scholarly journals An LPV Fractional Model for Canal Control

2009 ◽  
Vol 2009 ◽  
pp. 1-18 ◽  
Author(s):  
Rubén Martínez-González ◽  
Yolanda Bolea ◽  
Antoni Grau ◽  
Herminio Martínez-García

An LPV rational order control model of an irrigation canal is derived from system identification experiments. This model is experimentally obtained by using the described LPV fractional identification procedure. This procedure consists of the identification of a rational order model in each operation point in an experimental test canal. Global LPV model is obtained from polynomial interpolation of local model parameters. Validation results demonstrate that rational order models are more accurate than integer order models. Therefore rational order control models have an important role to play in management and efficient use of water resources.

2011 ◽  
Vol 374-377 ◽  
pp. 105-108
Author(s):  
Li Ying ◽  
Ting Ting Guo ◽  
Pan Pan Li

The conception and study status of ecological footprint of water resource were summarized and the research of two ecological footprint model parameters, ie equilibrium factors and yield factors were analyzed and compared. On this basis, the calculation of ecological footprint model parameters of the Beijing urban water resources, ie balance factor and yield factor were proposed. Water balance factors of Beijing urban water resources and water yield per unit area and water yield factor of Beijing Fangshan, Pinggu, Yanqing were calculated, thus provide reference for appraisal of ecological carrying capacity of Beijing urban water resources.


Author(s):  
Francesco Braghin ◽  
Federico Cheli ◽  
Edoardo Sabbioni

Individual tire model parameters are traditionally derived from expensive component indoor laboratory tests as a result of an identification procedure minimizing the error with respect to force and slip measurements. These parameters are then transferred to vehicle models used at a design stage to simulate the vehicle handling behavior. A methodology aimed at identifying the Magic Formula-Tyre (MF-Tyre) model coefficients of each individual tire for pure cornering conditions based only on the measurements carried out on board vehicle (vehicle sideslip angle, yaw rate, lateral acceleration, speed and steer angle) during standard handling maneuvers (step-steers) is instead presented in this paper. The resulting tire model thus includes vertical load dependency and implicitly compensates for suspension geometry and compliance (i.e., scaling factors are included into the identified MF coefficients). The global number of tests (indoor and outdoor) needed for characterizing a tire for handling simulation purposes can thus be reduced. The proposed methodology is made in three subsequent steps. During the first phase, the average MF coefficients of the tires of an axle and the relaxation lengths are identified through an extended Kalman filter. Then the vertical loads and the slip angles at each tire are estimated. The results of these two steps are used as inputs to the last phase, where, the MF-Tyre model coefficients for each individual tire are identified through a constrained minimization approach. Results of the identification procedure have been compared with experimental data collected on a sport vehicle equipped with different tires for the front and the rear axles and instrumented with dynamometric hubs for tire contact forces measurement. Thus, a direct matching between the measured and the estimated contact forces could be performed, showing a successful tire model identification. As a further verification of the obtained results, the identified tire model has also been compared with laboratory tests on the same tire. A good agreement has been observed for the rear tire where suspension compliance is negligible, while front tire data are comparable only after including a suspension compliance compensation term into the identification procedure.


1976 ◽  
Vol 40 (2) ◽  
pp. 171-176 ◽  
Author(s):  
T. B. Watt ◽  
C. S. Burrus

The form of an arterial blood pressure curve during the diastolic portion of the cardiac cycle was here employed to identify parameters in a third-order model of the vascular system. Calculated elastic and intertial characteristics of this fitted model then became clinically accessible indices of corresponding real vascular properties. This technique incurred no risk and little discomfort for the patient. Tested in theory, in animal experimentation, and in human observations, our procedure utilized a Gauss-Newton algorithm via digital computer to provide rapid model solutions from different starting values, from multiple measurements sites, and from normal or diseased patients. Model parameters thus determined defined ranges of normal variation and suggested a less compliant arterial bed in hypertensive than in normotensive patients.


Complexity ◽  
2017 ◽  
Vol 2017 ◽  
pp. 1-12 ◽  
Author(s):  
Lan Wang ◽  
Yu Cheng ◽  
Jinglu Hu ◽  
Jinling Liang ◽  
Abdullah M. Dobaie

Quasi-linear autoregressive with exogenous inputs (Quasi-ARX) models have received considerable attention for their usefulness in nonlinear system identification and control. In this paper, identification methods of quasi-ARX type models are reviewed and categorized in three main groups, and a two-step learning approach is proposed as an extension of the parameter-classified methods to identify the quasi-ARX radial basis function network (RBFN) model. Firstly, a clustering method is utilized to provide statistical properties of the dataset for determining the parameters nonlinear to the model, which are interpreted meaningfully in the sense of interpolation parameters of a local linear model. Secondly, support vector regression is used to estimate the parameters linear to the model; meanwhile, an explicit kernel mapping is given in terms of the nonlinear parameter identification procedure, in which the model is transformed from the nonlinear-in-nature to the linear-in-parameter. Numerical and real cases are carried out finally to demonstrate the effectiveness and generalization ability of the proposed method.


Author(s):  
Randell M. Johnson ◽  
Joe H. Chow ◽  
Michael V. Dillon

Underspeed needle control of two Pelton turbine hydro units operating in a small power system has caused many incidents of partial system blackouts. Among the causes are conservative governor designs with regard to small signal stability limits, non-minimum phase power characteristics, and long tunnel-penstock traveling wave effects. A needle control model is developed from “water to wires” and validated for hydro-turbine dynamics using turbine test data. Model parameters are tuned with trajectory sensitivity. Proposed governor designs decompose the needle regulation gains into the power and frequency governor loops with a multi-time-scale approach. Elements of speed loop gain scheduling and a new inner-loop pressure stabilization circuit are devised to improve the frequency regulation and to damp the traveling wave effects. Simulation studies show the improvements of the proposed control designs.


2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Jorge Santolaria ◽  
Ana C. Majarena ◽  
David Samper ◽  
Agustín Brau ◽  
Jesús Velázquez

A new procedure for the calibration of an articulated arm coordinate measuring machine (AACMM) is presented in this paper. First, a self-calibration algorithm of four laser trackers (LTs) is developed. The spatial localization of a retroreflector target, placed in different positions within the workspace, is determined by means of a geometric multilateration system constructed from the four LTs. Next, a nonlinear optimization algorithm for the identification procedure of the AACMM is explained. An objective function based on Euclidean distances and standard deviations is developed. This function is obtained from the captured nominal data (given by the LTs used as a gauge instrument) and the data obtained by the AACMM and compares the measured and calculated coordinates of the target to obtain the identified model parameters that minimize this difference. Finally, results show that the procedure presented, using the measurements of the LTs as a gauge instrument, is very effective by improving the AACMM precision.


2017 ◽  
Vol 24 (18) ◽  
pp. 4145-4159 ◽  
Author(s):  
Hai-Bo Yuan ◽  
Hong-Cheol Na ◽  
Young-Bae Kim

This paper examined system identification using grey-box model estimation and position-tracking control for an electro-hydraulic servo system (EHSS) using hybrid controller composed of proportional-integral control (PIC) and model predictive control (MPC). The nonlinear EHSS model is represented by differential equations. We identify model parameters and verify their accuracy against experimental data in MATLAB to evaluate the validity of this mathematical model. To guarantee improved performance of EHSS and precision of cylinder position, we propose a hybrid controller composed of PIC and MPC. The controller is designed using the Control Design and Simulation module in the Laboratory Virtual Instrumentation Engineering Workbench (LabVIEW). A LabVIEW-based experimental rig is developed to apply the proposed controller in real time. Then, the validity and performance superiority of the hybrid controller were confirmed by comparing them with the MPC and PIC results. Results of real-life experiments show improved robustness and dynamic and static properties of EHSS.


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