scholarly journals A Unified Approach for the Identification of Wiener, Hammerstein, and Wiener–Hammerstein Models by Using WH-EA and Multistep Signals

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-23
Author(s):  
J. Zambrano ◽  
J. Sanchis ◽  
J. M. Herrero ◽  
M. Martínez
Keyword(s):  
Dynamic Systems ◽  
Thermal Process ◽  
Prior Information ◽  
A Priori ◽  
Unified Approach ◽  
Hammerstein System ◽  
Static Nonlinearity ◽  
Hammerstein Models ◽  
Single Structure ◽  
Process Structure

Wiener, Hammerstein, and Wiener–Hammerstein structures are useful for modelling dynamic systems that exhibit a static type nonlinearity. Many methods to identify these systems can be found in the literature; however, choosing a method requires prior knowledge about the location of the static nonlinearity. In addition, existing methods are rigid and exclusive for a single structure. This paper presents a unified approach for the identification of Wiener, Hammerstein, and Wiener–Hammerstein models. This approach is based on the use of multistep excitation signals and WH-EA (an evolutionary algorithm for Wiener–Hammerstein system identification). The use of multistep signals will take advantage of certain properties of the algorithm, allowing it to be used as it is to identify the three types of structures without the need for the user to know a priori the process structure. In addition, since not all processes can be excited with Gaussian signals, the best linear approximation (BLA) will not be required. Performance of the proposed method is analysed using three numerical simulation examples and a real thermal process. Results show that the proposed approach is useful for identifying Wiener, Hammerstein, and Wiener–Hammerstein models, without requiring prior information on the type of structure to be identified.

scholarly journals A Unified Approach to Online Matching with Conflict-Aware Constraints

2019 ◽  
Vol 33 ◽  
pp. 2221-2228
Author(s):  
Pan Xu ◽  
Yexuan Shi ◽  
Hao Cheng ◽  
John Dickerson ◽  
Karthik Abinav Sankararaman ◽  
...  
Keyword(s):  
Online Algorithm ◽  
Broad Class ◽  
A Priori ◽  
Algorithm Design ◽  
Unified Approach ◽  
Bipartite Matching ◽  
Theoretical Predictions ◽  
Online Labor ◽  
Synthetic Datasets ◽  
Event Based

Online bipartite matching and allocation models are widely used to analyze and design markets such as Internet advertising, online labor, and crowdsourcing. Traditionally, vertices on one side of the market are fixed and known a priori, while vertices on the other side arrive online and are matched by a central agent to the offline side. The issue of possible conflicts among offline agents emerges in various real scenarios when we need to match each online agent with a set of offline agents.For example, in event-based social networks (e.g., Meetup), offline events conflict for some users since they will be unable to attend mutually-distant events at proximate times; in advertising markets, two competing firms may prefer not to be shown to one user simultaneously; and in online recommendation systems (e.g., Amazon Books), books of the same type “conflict” with each other in some sense due to the diversity requirement for each online buyer.The conflict nature inherent among certain offline agents raises significant challenges in both modeling and online algorithm design. In this paper, we propose a unifying model, generalizing the conflict models proposed in (She et al., TKDE 2016) and (Chen et al., TKDE 16). Our model can capture not only a broad class of conflict constraints on the offline side (which is even allowed to be sensitive to each online agent), but also allows a general arrival pattern for the online side (which is allowed to change over the online phase). We propose an efficient linear programming (LP) based online algorithm and prove theoretically that it has nearly-optimal online performance. Additionally, we propose two LP-based heuristics and test them against two natural baselines on both real and synthetic datasets. Our LP-based heuristics experimentally dominate the baseline algorithms, aligning with our theoretical predictions and supporting our unified approach.

Metallographic evaluation of duplex stainless steel powders processed by selective laser melting

2017 ◽  
Vol 23 (6) ◽  
pp. 1146-1163 ◽  
Author(s):  
Karl P. Davidson ◽  
Sarat B. Singamneni
Keyword(s):  
Stainless Steel ◽  
Duplex Stainless Steel ◽  
Selective Laser Melting ◽  
A Priori ◽  
Fine Tuning ◽  
Structure Property ◽  
Laser Melting ◽  
Content Type ◽  
Test Pieces ◽  
Process Structure

Purpose This paper aims to establish the microstructures and the process-structure relationships in duplex stainless steel powders consolidated by selective laser melting (SLM). Design/methodology/approach A priori data on energy density levels most appropriate to consolidation of duplex stainless steel powders through SLM served as the basis to converge on the laser settings. Experimental designs with varying laser power and scan speeds and test pieces generated allowed metallographic evaluations based on optical and scanning electron microscopy and electro backscatter diffraction analyses. Findings Duplex stainless steel powders are established for processing by SLM. However, the dynamic point heat source and associated transient thermal fields affect the microstructures to be predominantly ferritic, with grains elongated in the build direction. Austenite precipitated either at the grain boundaries or as Widmanstätten laths, whereas the crystallographic orientations and the grain growth are affected around the cavities. Considerable CrN precipitation is also evidenced. Originality/value Duplex stainless steels are relatively new candidates to be brought into the additive manufacturing realm. Considering the poor machinability and other difficulties, the overarching result indicating suitability of duplex powders by SLM is of considerable value to the industry. More significantly, the metallographic evaluation and results of the current research allowed further understanding of the material consolidation aspects and pave ways for fine tuning and establishment of the process-structure-property relationships for this important process-material combination.

On the Control of Dynamically Unstable Systems Using a Self Organizing Black Box Controller

Volume 3 ◽  
2004 ◽  
Author(s):  
David W. Russell
Keyword(s):  
Dynamic Systems ◽  
Statistical Data ◽  
A Priori ◽  
Black Box ◽  
System Model ◽  
Self Organization ◽  
Limiting Factor ◽  
Chaotic Oscillations ◽  
State Variable ◽  
Apparent Reason

Many systems are difficult to control by conventional means because of the complexity of the very fabric of their being. Some systems perform very well under some conditions and then burst into wild, maybe even chaotic, oscillations for no apparent reason. Such systems exist in bioreactors, electro-plating and other application domains. In these cases a model may not exist that can be trusted to accurately replicate the dynamics of the real-world system. BOXES is a well known methodology that learns to perform control maneuvers for dynamic systems with only cursory a priori knowledge of the mathematics of the system model. A limiting factor in the BOXES algorithm has always been the assignment of appropriate boundaries to subdivide each state variable into regions. In addition to suggesting a method of alleviating this weakness, the paper shows that the accumulated statistical data in near neighboring states may be a powerful agent in accelerating learning, and may eventually provide a possible evolution to self-organization.

Wavelet transform inversion with prior scale information

Geophysics ◽  
1996 ◽  
Vol 61 (5) ◽  
pp. 1379-1385 ◽  
Author(s):  
Xin-Gong Li ◽  
Mauricio D. Sacchi ◽  
Tadeusz J. Ulrych
Keyword(s):  
Wavelet Transform ◽  
Prior Information ◽  
A Priori ◽  
Wavelet Basis ◽  
Wavelet Domain ◽  
Central Importance ◽  
Traveltime Inversion ◽  
Data Inversion ◽  
Damped Least Squares ◽  
Special Case

The concept of scale is of central importance in all problems related to the interpretation of earth data. Inversion of geophysical data does not at present, however, allow the incorporation of scale‐dependent information directly. This article presents an application of the wavelet transform to traveltime inversion where we are specifically concerned with the selection and application of a priori scale information in the wavelet domain to reconstruct tomographic models. Because of the nature of the problem, the wavelet basis chosen for this example is the Haar basis. The results are compared with the classic damped least‐squares (DLS) method, which is a special case of the wavelet transform approach when all the scales are treated equally. We show that with scale‐dependent prior information, most of the artifacts created by the DLS technique are diminished considerably.

DETECTION OF TRACKS IN AERIAL PHOTOS BY THE GIBBS SAMPLER

2003 ◽  
Vol 17 (01) ◽  
pp. 1-16 ◽  
Author(s):  
A. TETERUKOVSKIY
Keyword(s):  
Prior Knowledge ◽  
Cell Size ◽  
Bayesian Approach ◽  
Gibbs Sampler ◽  
Prior Information ◽  
A Priori ◽  
A Priori Knowledge ◽  
Gray Level ◽  
Aerial Photos ◽  
Positive Results

A problem of automatic detection of tracks in aerial photos is considered. We adopt a Bayesian approach and base our inference on an a priori knowledge of the structure of tracks. The probability of a pixel to belong to a track depends on how the pixel gray level differs from the gray levels of pixels in the neighborhood and on additional prior information. Several suggestions on how to formalize the prior knowledge about the shape of the tracks are made. The Gibbs sampler is used to construct the most probable configuration of tracks in the area. The method is applied to aerial photos with cell size of 1 sq. m. Even for detection of trails of width comparable with or smaller than the cell size, positive results can be achieved.

Structural Decomposition Approach for the Stability of Uncertain Dynamic Systems

1988 ◽  
Vol 55 (4) ◽  
pp. 992-994 ◽  
Author(s):  
Y. H. Chen ◽  
Chieh Hsu
Keyword(s):  
Dynamic Systems ◽  
A Priori ◽  
Parameter Variation ◽  
Stability Study ◽  
Fast Time ◽  
Time Varying ◽  
Decomposition Approach ◽  
New Approach ◽  
Uncertain Dynamic Systems ◽  
The Stability

The stability property for a class of dynamic systems with uncertain parameter variation is studied. The uncertainty can be fast time-varying and unpredictable. A new approach for stability study is proposed. The only required information on the uncertain variation is its possible bound as well as structure. That is, no a priori knowledge on the realization of the variation is needed.

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