The Mathworks, Inc.

Ebrahim Mehran Mestchian

Pieter Johannes Mosterman

Vijay Raghavan

Srinath Avadhanula

William James Aldrich

Vijaya Raghavan

Paul F Kinnucan

John Edward Ciolfi

Jay Ryan Torgerson

Kiran K Kintali

Alan John Moore

Denizhan N Alparslan

Peter S Szpak

Fu Zhang

Yao Ren

Anand S Krishnamoorthi

Murali K Yeddanapudi

Biao Yu

Zhi Han

Daniel Forrest Higgins

Yuan Cao

Shomit Dutta

Richard Hyde

Ravi Vompolu

Siddhartha Shankar

Ivan Garcia

Gareth Thomas

Paul Cox

Matthew J Englehart

David A Foti

Robert Olson Aberg

Mojdeh Shakeri

Nathan Edward Brewton

Kerry Eden Grand

Michael David Tocci

Andrew C Grace

William F Potter

Krishna Balasubramanian

Zsolt Kalmar

Yit Phang Khoo

Shailesh Shashikant Nirgudkar

John P Dirner

Raju Kottamadal

Jean-Yves Brunel

Srinivas Muddana

Richard M McKeever

Prahladavaradan Sampath

Mohamed Babaali

Mark Reichelt

Fazil Peermohammed

Timothy Hosey

Anjali Dattatray Joshi

Dixit Manoj Gangadhar

Sudhir Kumar

Vineeth Kartha

Janaki Sivaramakrishnan

Wurigen Bo

Yang Xu

Naman Saraf

Vivek Bhownani

Alexander C Feinman

Roy Mathew

Alon Ludwig

Emmanuel Roy

Aaron Hughes

Dekun Pei

Jianhao Du

Antoine Requet

Alexander Feinman

A method and system automatically generates a display of symbolic equations from a graphical model (or vice versa) which is readable, parametric, and interactive.

Systems and methods for interactive display of symbolic equations extracted from graphical models

Systems and methods may generate code, for a model, with one or more service access points generated and at locations in the code based on an analysis of model constraints and deployment specifications (e.g., RTE specifications or OS specifications). The systems and methods may analyze the model and identify a functionality that needs an RTE service. The system and methods may receive deployment specifications. The systems and methods may generate code for the model, where an analysis of model constraints and the deployment specifications determine which service access points are generated and where in the code the service access points are located. In an embodiment, the code may be executed by different RTEs. In an embodiment, the systems and methods may determine, based on the analysis of the model constraints and the deployment specification, one or more admissible implementations for an RTE service that may be implemented in different ways.

Systems and methods for generating service access points for RTE services in code or other RTE service information for use with the code

Systems and methods establish, activate, and deactivate variant choices within an acausal physical component model of a physical system. The systems and methods utilize variant connector blocks to establish cut points in a physical network defined by the physical model. The cut points may be programmatically controlled to activate and/or deactivate a variant choice. The variant connector blocks may include internal connections that may be programmatically controlled to be either open or closed in order to cut or include a variant choice in the acausal physical component model. Variant conditions or labels may be associated with the internal connections, and the systems and methods may evaluate the variant conditions and/or examine the labels to determine whether the internal connections are open or closed.

Systems and methods for creating variant regions in acausal simulation models

Model elements of an executable model, representing a physical system, are partitioned into one or more linear portions and one or more nonlinear portions. Simulating behavior of the physical system, by executing the model, includes, for each of multiple simulation time intervals, for a first nonlinear portion, computing a correlation matrix characterizing noise associated with one or more ports of the model. A scattering matrix corresponds to a portion of the physical system represented by the first nonlinear portion without accounting for any noise within the portion of the physical system. The correlation matrix is derived from the scattering matrix based on noise within the portion of the physical system. Noise sources representing noise within the portion of the physical system are identified based on the correlation matrix. At least one characteristic of noise associated with each noise source is computed, and noise characteristics are output at selected ports.

Estimating noise characteristics in physical system simulations

A solver may generate a system of equations for an acausal model. A partitioning engine may transform at least some of the equations into groups of equations whose inputs/outputs are connected directly. The partitioning engine may transform at least some of the equations into groups of linear equations and/or groups of switched linear equations that are connected through nonlinear functions. The solver may determine input-output relationships of the groups of equations. A simulation model generator that may include a library of types of model elements may construct a causal simulation model.

Systems and methods for generating code for computer-based physical models

A method may comprise determining, by executing a first model having first configuration parameters, a first result associated with the first model. The method may comprise determining, by executing a second model having second configuration parameters, a second result associated with the second model. The method may comprise determining, based on the first result, the second result, and equivalency criteria, that the second model is not functionally equivalent to the first model. The equivalency criteria may indicate that the second model is functionally equivalent to the first model when a difference between the second result and the first result satisfies a threshold. The method may comprise modifying a configuration parameter, of the second configuration parameters, to cause the second model to improve toward functional equivalence with the first model.

Determining functional equivalence of configurations of a model

A device may analyze, by one or more processors, a model to identify a first set of model elements that are associated with a model element. The device may apply, by the one or more processors, one or more results from an analysis of the model to a first network unit to determine a complexity of the first network unit or a coupling of the first network unit to other model elements of the model. The device may generate, by the one or more processors, a second network unit, representing a second hierarchy of computation, from the first network unit based on the complexity or the coupling. The device may provide, by the one or more processors, the second network unit as a testing unit for testing the model, the second network unit comprising two or more model elements and one or more numeric expressions.

Method and system for improving efficacy of model verification by model partitioning

Systems and methods for coverage analysis using context information are described. The systems and methods can be used to obtain program code and test information for testing the program code, the test information associated with context information for providing context for testing the program code. Coverage information can be generated by testing the program code according to the test information. A first association can be generated between the context information and the test information. A second association can be generated between the context information and the program code. A third association can be generated between the coverage information and the test information. A subset of the coverage information can be determined based on the third association and a fourth association between the test information and the program code determined based on the first and second associations. An indication of the subset of the coverage information can be displayed.

Refining coverage analyses using context information

Systems and methods for syntactical change-resistant code generation are described. A code generator can generate syntactical change-resistant code from original code and new code, where the new code may be intended as a replacement or update for the original code. The code generator can determine, for code portions and/or sub-portions of the new code, whether or not semantic, syntactic, and structural differences from the original code exist. The code generator can generate the syntactical change-resistant code to leverage and include in the syntactical change-resistant code portions and sub-portions of the original code that have been used and tested, so as to improve reliability of the syntactical change-resistant code.

Syntactical change-resistant code generation

Processing external code includes: parsing the external code to identify a first semantic entity, mapping the first semantic entity to a second semantic entity, the first semantic entity comprising a first set of one or more specified attributes and the second semantic entity comprising a second set of one or more attributes that are capable of being specified, determining that a first attribute of the second set of one or more attributes does not have a corresponding specified attribute within the first set of one or more specified attributes, determining available information for specifying the first attribute of the second set of one or more attributes, and storing the second semantic entity in association with the first attribute of the second set of one or more attributes specified based on user selection or specifying the first attribute in response to available information provided to a user interface system.

External code integrations within a computing environment

Embodiments include techniques for estimating unknown or missing values for parameters of a motor based on high-level motor information and using the estimated parametric values in generating an executable model for modeling the behavior of the motor. An aspect of the techniques involves assumptions used to establish the predetermined parametric values that are applied to the algorithm for deriving estimates of the unknown parametric values for the motor. The estimated parametric values may then be used in the executable model of the motor to enable development and simulation of a plant (e.g., a closed loop system) including a plant model having a dynamic controller model and a lumped parameter model of a modeling environment of a technical computing environment executing on a data processing system. The simulation of the plant loop can be sufficient to test the dynamic (e.g., feedback-based) controller within a closed loop system, e.g., test motion control of a motorized vehicle seat.

Systems and method for parameter estimation for a permanent magnet synchronous machine

A computer-based model having executable semantics may be used to simulate the behavior of a system. A substructure of interest is sliced from the model and analyzed to determine a transformation of the slice while preserving some context of the model. The transformed slice may be further manipulated outside of the model, integrated back into the model in place of the original slice, or used in other ways.

Model structure analysis with integration of transformed slice

A system and method generates contextual information for a source model. An identification of one or more first model elements of interest within the source model may be received. One or more constraints on inputs of selected model elements also may be received. A scope of analysis regarding outputs of the first model elements may be specified. The contextual information may be derived automatically for the one or more first model elements. The contextual information may include one or more model elements, signals, or states that are contained with the scope of analysis while execution of the source model is limited by the one or more constraints. The derived contextual information may be provided to an output device.

Deriving contextual information for an execution constrained model

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Newton, MA, United States of America

Ebrahim Mehran Mestchian