11 [1] In this study, we investigate the significance of using an 12 improved error modeling strategy to characterize the spatio13 temporal characteristics of uncertainty in simulation of soil 14 moisture fields from an off-line land surface model forced 15 with satellite rainfall data. We coupled a Two-Dimensional 16 Satellite Rainfall Error Model (SREM2D) with the Common 17 Land Model to prop...

Particle size distribution (PSD) affects properties of particulate materials and is used for denoting their quality and performance. Among many techniques available to measure PSD, many are quite often offline methods and are time consuming. Also methods like sieving involve, handling of the material physically and electromagnetically, which is healthy, if avoided for certain materials. Thus th...

In this paper, we employ the reduced basis method as a surrogate model for the solution of linear-quadratic optimal control problems governed by parametrized elliptic partial differential equations. We present a posteriori error estimation and dual procedures that provide rigorous bounds for the error in several quantities of interest: the optimal control, the cost functional, and general linea...

The objective of this study is to present an offline control of highly non-linear inverted pendulum system moving on a plane inclined at an angle of 10° from horizontal. The stabilisation was achieved using three different soft-computing control techniques i.e. Proportional-integral-derivative (PID), Fuzzy logic and Adaptive neuro fuzzy inference system (ANFIS). A Matlab-Simulink model of the p...

We present a new approach to treat nonlinear operators in reduced basis approximations of parametrized evolution equations. Our approach is based on empirical interpolation of nonlinear differential operators and their Frechet derivatives. Efficient offline/online decomposition is obtained for discrete operators that allow an efficient evaluation for a certain set of interpolation functionals. ...

We use asymptotically optimal adaptive numerical methods (here specifically a wavelet scheme) for snapshot computations within the offline phase of the Reduced Basis Method (RBM). The resulting discretizations for each snapshot (i.e., parameter-dependent) do not permit the standard RB ‘truth space’, but allow for error estimation of the RB approximation with respect to the exact solution of the...

We consider the efficient and reliable solution of linear-quadratic optimal control problems governed by parametrized parabolic partial differential equations. To this end, we employ the reduced basis method as a low-dimensional surrogate model to solve the optimal control problem and develop a posteriori error estimation procedures that provide rigorous bounds for the error in the optimal cont...

In this paper we consider (hierarchical, Lagrange) reduced basis approximation and a posteriori error estimation for potential flows in affinely parametrized geometries. We review the essential ingredients: i) a Galerkin projection onto a lowdimensional space associated with a smooth “parametric manifold” in order to get a dimension reduction; ii) an efficient and effective greedy sampling meth...

This paper presents an online self-evolving fuzzy controller with global learning capabilities. Starting from very simple or even empty configurations, the controller learns from its own actions while controlling the plant. It applies learning techniques based on the input/output data collected during normal operation to modify online the fuzzy controller’s structure and parameters. The control...

We discuss the design of a novel analog checker that monitors two duplicate signals and provides a digital error indication when their absolute difference is unacceptably large. The key feature of the proposed checker is that it establishes a test criterion that is dynamically adapted to the magnitude of its input signals, thus enhancing the accuracy of assessing their relative discrepancy. Con...