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The performance of model-based bioprocess optimizations depends on the accuracy of the mathematical model. However, models of bioprocesses often have large uncertainty due to the lack of model identifiability. In the presence of such uncertainty, process optimizations that rely on the predictions of a single “best fit” model, e.g. the model resulting from a maximum likelihood parameter estimation...
In this paper, a robust fault detection filter design method for uncertain systems in linear fractional transformation (LFT) formulation with unknown inputs is proposed. The basic idea is to convert the complicated ℋ-/ℋ∞ problem to an easier ℋ∞ model following problem. Moreover, two major improvements have been made in this research. First, the uncertain systems in LFT formulation are studied. This...
This paper focuses on the design of a gripper that can grasp objects with shape, size and pose uncertainty. Rather than a dexterous hand with multiple actuators and sensors, a passively adaptive gripper made of soft material can conform to various objects by using compliance. In this paper, we present a novel design methodology for a passively adaptive gripper by employing a level-set-based topology...
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