41,580 research outputs found
Nonlinear system-identification of the filling phase of a wet-clutch system
The work presented illustrates how the choice of input perturbation signal and experimental design improves the derived model of a nonlinear system, in particular the dynamics of a wet-clutch system. The relationship between the applied input current signal and resulting output pressure in the filling phase of the clutch is established based on bandlimited periodic signals applied at different current operating points and signals approximating the desired filling current signal. A polynomial nonlinear state space model is estimated and validated over a range of measurements and yields better fits over a linear model, while the performance of either model depends on the perturbation signal used for model estimation
Design of ternary signals for MIMO identification in the presence of noise and nonlinear distortion
A new approach to designing sets of ternary periodic signals with different periods for multi-input multi-output system identification is described. The signals are pseudo-random signals with uniform nonzero harmonics, generated from Galois field GF(q), where q is a prime or a power of a prime. The signals are designed to be uncorrelated, so that effects of different inputs can be easily decoupled. However, correlated harmonics can be included if necessary, for applications in the identification of ill-conditioned processes. A design table is given for q les 31. An example is presented for the design of five uncorrelated signals with a common period N = 168 . Three of these signals are applied to identify the transfer function matrix as well as the singular values of a simulated distillation column. Results obtained are compared with those achieved using two alternative methods
Vibration-based methods for structural and machinery fault diagnosis based on nonlinear dynamics tools
This study explains and demonstrates the utilisation of different nonlinear-dynamics-based procedures for the purposes of structural health monitoring as well as for monitoring of robot joints
Comparison of the magneto-Peltier and magneto-Seebeck effects in magnetic tunnel junctions
Understanding heat generation and transport processes in a magnetic tunnel
junction (MTJ) is a significant step towards improving its application in
current memory devices. Recent work has experimentally demonstrated the
magneto-Seebeck effect in MTJs, where the Seebeck coefficient of the junction
varies as the magnetic configuration changes from a parallel (P) to an
anti-parallel (AP) configuration. Here we report the study on its
as-yet-unexplored reciprocal effect, the magneto-Peltier effect, where the heat
flow carried by the tunneling electrons is altered by changing the magnetic
configuration of the MTJ. The magneto-Peltier signal that reflects the change
in the temperature difference across the junction between the P and AP
configurations scales linearly with the applied current in the small bias but
is greatly enhanced in the large bias regime, due to higher-order Joule heating
mechanisms. By carefully extracting the linear response which reflects the
magneto-Peltier effect, and comparing it with the magneto-Seebeck measurements
performed on the same device, we observe results consistent with Onsager
reciprocity. We estimate a magneto-Peltier coefficient of 13.4 mV in the linear
regime using a three-dimensional thermoelectric model. Our result opens up the
possibility of programmable thermoelectric devices based on the Peltier effect
in MTJs
Modeling the pulse signal by wave-shape function and analyzing by synchrosqueezing transform
We apply the recently developed adaptive non-harmonic model based on the
wave-shape function, as well as the time-frequency analysis tool called
synchrosqueezing transform (SST) to model and analyze oscillatory physiological
signals. To demonstrate how the model and algorithm work, we apply them to
study the pulse wave signal. By extracting features called the spectral pulse
signature, {and} based on functional regression, we characterize the
hemodynamics from the radial pulse wave signals recorded by the
sphygmomanometer. Analysis results suggest the potential of the proposed signal
processing approach to extract health-related hemodynamics features
Fast Adaptive Robust Differentiator Based Robust-Adaptive Control of Grid-Tied Inverters with a New L Filter Design Method
In this research, a new nonlinear and adaptive state feedback controller with a fast-adaptive robust differentiator is presented for grid-tied inverters. All parameters and external disturbances are taken as uncertain in the design of the proposed controller without the disadvantages of singularity and over-parameterization. A robust differentiator based on the second order sliding mode is also developed with a fast-adaptive structure to be able to consider the time derivative of the virtual control input. Unlike the conventional backstepping, the proposed differentiator overcomes the problem of explosion of complexity. In the closed-loop control system, the three phase source currents and direct current (DC) bus voltage are assumed to be available for feedback. Using the Lyapunov stability theory, it is proven that the overall control system has the global asymptotic stability. In addition, a new simple L filter design method based on the total harmonic distortion approach is also proposed. Simulations and experimental results show that the proposed controller assurances drive the tracking errors to zero with better performance, and it is robust against all uncertainties. Moreover, the proposed L filter design method matches the total harmonic distortion (THD) aim in the design with the experimental result
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