Model-based optimization methods suffer from the limited accuracy of the available process models. Because of plant-model mismatch, model-based optimal inputs may be suboptimal or, worse, unfeasible for the plant. Modifier ...

This paper presents an overview of the recent developments of modifier-adaptation schemes for real-time optimization of uncertain processes. These schemes have the ability to reach plant optimality upon convergence despite ...

As a real-time optimization technique, modifier adaptation (MA) has gained much significance in recent years. This is mainly due to the fact that MA can deal explicitly with structural plant-model mismatch and unknown ...

Climate change can disrupt mutualisms by causing temporal or spatial mismatch between interacting species. However, the effects of climate change forecasts on biotic interactions remain poorly studied. In cactus species, ...

In the presence of plant-model mismatch, the estimation of plant gradients is key to the performance of measurement-based iterative optimization schemes. However, gradient estimation requires time-consuming experiments, ...

Modifier adaptation is a real-time optimization (RTO) methodology that uses plant gradient estimates to correct model gradients, thereby driving the plant to optimality. However, obtaining accurate gradient estimates ...

Animal-plant interactions are threatened by ongoing climate change, deforestation, and defaunation. The disruption of biotic interactions leads to loss of ecosystem services but estimates of the magnitude of reductions are ...

North western Argentina, the southernmost portion of the tropical Andes, contains one of the main areas of endemism within the Southern Cone, as well as one of the main diversity hotspots of the country. Historically its ...

In the context of real-time optimization, modifier-adaptation schemes use estimates of the plant gradients to achieve plant optimality despite plant-model mismatch. Plant feasibility is guaranteed upon convergence, but not ...