A Model Accuracy and Validation Algorithm

2002 ◽  
Author(s):  
Polat Sendur ◽  
Jeffrey L. Stein ◽  
Huei Peng ◽  
Loucas S. Louca
Keyword(s):  
Physical System ◽  
Dynamic Models ◽  
System Model ◽  
System Response ◽  
Model Accuracy ◽  
Physical Systems ◽  
System Models ◽  
Points Of Interest ◽  
Measured System

Dynamic models of physical systems with physically meaningful states and parameters have become increasingly important, for design, control and even procurement decisions. The successful use of models in these contexts requires that the models be of sufficient quality. However, while algorithms have been developed to help formulate and integrate physical system models, as well as to generate minimum complexity physical system models, algorithms to assess the “quality” of dynamic system models have not been produced. This is true even if the attributes of model are limited to accuracy and validity. The objective of this paper is to introduce a new methodology that systematically quantifies the accuracy of a predicted system response and determines the validity of the physical system model used to predict the system response. The accuracy and validity of the model are evaluated using statistical properties of measured system response. The new algorithm is called Accuracy & Validation Algorithm for Simulation (AVASIM), and is a time-domain perspective comparing the model’s time trajectories at user-defined points of interest as well as over the entire simulation horizon. To illustrate AVASIM, the quality of a handling model of a DaimlerChrysler Grand Cherokee is compared to the measurements obtained from that vehicle subjected to known steering inputs. Results demonstrate that the accuracy and validity of the Grand Cherokee model can be systematically assessed using the proposed methodology, and, thus, AVASIM appears to be a powerful tool for assessing the quality of system models.

Networked Assembly of Affine Physical System Models

2006 ◽  
Author(s):  
E. Motato ◽  
C. Radcliffe
Keyword(s):  
Physical System ◽  
Dynamic Models ◽  
Dynamic Stiffness ◽  
Global Strategy ◽  
Standard Format ◽  
Modular Modeling ◽  
Assembly Algorithm ◽  
System Models ◽  
Stiffness Matrices ◽  
External Behavior

Engineering design is evolving into a global strategy that distributes model information through computer networks. This strategy requires companies to provide dynamic models of supplied components. Component models must be assembled to obtain the product dynamic model. Four characteristics are needed. Specifically, models require a unique standard format, the exchange of model information must be executed in a single-query transmission, the models must describe only external behavior, and the assembly process must be recursive. The Modular Modeling Method (MMM) [1], is a model assembly algorithm that satisfies these requirements. The MMM algorithm assembles linear physical systems models with dynamic stiffness matrices. This paper will extend MMM to nonlinear affine behavior. In an affine system, deviations in the inputs and outputs exhibit a proportional relationship, but the outputs of the system are not zero at zero input [2]. The main reason for developing a process to assemble affine systems is the possibility of using this method to assemble general differentiable nonlinear physical system models performing around a constant operating point.

Networked Assembly of Mechatronic Linear Physical System Models

2009 ◽  
Vol 131 (2) ◽  
Author(s):  
Clark J. Radcliffe ◽  
Eliot Motato ◽  
Drew Reichenbach
Keyword(s):  
Physical System ◽  
Dynamic Models ◽  
External Input ◽  
Global Network ◽  
Analytical Models ◽  
Thermal Dynamics ◽  
Efficient System ◽  
Standard Format ◽  
System Models ◽  
Assembly Method

Engineering design is evolving into a global activity. Globally distributed design requires efficient global distribution of models of dynamic physical systems through computer networks. These models must describe the external input-output behavior of the electrical, mechanical, fluid, and thermal dynamics of engineering systems. An efficient system model assembly method is then required to assemble these component system models into a model of a yet higher-level dynamic system. Done recursively, these higher-level system models become possible components for yet higher-level analytical models composed of external model equations in the same standardized format as that of the lowest level components. Real-time, automated exchange, and assembly of engineering dynamic models over a global network requires four characteristics. The models exchanged must have a unique standard format so that they can be exchanged and assembled by an automated process. The exchange of model information must be executed in a single-query transmission to minimize network load. The models must describe only external behavior to protect internal model details. Finally, the assembly process must be recursive so that the transfer and assembly processes do not change with the level of the model exchanged or assembled. This paper will introduce the modular modeling method (MMM), a modeling strategy that satisfies these requirements. The MMM distributes and assembles linear dynamic physical system models with a dynamic matrix representation. Using the MMM method, dynamic models of complex assemblies can be built and distributed while hiding the topology and characteristics of their dynamic subassemblies.

Experimental Test Plan and Data Analysis Based on the Design of Experiment Methodology

2012 ◽  
Author(s):  
Angelo Esposito ◽  
Philippe Mocoteguy ◽  
Fabio Postiglione ◽  
Maurizio Guida ◽  
Cesare Pianese ◽  
...  
Keyword(s):  
Fuel Cell ◽  
Design Of Experiment ◽  
Solid Oxide ◽  
System Model ◽  
System Response ◽  
Test Plan ◽  
Model Accuracy ◽  
Fuel Cell Stack ◽  
Input Variables ◽  
Full Factorial

The development of fault diagnostics for fuel cell (FC) stacks and systems can increase their lifetime and therefore their overall efficiency. The development of such techniques often requires a reliable computational FC stack or system model. Given the complexity of such systems, endless time and effort has to be used to test the systems and identify the related models unless an adequate trade-off between available time and desired model accuracy is found. The Design of Experiment (DoE) methodology enables determining the best compromise between the number of experiments to conduct and the obtained information. In this work, the DoE approach is used to define a test plan that is carried out on a solid oxide fuel cell stack. The methodology is then further exploited to analyse the measured data and to determine the influence of the selected parameters (i.e. input variables) on the response extracted from the monitored variables. Specifically, a Full Factorial DoE analysis is performed and the relative results are compared. The results show which parameters have a direct effect and which affect indirectly, in coupling with other parameters, on the system response.

Methods of parallel computing for multilevel fuzzy Takagi – Sugeno systems

2016 ◽  
pp. 141-149
Author(s):  
S.V. Yershov ◽  
◽  
R.М. Ponomarenko ◽  
Keyword(s):  
Dynamic Models ◽  
Fuzzy Inference ◽  
Knowledge Bases ◽  
Comparative Characteristic ◽  
Software Systems ◽  
Scientific Papers ◽  
Speed Up ◽  
Diagnostic Software ◽  
Takagi Sugeno

Parallel tiered and dynamic models of the fuzzy inference in expert-diagnostic software systems are considered, which knowledge bases are based on fuzzy rules. Tiered parallel and dynamic fuzzy inference procedures are developed that allow speed up of computations in the software system for evaluating the quality of scientific papers. Evaluations of the effectiveness of parallel tiered and dynamic schemes of computations are constructed with complex dependency graph between blocks of fuzzy Takagi – Sugeno rules. Comparative characteristic of the efficacy of parallel-stacked and dynamic models is carried out.

scholarly journals VeriPhy: verified controller executables from verified cyber-physical system models

2018 ◽  
Vol 53 (4) ◽  
pp. 617-630 ◽  
Author(s):  
Brandon Bohrer ◽  
Yong Kiam Tan ◽  
Stefan Mitsch ◽  
Magnus O. Myreen ◽  
André Platzer
Keyword(s):  
Physical System ◽  
Cyber Physical System ◽  
System Models

scholarly journals A Survey on Machine-Learning Based Security Design for Cyber-Physical Systems

2021 ◽  
Vol 11 (12) ◽  
pp. 5458
Author(s):  
Sangjun Kim ◽  
Kyung-Joon Park
Keyword(s):  
Machine Learning ◽  
Physical System ◽  
Large Scale ◽  
Computing System ◽  
Future Research ◽  
Physical Security ◽  
Computing Systems ◽  
Physical Systems ◽  
Security Research ◽  
Simultaneous Control

A cyber-physical system (CPS) is the integration of a physical system into the real world and control applications in a computing system, interacting through a communications network. Network technology connecting physical systems and computing systems enables the simultaneous control of many physical systems and provides intelligent applications for them. However, enhancing connectivity leads to extended attack vectors in which attackers can trespass on the network and launch cyber-physical attacks, remotely disrupting the CPS. Therefore, extensive studies into cyber-physical security are being conducted in various domains, such as physical, network, and computing systems. Moreover, large-scale and complex CPSs make it difficult to analyze and detect cyber-physical attacks, and thus, machine learning (ML) techniques have recently been adopted for cyber-physical security. In this survey, we provide an extensive review of the threats and ML-based security designs for CPSs. First, we present a CPS structure that classifies the functions of the CPS into three layers: the physical system, the network, and software applications. Then, we discuss the taxonomy of cyber-physical attacks on each layer, and in particular, we analyze attacks based on the dynamics of the physical system. We review existing studies on detecting cyber-physical attacks with various ML techniques from the perspectives of the physical system, the network, and the computing system. Furthermore, we discuss future research directions for ML-based cyber-physical security research in the context of real-time constraints, resiliency, and dataset generation to learn about the possible attacks.

scholarly journals Modelling Exposure by Spraying Activities—Status and Future Needs

2021 ◽  
Vol 18 (15) ◽  
pp. 7737
Author(s):  
Stefan Hahn ◽  
Jessica Meyer ◽  
Michael Roitzsch ◽  
Christiaan Delmaar ◽  
Wolfgang Koch ◽  
...  
Keyword(s):  
Current Knowledge ◽  
Model Performance ◽  
Relevant Information ◽  
Systematic Evaluation ◽  
Model Accuracy ◽  
Efficient Manner ◽  
User Perspective ◽  
Model Predictions ◽  
Spray Applications

Spray applications enable a uniform distribution of substances on surfaces in a highly efficient manner, and thus can be found at workplaces as well as in consumer environments. A systematic literature review on modelling exposure by spraying activities has been conducted and status and further needs have been discussed with experts at a symposium. This review summarizes the current knowledge about models and their level of conservatism and accuracy. We found that extraction of relevant information on model performance for spraying from published studies and interpretation of model accuracy proved to be challenging, as the studies often accounted for only a small part of potential spray applications. To achieve a better quality of exposure estimates in the future, more systematic evaluation of models is beneficial, taking into account a representative variety of spray equipment and application patterns. Model predictions could be improved by more accurate consideration of variation in spray equipment. Inter-model harmonization with regard to spray input parameters and appropriate grouping of spray exposure situations is recommended. From a user perspective, a platform or database with information on different spraying equipment and techniques and agreed standard parameters for specific spraying scenarios from different regulations may be useful.

Land-uses as Quality of Making Successful Streets in Sulaimaniya City Centre, Iraq

2021 ◽  
Author(s):  
Musaab Al-Obeidy ◽  
Keyword(s):  
Global Positioning System ◽  
Structured Interview ◽  
City Centre ◽  
Key Factors ◽  
City Center ◽  
Qualitative And Quantitative ◽  
Points Of Interest ◽  
Global Positioning ◽  
Questionnaire Surveys

Although, the diverse activities and uses are one of the significant key factors to improve quality of streets, some places and shops in Mawlawi Street are disappeared or used by few number of people, while others are used by high number of people. Moreover, just some attractions and points of interest (POIs) are located in the Global Positioning System (GPS). This issues lead to lake of finding urban diversity in Mawlawi Street. This paper examines and find out the diversity of activities and uses that improves the quality of streets and makes successful streets in Sulaimaniya City Centre. It is also to identify POIs provided in GPS. The study employed a mix-methodology method. 330 questionnaire surveys, 20 semi-structured interview, and qualitative and quantitative observation, were conducted in Mawlawi Street. The results show that the diverse activities and choices are important key to make streets of Sulaimaniya City Center successful. There is also a need to define and insert many places on map for enhancing diversity. To secure the quality of the Street, this study suggests to improve the quality of goods and shops, provide night activities, and refresh some left places and shops along the Street.

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