No abstract

This paper presents a modified strong tracking unscented Kalman filter (MSTUKF) to address the performance degradation and divergence of the unscented Kalman filter because of process model uncertainty. The MSTUKF adopts the hypothesis testing method to identify process model uncertainty and further introduces a defined suboptimal fading factor into the prediction covariance to decrease the weight of the prior knowledge on filtering solution. The MSTUKF not only corrects the state estimation in the occurrence of process model uncertainty but also avoids the loss of precision for the state estimation in the absence of process model uncertainty. Further, it does not require the cumbersome evaluation of Jacobian matrix involved in the calculation of the suboptimal fading factor. Experimental results and comparison analysis demonstrate the effectiveness of the proposed MSTUKF.

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Shape memory alloy (SMA) actuators have drawn much attention and interest due to their unique and superior properties, and are expected to be equipped in many modern vehicles at competitive market prices. The key advantage is that SMA actuators do not require bulky and complicated mechanical design to function, where the active element (e.g. SMA wire or spring) can be deformed by applying minimal external force and will retain to their previous form when subjected to certain stimuli such as thermomechanical or magnetic changes. This paper describes the SMA attributes that make them ideally suited as actuators in automotive applications and to address their limitations, feasibilities and prospects.