Search results for "Linear"
showing 10 items of 7165 documents
D-stability for discrete-time t-s fuzzy descriptor systems with multiple delays
2014
In this work, the D-stability problem is considered for a class of discrete-time Takagi-Sugeno (T-S) fuzzy descriptor systems with multiple state delays. In terms of linear matrix inequality, sufficient conditions are proposed to ensure that all poles of the descriptor T-S fuzzy system are located within a disk contained in the unit circle. Moreover, a sufficient condition is presented such that the singular system is regular, causal and D-stable in spite of multiple state delays. Finally, an example is given to show the effectiveness and advantages of the proposed techniques Refereed/Peer-reviewed
Dependence of single-particle energies on coupling constants of the nuclear energy density functional
2008
We show that single-particle energies in doubly magic nuclei depend almost linearly on the coupling constants of the nuclear energy density functional. Therefore, they can be very well characterized by the linear regression coefficients, which we calculate for the coupling constants of the standard Skyrme functional. We then use these regression coefficients to refit the coupling constants to experimental values of single-particle energies. We show that the obtained rms deviations from experimental data are still quite large, of the order of 1.1 MeV. This suggests that the current standard form of the Skyrme functional cannot ensure spectroscopic-quality description of single-particle energ…
State Space-Vector Model of Linear Induction Motors Including Iron Losses Part I: Theoretical Analysis
2018
This is the first part of a paper, divided into two parts, dealing with the definition of a space-vector dynamic model of the linear Induction motor (LIM) taking into consideration both the dynamic end-effects and the iron losses and its off-line identification. This first part specifically treats the theoretical formulation of this model, which has been expressed in a state form, so to be, in perspective, suitably adopted for developing novel non linear control techniques, non-linear observers as well as electrical losses minimization techniques (ELMTs). Besides the formulation of the dynamic model in space-vector state form, a steady-state analysis is proposed, highlighting the combined e…
State Space-Vector Model of Linear Induction Motors Including Iron Losses: Part II: Model Identification and Results
2018
This is the second part of a paper, divided into two parts, dealing with the definition of a space-vector dynamic model of the linear Induction motor (LIM) taking into consideration both the dynamic end-effects and the iron losses as well as the off-line identification of its parameters. The first part has treated the theoretical framework of the model. This second part is devoted to the description of an identification technique which has been suitably developed for the estimation of the parameters of the LIM dynamic model accounting for both the dynamic end-effects and iron losses, described in the first part of the paper. Such an identification technique is strictly related to the state …
Nonlinear Complex PCA for spatio-temporal analysis of global soil moisture
2020
Soil moisture (SM) is a key state variable of the hydrological cycle, needed to monitor the effects of a changing climate on natural resources. Soil moisture is highly variable in space and time, presenting seasonalities, anomalies and long-term trends, but also, and important nonlinear behaviours. Here, we introduce a novel fast and nonlinear complex PCA method to analyze the spatio-temporal patterns of the Earth's surface SM. We use global SM estimates acquired during the period 2010-2017 by ESA's SMOS mission. Our approach unveils both time and space modes, trends and periodicities unlike standard PCA decompositions. Results show the distribution of the total SM variance among its differ…
Non-linear systems under impulsive parametric input
1999
In this paper the problem of the response of non-linear systems excited by an impulsive parametric input is treated. For such systems the response exhibits a jump depending on the amplitude of the impulse as well as on the value of the state variables immediately before the impulse occurrence. Recently, the jump prediction has been obtained in a series form. Here the incremental rule for any scalar real valued function is obtained in an analytical form involving the jump of the state variables. It is also shown that the formulation for the jump evaluation is also able to give a new step-by-step integration technique.
A comparison of simplex and simulated annealing for optimization of a new rear underrun protective device
2012
In this paper, two optimization approaches to improve the product design process have been analysed. Through the analysis of a case study, concerning the designing of a new High Energy Absorption Rear Underrun Protective Device (HEARUPD), two different optimization approaches (simplex and simulated annealing) have been compared. In the implemented optimization processes, the crash between an economy car and the rear part of a truck has been simulated by dynamic numerical (FEM) analyses. Moreover, authors have proposed the use of a suitable linear function of four variables with the purpose of reducing the multi-objective optimization processes to mono-objective ones. That has been made to s…
State Estimation of a Nonlinear Unmanned Aerial Vehicle Model using an Extended Kalman Filter
2008
An Extended Kalman Filter is designed in order to estimate both state variables and wind velocity vector at the same time for a non conventional unmanned aircraft. The proposed observer uses few measurements, obtained by means of either conventional simple air data sensors or a low cost GPS. To cope with the low rate of the GPS with respect to the other sensors, the EKF algorithm has been modified to allow for a dual rate measurement model. State propagation is obtained by means of an accurate six degrees of freedom nonlinear model of the aircraft dynamics. To obtain joint estimation of state and disturbance, wind velocity components are included in the set of the state variables. Both stoc…
Descriptor-type Kalman Filter and TLS EXIN Speed Estimate for Sensorless Control of a Linear Induction Motor.
2014
This paper proposes a speed observer for linear induction motors (LIMs), which is composed of two parts: 1) a linear Kalman filter (KF) for the online estimation of the inductor currents and induced part flux linkage components; and 2) a speed estimator based on the total least squares (TLS) EXIN neuron. The TLS estimator receives as inputs the state variables, estimated by the KF, and provides as output the LIM linear speed, which is fed back to the KF and the control system. The KF is based on the classic space-vector model of the rotating induction machine. The end effects of the LIMs have been considered an uncertainty treated by the KF. The TLS EXIN neuron has been used to compute, in …
Dynamical attractors of memristors and their networks
2018
It is shown that the time-averaged dynamics of memristors and their networks periodically driven by alternating-polarity pulses may converge to fixed-point attractors. Starting with a general memristive system model, we derive basic equations describing the fixed-point attractors and investigate attractors in the dynamics of ideal, threshold-type and second-order memristors, and memristive networks. A memristor potential function is introduced, and it is shown that in some cases the attractor identification problem can be mapped to the problem of potential function minimization. Importantly, the fixed-point attractors may only exist if the function describing the internal state dynamics dep…