1,720,984 research outputs found
A multi-model structure for model predictive control
No full textAbstract Model predictive control (MPC) is a wide popular control technique that can be applied starting from several model structures. In this paper black-box models are considered. In particular it is analysed the sets of regressors that it is better to use in order to obtain the best model for multi-step prediction. It is observed that for each prediction a different set of real data output and predicted output are available. Based on this observation a multi-model structure is proposed in order to improve the predictions needed in the computation of the MPC control law. A comparison with a classical one-model structure is discussed. A simulation experiment is presented
Twist Bike Atlantic ® - A New Biomechanical Efficiency Challenge
No full textTwist Bike Atlantic is a innovative bicycle with a new propulsion system in which the pedals run on a rectilinear trajectory very similar to a step movement.
The aim of this study was to examine differences in cycling efficiency between a traditional bike (B) and a Twist Bike (TB)
Artificial pancreas: Model predictive control design from clinical experience
No full textBackground:
The objective of this research is to develop a new artificial pancreas that takes into account the experience accumulated during more than 5000 h of closed-loop control in several clinical research centers. The main objective is to reduce the mean glucose value without exacerbating hypo phenomena. Controller design and in silico testing were performed on a new virtual population of the University of Virginia/Padova simulator.
Methods:
A new sensor model was developed based on the Comparison of Two Artificial Pancreas Systems for Closed- Loop Blood Glucose Control versus Open-Loop Control in Patients with Type 1 Diabetes trial AP@home data. The Kalman filter incorporated in the controller has been tuned using plasma and pump insulin as well as plasma and continuous glucose monitoring measures collected in clinical research centers. New constraints describing clinical knowledge not incorporated in the simulator but very critical in real patients (e.g., pump shutoff) have been introduced. The proposed model predictive control (MPC) is characterized by a low computational burden and memory requirements, and it is ready for an embedded implementation.
Results:
The new MPC was tested with an intensive simulation study on the University of Virginia/Padova simulator equipped with a new virtual population. It was also used in some preliminary outpatient pilot trials. The obtained results are very promising in terms of mean glucose and number of patients in the critical zone of the control variability grid analysis.
Conclusions:
The proposed MPC improves on the performance of a previous controller already tested in several experiments in the AP@home and JDRF projects. This algorithm complemented with a safety supervision module is a significant step toward deploying artificial pancreases into outpatient environments for extended periods of time
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