Search results for "linearization"
showing 10 items of 115 documents
Li-ion Battery Modeling and State of Charge Estimation Method Including the Hysteresis Effect
2019
In this paper, a new approach to modeling the hysteresis phenomenon of the open circuit voltage (OCV) of lithium-ion batteries and estimating the battery state of charge (SoC) is presented. A characterization procedure is proposed to identify the battery model parameters, in particular, those related to the hysteresis phenomenon and the transition between charging and discharging conditions. A linearization method is used to obtain a suitable trade-off between the model accuracy and a low computational cost, in order to allow the implementation of SoC estimation on common hardware platforms. The proposed characterization procedure and the model effectiveness for SoC estimation are experime…
Iterative closure method for non-linear systems driven by polynomials of Gaussian filtered processes
2008
This paper concerns the statistical characterization of the non-Gaussian response of non-linear systems excited by polynomial forms of filtered Gaussian processes. The non-Gaussianity requires the computation of moments of any order. The problem is solved profiting from both the stochastic equivalent linearization (EL), and the moment equation approach of Ito's stochastic differential calculus through a procedure divided into two parts. The first step requires the linearization of the system, while retaining the non-linear excitation; the response statistical moments are calculated exactly, and constitute a first estimate of the moments of the actual non-linear system. In the second step, t…
Pseudo-force method for a stochastic analysis of nonlinear systems
1996
Nonlinear systems, driven by external white noise input processes and handled by means of pseudo-force theory, are transformed through simple coordinate transformation to quasi-linear systems. By means of Itô stochastic differential calculus for parametric processes, a finite hierarchy for the moment equations of these systems can be exactly obtained. Applications of this procedure to the first-order differential equation with cubic nonlinearity and to the Duffing oscillator show the versatility of the proposed method. The accuracy of the proposed procedure improves by making use of the classical equivalent linearization technique.
Linear and nonlinear approximations for periodically driven bistable systems
2005
We analyze periodically driven bistable systems by two different approaches. The first approach is a linearization of the stochastic Langevin equation of our system by the response on small external force. The second one is based on the Gaussian approximation of the kinetic equations for the cumulants. We obtain with the first approach the signal power amplification and output signal-to-noise ratio for a model piece-wise linear bistable potential and compare with the results of linear response approximation. By using the second approach to a bistable quartic potential, we obtain the set of nonlinear differential equations for the first and the second cumulants.
Symmetric identities in graded algebras
1997
Let P k be the symmetric polynomial of degree k i.e., the full linearization of the polynomial x k . Let G be a cancellation semigroup with 1 and R a G-graded ring with finite support of order n. We prove that if R 1 satisfies $ P_k \equiv 0 $ then R satisfies $ P_{kn} \equiv 0 $ .
Stochastic linearization critically re-examined
1997
Abstract The stochastic linearization technique, widely used for the analysis of nonlinear dynamic systems subjected to random excitations, is revisited. It is shown that the standard procedure universally adopted for determining the so-called effective stiffness of the equivalent linear system is erroneous in all previous publications. Two error-free stochastic linearization techniques are elucidated, namely those based on (1) the force linearization and (2) energy linearization.
Gain-scheduled H-infinity observer design for nonlinear stochastic systems with time-delay and actuator saturation
2012
In this paper, we propose a method for designing continuous gain-scheduled robust H ∞ observer on a class of extended stochastic nonlinear systems subject to time delay and actuator saturation. Initially, gradient linearization procedure is applied to describe such extended nonlinear systems into several model-based linear systems. Next, a robust linear H ∞ observer is designed to such linear stochastic models. Subsequently, a convex hull set is investigated and sufficient condition is derived in terms of feedback observer to determine whether a given initial condition belongs to an ellipsoid invariant set. Finally, continuous gain-scheduled approach is employed to design continuous nonline…
Development of Point-to-Point Path Control in Actuator Space for Hydraulic Knuckle Boom Crane
2020
This paper presents a novel method for point-to-point path control for a hydraulic knuckle boom crane. The developed path control algorithm differs from previous solutions by operating in the actuator space instead of the joint space or Cartesian space of the crane. By operating in actuator space, almost all the parameters and constraints of the system become either linear or constant, which greatly reduces the complexity of both the control algorithm and path generator. For a given starting point and endpoint, the motion for each actuator is minimized compared to other methods. This ensures that any change in direction of motion is avoided, thereby greatly minimizing fatigue, jerky motion,…
A subtle error in conventional stochastic linearization techniques
1998
Abstract The stochastic linearization technique as applied to the SDOF system is re-examined. Two standard procedures associated with the stochastic linearization, widely adopted in the literature, are shown to be erroneous. Two new procedures to correct the errors made in previous works are introduced. To gain more insight, the procedures are applied to the quintic oscillator. Comparative numerical analysis is performed.
Stochastic linearization of MDOF systems under parametric excitations
1992
Abstract The stochastic linearization approach is examined for non-linear systems subjected to parametric type excitations. It is shown that, for these systems too, stochastic linearization and Gaussian closure are two equivalent approaches if the former is applied to the coefficients of the Ito differential rule. A critical review of other stochastic linearization approaches is also presented and discussed by means of simple examples.