scholarly journals Multimodel System Identification Based on New Fuzzy Partitioning Similarity Measure

2021 ◽  
Vol 10 (9) ◽  
pp. 19-30
Author(s):  
Abdelhadi Radouane ◽  
◽  
Fouad Giri ◽  
Abdessamad Naitali ◽  
Fatima Zahra Chaoui ◽  
...  
Keyword(s):  
Nonlinear System ◽  
Similarity Measure ◽  
Tropospheric Ozone ◽  
Euclidean Distance ◽  
Angular Deviation ◽  
Local Models ◽  
Working Space ◽  
Fuzzy Partitioning ◽  
Global Representation ◽  
Operating Space

The problem of identifying unstructured nonlinear systems is generally addressed on the basis of multi-model representations involving several linear local models. In the present work, local models are combined to get a global representation using incremental fuzzy clustering. The main contribution is a novel vector similarity measure defined in the System Working Space (SWS) that combines the angular deviation and the usual Euclidean distance. Such a combination makes the new metric highly discriminating leading to a better partitioning of the operating space providing, thereby, a higher accuracy of the model. The developed partitioning method is first evaluated by performing linear local model (LLM) based identification of a academic benchmark multivariable nonlinear system. Then, the performances of the identification method are evaluated using experimental tropospheric ozone data. These evaluations illustrate the supremacy of the new method over the standard Euclidian-distance based partitioning approach.

Spheric radial basis functions in Mahalanobis measuring for displaying local field features

2019 ◽  
Vol 952 (10) ◽  
pp. 2-9
Author(s):  
Yu.M. Neiman ◽  
L.S. Sugaipova ◽  
V.V. Popadyev
Keyword(s):  
Gravitational Field ◽  
Quadratic Form ◽  
Local Field ◽  
Euclidean Distance ◽  
Basis Functions ◽  
Spherical Functions ◽  
Local Models ◽  
Stationary Field ◽  
Modeling Process ◽  
The Earth

As we know the spherical functions are traditionally used in geodesy for modeling the gravitational field of the Earth. But the gravitational field is not stationary either in space or in time (but the latter is beyond the scope of this article) and can change quite strongly in various directions. By its nature, the spherical functions do not fully display the local features of the field. With this in mind it is advisable to use spatially localized basis functions. So it is convenient to divide the region under consideration into segments with a nearly stationary field. The complexity of the field in each segment can be characterized by means of an anisotropic matrix resulting from the covariance analysis of the field. If we approach the modeling in this way there can arise a problem of poor coherence of local models on segments’ borders. To solve the above mentioned problem it is proposed in this article to use new basis functions with Mahalanobis metric instead of the usual Euclidean distance. The Mahalanobis metric and the quadratic form generalizing this metric enables us to take into account the structure of the field when determining the distance between the points and to make the modeling process continuous.

Similarity improvement using angular deviation in multimodel nonlinear system identification

2013 ◽  
Vol 46 (11) ◽  
pp. 605-610
Author(s):  
Abdelhadi RADOUANE ◽  
Fouad GIRI ◽  
Abdessamad NAITALI ◽  
Fatima Zahra Chaoui
Keyword(s):  
System Identification ◽  
Nonlinear System ◽  
Nonlinear System Identification ◽  
Angular Deviation

Motion Analysis and Research on Mobile Swing Type Manipulator

2012 ◽  
Vol 588-589 ◽  
pp. 194-197
Author(s):  
Ke Tao ◽  
Xing Liu
Keyword(s):  
Degrees Of Freedom ◽  
Linear Interpolation ◽  
Joint Space ◽  
Transformation Method ◽  
Inverse Transformation ◽  
Interpolation Theory ◽  
End Effector ◽  
Working Space ◽  
Space Coordinate ◽  
Operating Space

The working space and the end-effector pose of the two degrees of freedom mobile swing type manipulator are analyzed, through homogeneous coordinate transformation to establish the transformation relationship between operating space coordinate and each joint space coordinate, derived the end-effector pose matrix , using the inverse transformation method to seek motion reverse solution. Application of linear interpolation theory, doing trajectory planning for arbitrary movement path, show manipulator in its working space can realize arbitrary trajectory.

scholarly journals Mixed Reality-Enhanced Intuitive Teleoperation with Hybrid Virtual Fixtures for Intelligent Robotic Welding

2021 ◽  
Vol 11 (23) ◽  
pp. 11280
Author(s):  
Yun-Peng Su ◽  
Xiao-Qi Chen ◽  
Tony Zhou ◽  
Christopher Pretty ◽  
J. Geoffrey Chase
Keyword(s):  
Haptic Feedback ◽  
Mixed Reality ◽  
Hand Movements ◽  
Robotic Welding ◽  
Virtual Fixtures ◽  
Working Space ◽  
Welding Operation ◽  
Welding Torch ◽  
Operating Space ◽  
Welding System

This paper presents an integrated scheme based on a mixed reality (MR) and haptic feedback approach for intuitive and immersive teleoperation of robotic welding systems. By incorporating MR technology, the user is fully immersed in a virtual operating space augmented by real-time visual feedback from the robot working space. The proposed robotic tele-welding system features imitative motion mapping from the user’s hand movements to the welding robot motions, and it enables the spatial velocity-based control of the robot tool center point (TCP). The proposed mixed reality virtual fixture (MRVF) integration approach implements hybrid haptic constraints to guide the operator’s hand movements following the conical guidance to effectively align the welding torch for welding and constrain the welding operation within a collision-free area. Onsite welding and tele-welding experiments identify the operational differences between professional and unskilled welders and demonstrate the effectiveness of the proposed MRVF tele-welding framework for novice welders. The MRVF-integrated visual/haptic tele-welding scheme reduced the torch alignment times by 56% and 60% compared to the MRnoVF and baseline cases, with minimized cognitive workload and optimal usability. The MRVF scheme effectively stabilized welders’ hand movements and eliminated undesirable collisions while generating smooth welds.

Online Nonlinear System Identification With Parameter Constraints: Application to Automotive Engine Systems

2019 ◽  
Author(s):  
Kaian Chen ◽  
Zhaojian Li ◽  
Yan Wang ◽  
Jing Wang ◽  
Kai Wu ◽  
...  
Keyword(s):  
System Identification ◽  
Nonlinear System ◽  
Gasoline Engine ◽  
Nonlinear System Identification ◽  
Local Models ◽  
Automotive Engine ◽  
Linear Equality ◽  
Parameter Constraints ◽  
Engine Systems ◽  
Output Space

Abstract In this paper, we treat the problem of online nonlinear system identification with parameter constraints. This approach is based upon our prior work on nonlinear system identification that exploits evolving Spatial-Temporal Filters (STF) to dynamically decompose system’s input/output space into a nonlinear combination of weighted local models. We extend the nonlinear system identification framework with the capability of dealing with linear equality and inequality parameter constraints. We leverage the gradient projection method in the local model parameter estimation process to inherently enforce the parameter constraints while retaining optimality. We apply the proposed algorithm to a turbo-charged gasoline engine system and promising results are demonstrated by experimental data.

scholarly journals Multiscale Hybrid Nonlocal Means Filtering Using Modified Similarity Measure

2015 ◽  
Vol 2015 ◽  
pp. 1-17 ◽  
Author(s):  
Zahid Hussain Shamsi ◽  
Dai-Gyoung Kim
Keyword(s):  
Similarity Measure ◽  
Euclidean Distance ◽  
State Of The Art ◽  
Inner Product ◽  
Wavelet Domain ◽  
Noisy Image ◽  
Nonlocal Means ◽  
Normal Vectors ◽  
Proposed Modification ◽  
Refined Version

A new multiscale implementation of nonlocal means filtering (MHNLM) for image denoising is proposed. The proposed algorithm also introduces a modification of the similarity measure for patch comparison. Assuming the patch as an oriented surface, the notion of a normal vectors patch is introduced. The inner product of these normal vectors patches is defined and then used in the weighted Euclidean distance of intensity patches as the weight factor. The algorithm involves two steps: the first step is a multiscale implementation of an accelerated nonlocal means filtering in the discrete stationary wavelet domain to obtain a refined version of the noisy patches for later comparison. The next step is to apply the proposed modification of standard nonlocal means filtering to the noisy image using the reference patches obtained in the first step. These refined patches contain less noise, and consequently the computation of normal vectors and partial derivatives is more precise. Experimental results show equivalent or better performance of the proposed algorithm compared to various state-of-the-art algorithms.

scholarly journals A Control-Performance-Based Partitioning Operating Space Approach in a Heterogeneous Multiple Model

Processes ◽  
2020 ◽  
Vol 8 (2) ◽  
pp. 215
Author(s):  
Bing Wu ◽  
Ximei Liu ◽  
Yaobin Yue
Keyword(s):  
Nonlinear System ◽  
Equilibrium Points ◽  
Control Input ◽  
Multiple Model ◽  
Control Performance ◽  
Model Predictive Controller ◽  
Space Partition ◽  
Computational Implementation ◽  
Predictive Controller ◽  
Operating Space

An operating space partition method with control performance is proposed, where the heterogeneous multiple model is applied to a nonlinear system. Firstly, the heterogeneous multiple model is obtained from a nonlinear system at the given equilibrium points and transformed into a homogeneous multiple model with auxiliary variables. Secondly, an optimal problem where decision variables are composed of control input and boundary conditions of sub-models is formulated with the hybrid model developed from the homogeneous multiple model. The computational implementation of an optimal operating space partition algorithm is presented according to the Hamilton–Jacobi–Bellman equation and numerical method. Finally, a multiple model predictive controller is designed, and the computational implementation of the multiple model predictive controller is addressed with the auxiliary vectors. Furthermore, a continuous stirred tank reactor (CSTR) is used to confirm the effectiveness of the developed method as well as compare with other operating space decomposition methods.

scholarly journals AN EFFICIENT APPROACH FOR CONTENT BASED RETRIEVAL USING MULTI WAVELET AND HSV COLOR SPACE

2013 ◽  
pp. 23-25
Author(s):  
E. VENKATESWARLU ◽  
K.SOUNDARA RAJAN
Keyword(s):  
Image Retrieval ◽  
Similarity Measure ◽  
Euclidean Distance ◽  
Color Space ◽  
Visual Feature ◽  
Computation Complexity ◽  
Hsv Color Space ◽  
Efficient Approach ◽  
Retrieval Accuracy ◽  
Canberra Distance

This paper presents an approach for image retrieval by using multiwavelet and hsv color space. The HSV stands for the Hue, Saturation and Value, provides the perception representation according with human visual feature. The multiwavelets offer simultaneous orthogonality, symmetry and short support. In this paper, we have tested 140 images with 5 different categories. the experimental results show the better results interms of retrieval accuracy and computation complexity. The performance of this approach is measured and results are shown. Euclidean Distance and Canberra Distance are used as similarity measure in the proposed CBIR system.

A New Similarity Measure Based on Adjusted Euclidean Distance for Memory-based Collaborative Filtering

2011 ◽  
Vol 6 (6) ◽  
Author(s):  
Huifeng Sun ◽  
Yong Peng ◽  
Junliang Chen ◽  
Chuanchang Liu ◽  
Yuzhuo Sun
Keyword(s):  
Collaborative Filtering ◽  
Similarity Measure ◽  
Euclidean Distance
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