers. Considering additional sensors that provide measurements of accelerations increases the robustness of the controlled system. The second stage consists into adding a supplementary robustness layer (i.e. explicitly considering the robust stability under unstructured uncertainties) on the stabilizing MPC developed at the previous stage. Comparative results are proposed highlighting the trade-off between robust stability and nominal performance for disturbances rejection.
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Emanuel Dogaru, Cristina Stoica, Emmanuel Godoy. Robustified control of a multivariable robot. 8th International Conference on Informatics in Control, Automation and Robotics (ICINCO), Jul 2011, Noordwijkerhout, Netherlands. 10 p. ⟨hal-00593043⟩

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