This brief addresses the model-based control of the air path of diesel engines in terms of an optimal control problem with input constraints which can be solved using model predictive algorithms. A multilinear model identified from data and a switched controller design are used to cope with the nonlinearity of the engine. Experimental results on a production engine confirm that the proposed control method strongly improves the dynamics of the air path and enormously reduces the parameterization work if compared with the conventional approach. To obtain improvements in emissions as well, the new controller approach cannot simply be plugged in at the site of the conventional one, but new set points must be determined. After such a redesign, improvements of 50% in terms of nitrogen oxides and of 10% in terms of particulate matter have been recorded without a net consumption increase, the main price being the increased activity of the turbocharger vane and especially of the exhaust gas recirculation valve.

High-quality performance of medical devices for glucose monitoring is important for a safe and efficient usage of this diagnostic option by patients with diabetes. The mean absolute relative difference (MARD) parameter is used most often to characterize the measurement performance of systems for continuous glucose monitoring (CGM). Calculation of this parameter is relatively easy and comparison of the MARD numbers between different CGM systems appears to be straightforward on the first glance. However, a closer look reveals that a number of complex aspects make interpretation of the MARD numbers provided by the manufacturer for their CGM systems difficult. In this review, these aspects are discussed and considerations are made for a systematic and appropriate evaluation of the MARD in clinical trials. The MARD should not be used as the sole parameter to characterize CGM systems, especially when it comes to nonadjunctive usage of such systems.

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MARD values from clinical studies should not be used blindly but the reliability of the evaluation should be considered as well. Furthermore, it should not be ignored that MARD does not take into account the key feature of CGM sensors, the frequency of the measurements. Additional metrics, such as precision absolute relative difference (PARD) should be used as well to obtain a better evaluation of the CGM performance for specific uses, for example, for artificial pancreas.

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