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Abstract Aim Understanding the considerable variability and drivers of global leaf photosynthetic capacity [indicated by the maximum carboxylation rate standardized to 25°C ( V c,max25 )] is an essential step for accurate modelling of terrestrial plant photosynthesis and carbon uptake under climate change. Although current environmental conditions have often been connected with empirical and theoretical models to explain global V c,max25 variability through acclimatization and adaptation, long‐term evolutionary history has largely been neglected, but might also explicitly play a role in shaping the V c,max25 variability. Location Global. Time period Contemporary. Major taxa studied Terrestrial plants. Methods We compiled a geographically comprehensive global dataset of V c,max25 for C 3 plants ( n  = 6917 observations from 2157 species and 425 sites covering all major biomes world‐wide), explored the biogeographical and phylogenetic patterns of V c,max25 , and quantified the relative importance of current environmental factors and evolutionary history in driving global V c,max25 variability. Results We found that V c,max25 differed across different biomes, with higher mean values in relatively drier regions, and across different life‐forms, with higher mean values in non‐woody relative to woody plants and in legumes relative to non‐leguminous plants. The values of V c,max25 displayed a significant phylogenetic signal and diverged in a contrasting manner across phylogenetic groups, with a significant trend along the evolutionary axis towards a higher V c,max25 in more modern clades. A Bayesian phylogenetic linear mixed model revealed that evolutionary history (indicated by phylogeny and species) explained nearly 3‐fold more of the variation in global V c,max25 than present‐day environment (53 vs. 18%). Main conclusions These findings contribute to a comprehensive assessment of the patterns and drivers of global V c,max25 variability, highlighting the importance of evolutionary history in driving global V c,max25 variability, hence terrestrial plant photosynthesis. 

In this paper, a model predictive current controller (MPCC) is proposed for short-pitched mutually coupled switched reluctance machines (MCSRMs) using a three-phase voltage source converter (VSC) to achieve fast dynamics and advanced current tracking ability. Due to strong mutually coupling between phases, to our knowledge, MPCC for MCSRMs has not been studied yet. A two-order flux-based prediction model of the MCSRMs using the VSC is presented with standard state space equations in discrete-time domain, based on which, the current regulation is achieved by solving a constrained optimization problem. With the receding optimal duty ratio input, MPCC demonstrates good current tracking ability, which is verified by simulations with a three-phase, sinusoidal excitation 12/8 MCSRM. Compared to hysteresis current control, the current response with MPCC bears lower current ripples and a fixed switching frequency.