scholarly journals A High-Order Load Model and the Control Algorithm for an Aerospace Electro-Hydraulic Actuator

Actuators ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 53
Author(s):  
Shoujun Zhao ◽  
Keqin Chen ◽  
Xiaosha Zhang ◽  
Yingxin Zhao ◽  
Guanghui Jing ◽  
...  
Keyword(s):  
Transfer Function ◽  
Fourth Order ◽  
Dynamic Pressure ◽  
Resonance Effect ◽  
Notch Filter ◽  
High Order ◽  
Model Parameters ◽  
Hydraulic Actuator ◽  
Control Block ◽  
Load Model

It is difficult to describe precisely, and thus control satisfactorily, the dynamics of an electro-hydraulic actuator to drive a high thrust liquid launcher engine, whose structural resonant frequency is usually low due to its heavy inertia and complicated mass distribution, let alone one to drive a heavy kerolox engine with high-order dynamics. By transforming classic control block diagrams, a baseline two-mass-two-spring load model and a normalized actuator-engine system model were developed for understanding the basic physics and methodology, where a fourth-order transfer function is used to model the multi-resonance-frequency engine body outside of the rod position loop, another fourth-order transfer function with two pairs of conjugated zeros and poles to represent the composite hydro-mechanical resonance effect in the closed rod position loop. A sixth-order model was thereafter proposed for even higher dynamics. The model parameters were identified and optimized by a full factor search approach. To meet the stringent specification of static and dynamic performances, it was demonstrated that a notch filter network combined with other controllers is needed since the traditional dynamic pressure feedback (DPF) is difficult to handle the high-order dynamics. The approach has been validated by simulation, experiments and successful flights. The models, analysis, data and insights were elaborated.

scholarly journals A Generalized Control Model and Its Digital Algorithm for Aerospace Electrohydraulic Actuators

Proceedings ◽  
2020 ◽  
Vol 64 (1) ◽  
pp. 31
Author(s):  
Shoujun Zhao ◽  
Keqin Chen ◽  
Xiaosha Zhang ◽  
Yingxin Zhao ◽  
Guanghui Jing ◽  
...  
Keyword(s):  
Transfer Function ◽  
Dynamic Pressure ◽  
Resonance Effect ◽  
Notch Filter ◽  
Digital Signal ◽  
Second Order ◽  
Large Engine ◽  
Combined Control ◽  
Pressure Feedback ◽  
Digital Algorithm

It is difficult to describe precisely, and thus control satisfactorily, the dynamics of an electrohydraulic actuator to drive a high thrust liquid launcher engine, whose structural resonant frequency is usually low due to its heavy inertia and its complicated mass distribution. A generalized model is therefore put forward for maximum simplification and sufficient approximation, where a second-order transfer function is used to model the heavy mass-spring nature of the large engine body outside of the rod position loop, another second-order transfer function with two zeros and two poles representing the hydro-mechanical composite resonance effect in the closed rod position loop. A combined control strategy is applied to meet the stringent specification of static and dynamic performances, including a notch filter, a piecewise or nonlinear proportional, integral and differential (PID) controller and a feed-forward compensation. The control algorithm is implemented in digital signal processors with the same software structure but different parameters for different aerospace actuators. Compared to other approaches, this one makes it easier to grasp the system resonance nature, and, most importantly, the traditional dynamic pressure feedback (DPF) is replaced with the convenient digital algorithm, bringing prominent benefits such as a simplified design, reduced hardware cost and inherent higher reliability. The approach has been validated by simulation, experiments and successful flights.

scholarly journals High-Order Deterministic Sensitivity Analysis and Uncertainty Quantification: Review and New Developments

Energies ◽  
2021 ◽  
Vol 14 (20) ◽  
pp. 6715
Author(s):  
Dan Cacuci
Keyword(s):  
Sensitivity Analysis ◽  
Nonlinear Systems ◽  
Fourth Order ◽  
State Of The Art ◽  
Solvable Model ◽  
High Order ◽  
Finite Difference Schemes ◽  
Model Parameters ◽  
Mathematical Framework ◽  
Deterministic Sensitivity Analysis

This work reviews the state-of-the-art methodologies for the deterministic sensitivity analysis of nonlinear systems and deterministic quantification of uncertainties induced in model responses by uncertainties in the model parameters. The need for computing high-order sensitivities is underscored by presenting an analytically solvable model of neutron scattering in a hydrogenous medium, for which all of the response’s relative sensitivities have the same absolute value of unity. It is shown that the wider the distribution of model parameters, the higher the order of sensitivities needed to achieve a desired level of accuracy in representing the response and in computing the response’s expectation, variance, skewness and kurtosis. This work also presents new mathematical expressions that extend to the sixth-order of the current state-of-the-art fourth-order formulas for computing fourth-order correlations among computed model response and model parameters. Another novelty presented in this work is the mathematical framework of the 3rd-Order Comprehensive Adjoint Sensitivity Analysis Methodology for Nonlinear Systems (3rd-CASAM-N), which enables the most efficient computation of the exact expressions of the 1st-, 2nd- and 3rd-order functional derivatives (“sensitivities”) of a model’s response to the underlying model parameters, including imprecisely known initial, boundary and/or interface conditions. The 2nd- and 3rd-level adjoint functions are computed using the same forward and adjoint computer solvers as used for solving the original forward and adjoint systems. Comparisons between the CPU times are also presented for an OECD/NEA reactor physics benchmark, highlighting the fact that finite-difference schemes would not only provide approximate values for the respective sensitivities (in contradistinction to the 3rd-CASAM-N, which provides exact expressions for the sensitivities) but would simply be unfeasible for computing sensitivities of an order higher than first-order. Ongoing work will generalize the 3rd-CASAM-N to a higher order while aiming to overcome the curse of dimensionality.

A Study on Adaptive Notch Filter Using Exponential All-Pass Transfer Function

2008 ◽  
Vol 128 (8) ◽  
pp. 1265-1270 ◽  
Author(s):  
Masaki Kobayashi ◽  
Chi Wang
Keyword(s):  
Transfer Function ◽  
Notch Filter ◽  
Adaptive Notch Filter

scholarly journals A Multivariate High-Order Markov Model for the Income Estimation of a Wind Farm

Energies ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 388
Author(s):  
Riccardo De Blasis ◽  
Giovanni Batista Masala ◽  
Filippo Petroni
Keyword(s):  
Markov Model ◽  
Electricity Market ◽  
Wind Farm ◽  
Central Italy ◽  
High Order ◽  
Distribution Model ◽  
Spot Price ◽  
Model Parameters ◽  
Price Series ◽  
Cross Correlations

The energy produced by a wind farm in a given location and its associated income depends both on the wind characteristics in that location—i.e., speed and direction—and the dynamics of the electricity spot price. Because of the evidence of cross-correlations between wind speed, direction and price series and their lagged series, we aim to assess the income of a hypothetical wind farm located in central Italy when all interactions are considered. To model these cross and auto-correlations efficiently, we apply a high-order multivariate Markov model which includes dependencies from each time series and from a certain level of past values. Besides this, we used the Raftery Mixture Transition Distribution model (MTD) to reduce the number of parameters to get a more parsimonious model. Using data from the MERRA-2 project and from the electricity market in Italy, we estimate the model parameters and validate them through a Monte Carlo simulation. The results show that the simulated income faithfully reproduces the empirical income and that the multivariate model also closely reproduces the cross-correlations between the variables. Therefore, the model can be used to predict the income generated by a wind farm.

scholarly journals Parameter Estimation of DC Motor using Adaptive Transfer Function Based on Nelder-Mead Optimisation

2018 ◽  
Vol 9 (3) ◽  
pp. 696 ◽  
Author(s):  
Byamakesh Nayak ◽  
Sangeeta Sahu ◽  
Tanmoy Roy Choudhury
Keyword(s):  
Experimental Data ◽  
Transfer Function ◽  
Adaptive Method ◽  
Dc Motor ◽  
Model Parameters ◽  
Current Response ◽  
Adaptive Model ◽  
Unknown Parameters ◽  
Dc Motors ◽  
Estimated Parameters

<p>This paper explains an adaptive method for estimation of unknown parameters of transfer function model of any system for finding the parameters. The transfer function of the model with unknown model parameters is considered as the adaptive model whose values are adapted with the experimental data. The minimization of error between the experimental data and the output of the adaptive model have been realised by choosing objective function based on different error criterions. Nelder-Mead optimisation Method is used for adaption algorithm. To prove the method robustness and for students learning, the simple system of separately excited dc motor is considered in this paper. The experimental data of speed response and corresponding current response are taken and transfer function parameters of  dc motors are adapted based on Nelder-Mead optimisation to match with the experimental data. The effectiveness of estimated parameters with different objective functions are compared and validated with machine specification parameters.</p>

scholarly journals Measurement-based Estimation of the Composite Load Model Parameters

2012 ◽  
Vol 7 (6) ◽  
pp. 845-851 ◽  
Author(s):  
Byoung-Ho Kim ◽  
Hong-Rae Kim
Keyword(s):  
Model Parameters ◽  
Load Model ◽  
Composite Load Model
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