LQ optimal and risk-sensitive control for vehicle suspensions

This paper is concerned with time-domain optimal control of active suspensions. The optimal control problem formulation has been generalised by incorporating both road disturbances (ride quality) and a representation of driver inputs (handling quality) into the optimal control formulation. A regular optimal control problem as well as a risk-sensitive exponential optimal control performance index is considered. Emphasis has been given to practical considerations including the issue of state estimation in the presence of load disturbances (driver inputs). © 2012 IEEE.

RNA processing and Arabidopsis flowering time control.

Plants control their flowering time in order to ensure that they reproduce under favourable conditions. The components involved in this complex process have been identified using a molecular genetic approach in Arabidopsis and classified into genetically separable pathways. The autonomous pathway controls the level of mRNA encoding a floral repressor, FLC, and comprises three RNA-binding proteins, FCA, FPA and FLK. FCA interacts with the 3'-end RNA-processing factor FY to autoregulate its own expression post-transcriptionally and to control FLC. Other components of the autonomous pathway, FVE and FLD, regulate FLC epigenetically. This combination of epigenetic and post-transcriptional control gives precision to the control of FLC expression and flowering time.

Coupling model uncertainty for coupled rainfall/runoff and surface water quality models in river problems

Coupled hydrology and water quality models are an important tool today, used in the understanding and management of surface water and watershed areas. Such problems are generally subject to substantial uncertainty in parameters, process understanding, and data. Component models, drawing on different data, concepts, and structures, are affected differently by each of these uncertain elements. This paper proposes a framework wherein the response of component models to their respective uncertain elements can be quantified and assessed, using a hydrological model and water quality model as two exemplars. The resulting assessments can be used to identify model coupling strategies that permit more appropriate use and calibration of individual models, and a better overall coupled model response. One key finding was that an approximate balance of water quality and hydrological model responses can be obtained using both the QUAL2E and Mike11 water quality models. The balance point, however, does not support a particularly narrow surface response (or stringent calibration criteria) with respect to the water quality calibration data, at least in the case examined here. Additionally, it is clear from the results presented that the structural source of uncertainty is at least as significant as parameter-based uncertainties in areal models. © 2012 John Wiley & Sons, Ltd.