Application of ADRC Based on Reduced Order Model in Electromechanical Actuation System of Rudder

2021 ◽  
pp. 727-741
Author(s):  
Wen-bo Xu ◽  
Ze-yu Wei ◽  
Yong-jian Ni ◽  
Di-kai Jiang
Keyword(s):  
Reduced Order Model ◽  
Order Model ◽  
Reduced Order ◽  
Actuation System ◽  
Electromechanical Actuation

scholarly journals A Novel Sliding Mode Control Framework for Electrohydrostatic Position Actuation System

2018 ◽  
Vol 2018 ◽  
pp. 1-22 ◽  
Author(s):  
Rongrong Yang ◽  
Yongling Fu ◽  
Ling Zhang ◽  
Haitao Qi ◽  
Xu Han ◽  
...  
Keyword(s):  
Sliding Mode Control ◽  
Position Control ◽  
Sliding Mode ◽  
Reduced Order Model ◽  
Design Solution ◽  
Order Model ◽  
Reduced Order ◽  
Mode Control ◽  
Actuation System ◽  
Mismatched Disturbances

A novel sliding mode control (SMC) design framework is devoted to providing a favorable SMC design solution for the position tracking control of electrohydrostatic actuation system (EHSAS). This framework is composed of three submodules as follows: a reduced-order model of EHSAS, a disturbance sliding mode observer (DSMO), and a new adaptive reaching law (NARL). First, a reduced-order model is obtained by analyzing the flow rate continuation equation of EHSAS to avoid the use of a state observer. Second, DSMO is proposed to estimate and compensate mismatched disturbances existing in the reduced-order model. In addition, a NARL is developed to tackle the inherent chattering problem of SMC. Extensive simulations are conducted compared with the wide adoption of three-loop PID method on the cosimulation platform of EHSAS, which is built by combining AMESim with MATLAB/Simulink, to verify the feasibility and superiority of the proposed scheme. Results demonstrate that the chattering can be effectively attenuated, and the mismatched disturbance can be satisfyingly compensated. Moreover, the transient performance, steady-state accuracy, and robustness of position control are all improved.

Model Order Reduction of Transmission Line Model

2020 ◽  
Vol 19 ◽  
Keyword(s):  
Transmission Line ◽  
Large Scale ◽  
Original System ◽  
Reduced Order Model ◽  
Benchmark Problems ◽  
Transmission Line Model ◽  
Order Model ◽  
Line Model ◽  
Reduced Order ◽  
Numerical Effort

Transmission Line model are an important role in the electrical power supply. Modeling of such system remains a challenge for simulations are necessary for designing and controlling modern power systems.In order to analyze the numerical approach for a benchmark collection Comprehensive of some needful real-world examples, which can be utilized to evaluate and compare mathematical approaches for model reduction. The approach is based on retaining the dominant modes of the system and truncation comparatively the less significant once.as the reduced order model has been derived from retaining the dominate modes of the large-scale stable system, the reduction preserves the stability. The strong demerit of the many MOR methods is that, the steady state values of the reduced order model does not match with the higher order systems. This drawback has been try to eliminated through the Different MOR method using sssMOR tools. This makes it possible for a new assessment of the error system Offered that the Observability Gramian of the original system has as soon as been thought about, an H∞ and H2 error bound can be calculated with minimal numerical effort for any minimized model attributable to The reduced order model (ROM) of a large-scale dynamical system is essential to effortlessness the study of the system utilizing approximation Algorithms. The response evaluation is considered in terms of response constraints and graphical assessments. the application of Approximation methods is offered for arising ROM of the large-scale LTI systems which consist of benchmark problems. The time response of approximated system, assessed by the proposed method, is also shown which is excellent matching of the response of original system when compared to the response of other existing approaches .

Theoretical and practical identifiability of a reduced order model in an activated sludge process doing nitrification and denitrification

1998 ◽  
Vol 37 (12) ◽  
pp. 309-316 ◽  
Author(s):  
S. Julien ◽  
J. P. Babary ◽  
P. Lessard
Keyword(s):  
Activated Sludge ◽  
Reduced Order Model ◽  
Actual Behavior ◽  
Activated Sludge Process ◽  
Order Model ◽  
Identifiability Analysis ◽  
Reduced Order ◽  
3 Dimensional ◽  
Nitrification And Denitrification ◽  
Line Oxygen

This paper deals with the structural identifiability and the identification of the parameters of a reduced order model used for control of a single reactor activated sludge process doing nitrification and denitrification. This reduced order model is splitted into two submodels, one 3-dimensional state submodel in aerobic conditions and one 2-dimensional state submodel in anoxic conditions. The identifiability analysis is based on on-line oxygen and nitrate concentrations data. It has been shown that the reduced order model is structurally identifiable. The parameter identification has been carried out by using the simplex method of Nelder and Mead. Simulation results performed over a range of six hours (two aerobic/anoxic cycles), show that there exists a good fit between the simulated solution and the actual behavior of a lab scale pilot plant.

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