An algorithm for non-parametric identification of highly nonlinear structures with incomplete measurements

2015 ◽  
pp. 169-172
Keyword(s):  
Parametric Identification ◽  
Nonlinear Structures ◽  
Highly Nonlinear ◽  
Non Parametric

scholarly journals Non-parametric identification of thermal control system elements

2021 ◽  
pp. 7-20
Author(s):  
Vasilisa Boeva ◽  
◽  
Yuri Voskoboinikov ◽  
Rustam Mansurov ◽  
◽  
...  
Keyword(s):  
Integral Equation ◽  
Control System ◽  
Impulse Response ◽  
Stable Solution ◽  
Parametric Identification ◽  
Thermal Control ◽  
Black Box ◽  
Response Evaluation ◽  
Thermal Control System ◽  
Non Parametric

The thermal control system “Heater-Fan-Room” is represented by three different-type interconnected simpler subsystems. In this paper, a “black-box” whose structure is not specified is used as a mathematical model of the system and subsystems due to complexity of physical processes proceeding in these subsystems. For stationary linear systems, the connection between an input and an output of the “black-box” is defined by the Volterra integral equation of the first kind with an undetermined difference kernel also known as impulse response in the automatic control theory. In such a case, it is necessary to evaluate an unknown impulse response to use the “black-box” model and formulate all subsystems and the system as a whole. This condition complicates significantly the solution search of non-parametric identification problems in the system because an output of one subsystem is an input of another subsystem, so active identification schemes are unappropriated. Formally, an impulse response evaluation is a solution of the integral equation of the first kind for its kernel by registered noise-contaminated discrete input and output values. This problem is ill-posed because of the possible solution instability (impulse response evaluation in this case) relative to measurement noises in initial data. To find a unique stable solution regularizing algorithms are used, but the specificity of the impulse response identification experiment in the “Heater-Fan-Room” system do not allow applying computational methods of these algorithms (a system of linear equations or discrete Fourier transformation). In this paper, the authors propose two specific identification algorithms for complex technical systems. In these algorithms, impulse responses are evaluated using first derivatives of identified system signals that are stably calculated by smoothing cubic splines with an original smoothing parameter algorithm. The results of the complex “Heater-Fan-Room” system modeling and identification prove the efficiency of the algorithms proposed. Acknowledgments: The reported study was funded by RFBR, project number 20-38-90041.

NON-PARAMETRIC IDENTIFICATION TECHNIQUES FOR INTELLIGENT PNEUMATIC ACTUATOR

2015 ◽  
Vol 77 (20) ◽  
Author(s):  
Abdulrahman A. A. Emhemed ◽  
Rosbi Mamat ◽  
Ahmad ‘Athif Mohd Faudzi
Keyword(s):  
System Identification ◽  
Parametric Identification ◽  
Pneumatic Actuator ◽  
Step Response ◽  
Model Parameters ◽  
Force Model ◽  
Force System ◽  
Identification Technique ◽  
Identification Techniques ◽  
Non Parametric

The aim of this paper is to present experimental, empirical and analytic identification techniques, known as non-parametric techniques. Poor dynamics and high nonlinearities are parts of the difficulties in the control of pneumatic actuator functions, which make the identification technique very challenging. Firstly, the step response experimental data is collected to obtain real-time force model of the intelligent pneumatic actuator (IPA). The IPA plant and Personal Computer (PC) communicate through Data Acquisition (DAQ) card over MATLAB software. The second method is approximating the process by curve reaction of a first-order plus delay process, and the third method uses the equivalent n order process with PTn model parameters. The obtained results have been compared with the previous study, achieved based on force system identification of IPA obtained by the (Auto-Regressive model with eXogenous) ARX model. The models developed using non-parameters identification techniques have good responses and their responses are close to the model identified using the ARX system identification model. The controller approved the success of the identification technique with good performance. This means the Non-Parametric techniques are strongly recommended, suitable, and feasible to use to analyze and design the force controller of IPA system. The techniques are thus very suitable to identify the real IPA plant and achieve widespread industrial acceptance.

Non-Parametric Identification Method of Volterra Kernels for Nonlinear Systems Excited by Multitone Signal

2013 ◽  
Vol 16 (2) ◽  
pp. 519-529 ◽  
Author(s):  
H. T. Han ◽  
H. G. Ma ◽  
L. N. Tan ◽  
J. F. Cao ◽  
J. L. Zhang
Keyword(s):  
Nonlinear Systems ◽  
Parametric Identification ◽  
Volterra Kernels ◽  
Identification Method ◽  
Non Parametric
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