Algebraic Constraint

Constrain input signal

• Library:

• Description

The Algebraic Constraint block constrains the input signal f(z) to z or 0 and outputs an algebraic state z. The block outputs a value that produces 0 or z at the input. The output must affect the input through a direct feedback path. In other words, the feedback path only contains blocks with direct feedthrough. For example, you can specify algebraic equations for index 1 differential-algebraic systems (DAEs).

Ports

Input

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Signal is subjected to the constraint f(z) = 0 or f(z) = z to solve the algebraic loop.

Data Types: double

Output

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Solution to the algebraic loop when the input signal f(z) is subjected to the constraint f(z) = 0 or f(z) = z.

Data Types: double

Parameters

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Type of constraint for which to solve. You can solve for f(z) = 0 or f(z) = z

Programmatic Use

 Block Parameter: Constraint Type: character vector Values: 'f(z) = 0' | 'f(z) = z' Default: 'f(z) = 0'

Choose between the Trust region ,  or Line search  algorithms to solve the algebraic loop. By default this value is set to auto, which selects the algebraic loop solver based on the model configuration and switches the solver between the Trust region and Line search algorithm during simulation

Programmatic Use

 Block Parameter: Solver Type: character vector Values: 'auto' | 'Trust region' | 'Line search' Default: 'auto'

This option is visible when you explicitly specify a solver to be used (Trust region or Line Search) in the Solver drop-down menu. Specify a smaller value for higher accuracy or a larger value for faster execution. By default it is set to auto.

Programmatic Use

 Block Parameter: Tolerance Type: character vector Values: 'auto' | positive scalar Default: 'auto'

Initial guess for the algebraic state z that is close to the expected solution value to improve the efficiency of the algebraic loop solver. By default, this value is set to 0

Programmatic Use

 Block Parameter: InitialGuess Type: character vector Values: scalar Default: '0'

Block Characteristics

 Data Types double Direct Feedthrough no Multidimensional Signals no Variable-Size Signals no Zero-Crossing Detection no

 Garbow, B. S., K. E. Hillstrom, and J. J. Moré. User Guide for MINPACK-1. Argonne, IL: Argonne National Laboratory, 1980.

 Rabinowitz, P. H. Numerical Methods for Nonlinear Algebraic Equations. New York: Gordon and Breach, 1970.

 Kelley, C. T. Iterative Methods for Linear and Nonlinear Equations. Society for Industrial and Applied Mathematics, Philadelphia, PA: 1995.