1,721,244 research outputs found
Robust moving horizon estimation for nonlinear systems: From perfect to imperfect optimization
No full textThis paper examines the robust stability of moving-horizon estimators for nonlinear discrete-time systems that are detectable in the sense of incremental input/output-to-state stability and are affected by disturbances. The estimate of a moving-horizon estimator is derived from the on-line solution of a least-squares minimization problem at each time instant. The resulting stability guarantees depend on the optimization tolerance in solving these minimization problems. Specifically, two main contributions are established: (i) the robust stability of the estimation error, assuming the on-line minimization problem is solved exactly; (ii) the practical robust stability of the estimation error with state estimates obtained through imperfect minimization. Finally, the construction of such robust moving-horizon estimators and the performance resulting from the design based on the theoretical findings are showcased with two numerical examples. (c) 2025 Published by Elsevier Ltd
Improvement of grand multi-model ensemble prediction skills for the coupled models of APCC/ENSEMBLES using a climate filter
No full textTwelve coupled model simulations of two multi-model ensemble (MME) systems for boreal winters from 1983 to 2005 are used to improve the climate prediction. From grading the relative capability of each simulation in reproducing the observed link between the tropical El Niño-Southern Oscillation (ENSO)-related Walker circulation and the Pacific rainfall, we find an optimal MME suite with improved prediction skills. This study demonstrates that the climate filter concept, proposed by us in a recent work, is not only useful in improving the MME prediction skills as compared to a single MME system, but also the skills of a grand MME that encompasses two well-performing MMEs. © 2013 Royal Meteorological Society
Long-term climate change in the Mediterranean region in the midst of decadal variability
No full textLong-term climate change and decadal variability in the Mediterranean region during 1860–2100 are investigated based on observational data and the newly available Coupled Model Intercomparison Project—Phase 5 (CMIP5) experiments. Observational records show that decadal variability and a general tendency for annual-mean conditions to be warmer and drier have characterized the Mediterranean during 1860–2005. Consistency with CMIP5 model simulations including greenhouse gases (GHG), as well as anthropogenic aerosols and natural forcings, suggest that forced changes have characterized aspects of Mediterranean climate during this period. Future GHG-forced change will take place in the midst of decadal variability, both internal and forced, as it has occurred in the past. However, future rates of forced warming and drying over the Mediterranean are projected to be higher than in the past century. The degree to which forced change and internal variability will matter depends on the climatic quantity being considered. For surface air temperature and Mediterranean Sea annual-mean evaporation and surface freshwater fluxes, variability and forced change have become comparable and the forced signal has already emerged from internal variability. For quantities with large internal variability and relatively small forced signal such as precipitation, forced change will emerge later on in the twenty-first century over selected regions and seasons. Regardless, the probability distribution of future precipitation anomalies is progressively shifting towards drier conditions. Overall, results highlight that both mean projected forced change and the variability that will accompany forced mean change should be considered in the development of future climate outlooks. © 2015, Springer-Verlag (outside the USA)
On Hamilton-Jacobi Approaches to State Reconstruction for Dynamic Systems
No full textWe investigate the use of Hamilton-Jacobi approaches for the purpose of state reconstruction of dynamic systems. First, the classical formulation based on the minimization of an estimation functional is analyzed. Second, the structure of the resulting estimator is taken into account to study the global stability properties of the estimation error by relying on the notion of input-to-state stability. A condition based on the satisfaction of a Hamilton-Jacobi inequality is proposed to construct estimators with input-to-state stable dynamics of the estimation error, where the disturbances affecting such dynamics are regarded as input. Third, the so-developed general framework is applied to the special case of high-gain observers for a class of nonlinear systems
State Observers for Systems Subject to Bounded Disturbances Using Quadratic Boundedness
Full text linkQuadratic boundedness is adopted to design state observers for linear, piecewise linear, and Lipschitz nonlinear systems subject to bounded disturbances. Upper bounds on the estimation error are derived by exploiting quadratic boundedness and a design method based on linear matrix inequalities is proposed to minimize such bounds. Simulation results are provided to show the effectiveness of the proposed approach
On the coupling between vegetation and rainfall inter-annual anomalies: Possible contributions to seasonal rainfall predictability over land areas
No full textVegetation, rainfall, climateIt's well known that rainfall affects vegetation through its effect on soil moisture content, but the extent to which vegetation could in turn impact precipitation occurrence is poorly understood. Here we focus on the assessment, from observations, of the reciprocal forcing of seasonal-mean vegetation and rainfall interannual anomalies over land areas using the coupled manifold technique. Considering global lands, we estimate at the 1% significance level that 19% (12%) of the vegetation (precipitation) variance is forced by precipitation (vegetation). Our analysis reveals that the dominant component of the vegetation-forced rainfall variability is a delayed response to ENSO cycles. Vegetation appears to provide a biophysical memory of ENSO and is supposed to act through delayed feedbacks on rainfall. As ENSO cycles are currently well predicted by dynamical seasonal forecasting systems, this result displays the potential for a reliable soil moisture-vegetation initialization to improve rainfall prediction over lands
Hysteresis-based switching observers for linear systems using quadratic boundedness
No full textSwitched-gain observers are investigated for the purpose of estimating the state of linear systems affected by bounded noises. Under mild assumptions, hybrid observers with switching gains are proposed and provided with stability analysis based on quadratic boundedness for the estimation error. Such observers are designed by solving optimization problems aimed at minimizing upper bounds on the estimation error in such a way as to get the smallest invariant set. The effectiveness of the proposed approach is evaluated with some numerical case studies
Design assisted by testing: procedure for the statistical determination of a capacity model
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