Fuzzy Logic Tools (FLT) namespace. More...

Classes
class	Anymf
	Any Membership function. More...

class	Constmf
	Constant Membership function. More...

class	Gauss2mf
	Double gaussian Membership function. More...

class	Gaussmf
	Gaussian Membership function. More...

class	GBellmf
	Bell Membership function. More...

class	Membership
	This class contains methods and attributes common to all Membership functions. More...

class	Pimf
	Pi (S-Z) Membership function. More...

class	PSigmf
	Product of sigmoidals Membership function. More...

class	Rule
	This class contains methods and attributes common to fuzzy Rules. More...

class	Sig2mf
	Difference of sigmoidals Membership function. More...

class	Sigmf
	Sigmoidal Membership function. More...

class	Smf
	S Membership function. More...

class	System
	This class contains methods and attributes common to fuzzy Systems. More...

class	Trapmf
	Trapezoidal Membership function. More...

class	Trimf
	Triangular Membership function. More...

class	Zmf
	Z Membership function. More...

Enumerations
enum	TYPE_MF { ANYMF = 0, CONSTMF, GAUSSMF, GAUSS2MF, GBELLMF, PIMF, PSIGMF, SMF, SIGMF, SIG2MF, TRAPMF, TRIMF, ZMF }
	Enumeration with the implemented Membership functions. More...

Functions
TNT::Array2D< double >	jacobian (System &S, const double const x, const double const u, TNT::Array2D< double > &B, TNT::Array1D< double > &F)
	Computes the open-loop jacobian matrix in `x` for the Plant `S`. More...

TNT::Array2D< double >	jacobian (System &S, System &C, const double *const x)
	Computes the closed-loop jacobian matrix in `x` for the Plant `S` and the Controller `C`. More...

TNT::Array2D< double >	jacobianAprox (System &S, System &C, const double *const x, double h=0.001)
	Computes the approximation of the closed-loop jacobian matrix in `x` for the Plant `S` and the Controller `C` using finite differences with a step `h`. More...

TNT::Array2D< double >	jacobianAprox (System &S, const double const x, const double const u, TNT::Array2D< double > &B, TNT::Array1D< double > &F, double h=0.001)
	Computes the approximation of the open-loop jacobian matrix in `x` for the Plant `S` using finite differences with a step `h`. More...

double	derconseq (System &S, double *x, size_t output, size_t rule, size_t parameter, int &error)
	Obtains the derivative of a fuzzy model with respect to a consequent. More...

TNT::Array2D< double >	derconseq (System &S, double *x)
	Obtains the jacobian matrix of a fuzzy model with respect to its consequents. More...

TNT::Array2D< double >	deraffine (System &S, double *x)
	Obtains the jacobian matrix of a fuzzy model with respect to its affine consequents. More...

double	derantec (System &S, double *x, size_t input, size_t output, size_t rule, size_t parameter, int &error)
	Obtains the derivative of a fuzzy model with respect to a parameter of an antecedent. More...

TNT::Array2D< double >	derantec (System &S, double *x)
	Obtains the jacobian matrix of a fuzzy model with respect to its antecedents. More...

TNT::Array2D< double >	derfuzzy (System &S, double *x)
	Obtains the jacobian matrix of a fuzzy model with respect to all of its parameters. More...

TNT::Array2D< double >	derCLFSconseq (System &P, System &C, const double *const x)
	Obtains the jacobian matrix of a Closed Loop Fuzzy System (CLFS) with respect to the consequents of the fuzzy controller This implementation does not provide for the inclusion of the control signal in the antecedents of the plant. More...

TNT::Array1D< double >	KalmanAntec (System &Model, TNT::Array1D< double > &input, TNT::Array1D< double > &output, TNT::Array2D< double > &covariance, TNT::Array2D< double > &P, TNT::Array2D< double > &Phi)
	Computes antecedets adjust by the discrete extended Kalman filter. More...

TNT::Array1D< double >	KalmanAntec (System &Model, TNT::Array1D< double > &input, TNT::Array1D< double > &output, TNT::Array2D< double > &covariance, TNT::Array2D< double > &P)
	Computes antecedets adjust by the discrete extended Kalman filter where Phi is assumed to be the identity matrix. More...

TNT::Array1D< double >	KalmanConseq (System &Model, TNT::Array1D< double > &input, TNT::Array1D< double > &output, TNT::Array2D< double > &covariance, TNT::Array2D< double > &P, TNT::Array2D< double > &Phi)
	Computes consequents adjust by the discrete extended Kalman filter. More...

TNT::Array1D< double >	KalmanConseq (System &Model, TNT::Array1D< double > &input, TNT::Array1D< double > &output, TNT::Array2D< double > &covariance, TNT::Array2D< double > &P)
	Computes consequents adjust by the discrete extended Kalman filter where Phi is assumed to be the identity matrix. More...

TNT::Array1D< double >	KalmanFuz (System &Model, TNT::Array1D< double > &input, TNT::Array1D< double > &output, TNT::Array2D< double > &covariance, TNT::Array2D< double > &P, TNT::Array2D< double > &Phi)
	Computes the simultaneous adjustment of antecedets and consequents by the discrete extended Kalman filter. More...

TNT::Array1D< double >	KalmanFuz (System &Model, TNT::Array1D< double > &input, TNT::Array1D< double > &output, TNT::Array2D< double > &covariance, TNT::Array2D< double > &P)
	Computes the simultaneous adjustment of antecedets and consequents by the discrete extended Kalman filter where Phi is assumed to be the identity matrix. More...

int	sign (double x)
	Implementation of the sign function. More...

Membership *	createMF (TYPE_MF t)
	Virtual constructor for Membership functions. More...

int	System2TXT (System &S, const char *file)
	Saves the fuzzy System `S` in a text file. More...

System	TXT2System (const char *file)
	Reads a fuzzy System from a text file. More...

int	printSystem (const char file, System &S, char inputs[]=NULL, char *outputs[]=NULL, int accuracy=10)
	Writes a fuzzy system in its linguistic form. More...

TNT::Array1D< double >	evaluate (const double *const point, System &S, System &C)
	Evaluates a closed loop fuzzy system in the given `point`. More...

System	initialController (System &Plant)
	Creates a fuzzy Controller from a given plant. More...

System	subSystem (System &S, size_t nrules, size_t outputs, size_t rules)
	Extracts a subsystem from a fuzzy System. More...

TNT::Array2D< double >	extractPoints (System &S, unsigned int numMeshPoints=5, double precision=1E-3, bool addMesh=false, bool onlyStatePoints=true)
	Extracts the representative points of a fuzzy system. More...

void	col2row_major (const double const colM, double rowM, size_t num_rows, size_t num_cols)
	Converts a column-major matrix in a row-major one. More...

TNT::Array2D< double >	col2row_major (const double *const colM, size_t num_rows, size_t num_cols)
	Converts a column-major matrix in a row-major one. More...

void	row2col_major (const double const rowM, double colM, size_t num_rows, size_t num_cols)
	Converts a row-major matrix in a column-major one. More...

int	readModel (const mxArray *model, System &S)
	Reads a Fuzzy Model (TXT, FIS file or FIS variable) More...

int	FIS2System (const mxArray *FIS, System &S)
	Reads the Fuzzy Model from a FIS variable. More...

int	System2FIS (System &S, mxArray *FIS)
	Writes the Fuzzy Model in a FIS variable. More...

Variables
static const char *	MF_NAMES []
	Names of the Membership functions. More...

static const size_t	MF_PARAM_NUMBER []
	Initial number of parameters of each Membership function in FLT::TYPE_MF. More...

Detailed Description

Fuzzy Logic Tools (FLT) namespace.

Enumeration Type Documentation

enum FLT::TYPE_MF

Enumeration with the implemented Membership functions.

FLT::TYPE_MF is used to determinate the Membership function type, FLT::MF_NAMES are the names of the Membership functions, and FLT::MF_PARAM_NUMBER are the initial number of parameters of the Membership functions.

Remarks: FLT::TYPE_MF, FLT::MF_NAMES and FLT::MF_PARAM_NUMBER must be consistent.; Important: If the first or last element of FLT::TYPE_MF are changed, you needd to check membership.cpp (and perhaps others files), because these elements are used to make some comparisons.

Enumerator
ANYMF	Any Membership function (FLT::Anymf).
CONSTMF	Constant Membership function (FLT::Constmf).
GAUSSMF	Gaussian Membership function (FLT::Gaussmf).
GAUSS2MF	Double gaussian Membership function (FLT::Gauss2mf).
GBELLMF	Bell Membership function (FLT::GBellmf).
PIMF	Pi (S-Z) Membership function (FLT::Pimf).
PSIGMF	Product of sigmoidals Membership function (FLT::PSigmf).
SMF	S Membership function (FLT::Smf).
SIGMF	Sigmoidal Membership function (FLT::Sigmf).
SIG2MF	Difference of sigmoidals Membership function (FLT::Sig2mf).
TRAPMF	Trapezoidal Membership function (FLT::Trapmf).
TRIMF	Triangular Membership function (FLT::Trimf).
ZMF	Z Membership function (FLT::Zmf).

Function Documentation

void FLT::col2row_major	(	const double *const	colM,
		double *	rowM,
		size_t	num_rows,
		size_t	num_cols
	)

inline

Converts a column-major matrix in a row-major one.

MATLAB© uses column-major matrices, but C uses row-major.

Examples:: matlab_utilities/Kalmanantec.cpp, matlab_utilities/Kalmanconseq.cpp, and matlab_utilities/Kalmanfuz.cpp.

TNT::Array2D<double> FLT::col2row_major	(	const double *const	colM,
		size_t	num_rows,
		size_t	num_cols
	)

inline

Converts a column-major matrix in a row-major one.

MATLAB© uses column-major matrices, but C uses row-major.

Membership * FLT::createMF ( TYPE_MF t )

Virtual constructor for Membership functions.

This function create and return a Membership function of the selected type.

TNT::Array2D< double > FLT::deraffine	(	System &	S,
		double *	x
	)

Obtains the jacobian matrix of a fuzzy model with respect to its affine consequents.

Returns: Returns an empty array if error.

Examples:: matlab_utilities/fuzderaffine.cpp.

double FLT::derantec	(	System &	S,
		double *	x,
		size_t	input,
		size_t	output,
		size_t	rule,
		size_t	parameter,
		int &	error
	)

Obtains the derivative of a fuzzy model with respect to a parameter of an antecedent.

It is assumed that the output of the system is the same as the parameter, otherwise it should be considered derivative equal to 0.

Returns: If output, rule or parameter are out of System limits, the function returns 0 and error = 1.

Examples:: matlab_utilities/fuzderantec.cpp.

TNT::Array2D< double > FLT::derantec	(	System &	S,
		double *	x
	)

Obtains the jacobian matrix of a fuzzy model with respect to its antecedents.

Returns: Returns an empty array if error.

TNT::Array2D<double> FLT::derCLFSconseq	(	System &	P,
		System &	C,
		const double *const	x
	)

Obtains the jacobian matrix of a Closed Loop Fuzzy System (CLFS) with respect to the consequents of the fuzzy controller This implementation does not provide for the inclusion of the control signal in the antecedents of the plant.

Returns: Returns an empty array if error.

double FLT::derconseq	(	System &	S,
		double *	x,
		size_t	output,
		size_t	rule,
		size_t	parameter,
		int &	error
	)

Obtains the derivative of a fuzzy model with respect to a consequent.

It is assumed that the output of the system is the same as the parameter, otherwise it should be considered derivative equal to 0.

Returns: If output, rule or parameter are out of System limits, the function returns 0 and error = 1.

Examples:: matlab_utilities/fuzderaffine.cpp, and matlab_utilities/fuzderconseq.cpp.

TNT::Array2D< double > FLT::derconseq	(	System &	S,
		double *	x
	)

Obtains the jacobian matrix of a fuzzy model with respect to its consequents.

Returns: Returns an empty array if error.

TNT::Array2D< double > FLT::derfuzzy	(	System &	S,
		double *	x
	)

Obtains the jacobian matrix of a fuzzy model with respect to all of its parameters.

Returns: Returns an empty array if error.

Examples:: matlab_utilities/fuzderparam.cpp.

Array1D< double > FLT::evaluate	(	const double *const	point,
		System &	S,
		System &	C
	)

Evaluates a closed loop fuzzy system in the given point.

S is the plant and C is a fuzzy controller.

Returns: Returns an empty array if error.

Examples:: example.cpp, and matlab_utilities/fuzeval.cpp.

Array2D< double > FLT::extractPoints	(	System &	S,
		unsigned int	numMeshPoints = `5`,
		double	precision = `1E-3`,
		bool	addMesh = `false`,
		bool	onlyStatePoints = `true`
	)

Extracts the representative points of a fuzzy system.

Parameters

S	Is a fuzzy System.
numMeshPoints	Is used in Memberships functions without significative points, like ANYMF, CONSTMF, SMF, ...
precision	Is used to remove similar points.
addMesh	If `addMesh` is true, a mesh of `numMeshPoints` for each dimmension will be added to System points.
onlyStatePoints	If `onlyStatePoints` is true, this function only extracts the state vector points, not the control vector points.

Examples:: matlab_utilities/extractPoints.cpp.

int FLT::FIS2System	(	const mxArray *	FIS,
		System &	S
	)

Reads the Fuzzy Model from a FIS variable.

Returns 0 if no errors.

System FLT::initialController ( System & Plant )

Creates a fuzzy Controller from a given plant.

The fuzzy controller will have all the rules that the plant owns in each of its outputs.
Consequents all initialized to 0.

Returns: Returns an empty System if error.

Examples:: matlab_utilities/initializeController.cpp.

Array2D< double > FLT::jacobian	(	System &	S,
		const double *const	x,
		const double *const	u,
		TNT::Array2D< double > &	B,
		TNT::Array1D< double > &	F
	)

Computes the open-loop jacobian matrix in x for the Plant S.

Obtains the linearization $\mathbf{f}(\mathbf{x},\mathbf{u}) \approx \mathbf{F} + \mathbf{A x} + \mathbf{Bu}$ .

Returns: Returns the dynamic matrix, $\mathbf{A}$ , or an empty array if error.

Examples:: example.cpp, matlab_utilities/fuzderparam.cpp, matlab_utilities/fuzjac.cpp, and matlab_utilities/fuzlinear.cpp.

TNT::Array2D< double > FLT::jacobian	(	System &	S,
		System &	C,
		const double *const	x
	)

Computes the closed-loop jacobian matrix in x for the Plant S and the Controller C.

Returns: Returns the jacobian matrix or an empty array if error.

TNT::Array2D< double > FLT::jacobianAprox	(	System &	S,
		System &	C,
		const double *const	x,
		double	h = `0.001`
	)

Computes the approximation of the closed-loop jacobian matrix in x for the Plant S and the Controller C using finite differences with a step h.

Returns: Returns an empty array if error.

Examples:: matlab_utilities/aproxjac.cpp, and matlab_utilities/aproxlinear.cpp.

TNT::Array2D< double > FLT::jacobianAprox	(	System &	S,
		const double *const	x,
		const double *const	u,
		TNT::Array2D< double > &	B,
		TNT::Array1D< double > &	F,
		double	h = `0.001`
	)

Computes the approximation of the open-loop jacobian matrix in x for the Plant S using finite differences with a step h.

Obtains the linearization $\mathbf{f}(\mathbf{x},\mathbf{u}) \approx \mathbf{F} + \mathbf{A x} + \mathbf{Bu}$ .

Returns: Returns the dynamic matrix, $\mathbf{A}$ , or an empty array if error.

TNT::Array1D< double > FLT::KalmanAntec	(	System &	Model,
		TNT::Array1D< double > &	input,
		TNT::Array1D< double > &	output,
		TNT::Array2D< double > &	covariance,
		TNT::Array2D< double > &	P,
		TNT::Array2D< double > &	Phi
	)

Computes antecedets adjust by the discrete extended Kalman filter.

Parameters

Model	Is the fuzzy system whose antecedents will be adjusted.
input	Is the input applied to the system in the current iteration.
output	Is the real output of the system in the current iteration.
covariance	Is the noise covariance matrix estimated from the hope operator.
P	Is the covariance matrix of the filter.
Phi	Is the Jacobian matrix that relates the parameters to be set with the following value of these parameters. Usually this will be an identity matrix of appropriate dimensions.

Returns: Returns the error vector of the iteration, or an empty vector if there was some error.

Model and P will be changed according to the Kalman discrete filte algorithm.

Examples:: matlab_utilities/Kalmanantec.cpp.

TNT::Array1D< double > FLT::KalmanAntec	(	System &	Model,
		TNT::Array1D< double > &	input,
		TNT::Array1D< double > &	output,
		TNT::Array2D< double > &	covariance,
		TNT::Array2D< double > &	P
	)

Computes antecedets adjust by the discrete extended Kalman filter where Phi is assumed to be the identity matrix.

Parameters

Model	Is the fuzzy system whose antecedents will be adjusted.
input	Is the input applied to the system in the current iteration.
output	Is the real output of the system in the current iteration.
covariance	Is the noise covariance matrix estimated from the hope operator.
P	Is the covariance matrix of the filter.

Returns: Returns the error vector of the iteration, or an empty vector if there was some error.

Model and P will be changed according to the Kalman discrete filte algorithm.

TNT::Array1D< double > FLT::KalmanConseq	(	System &	Model,
		TNT::Array1D< double > &	input,
		TNT::Array1D< double > &	output,
		TNT::Array2D< double > &	covariance,
		TNT::Array2D< double > &	P,
		TNT::Array2D< double > &	Phi
	)

Computes consequents adjust by the discrete extended Kalman filter.

Parameters

Model	Is the fuzzy system whose consequents will be adjusted.
input	Is the input applied to the system in the current iteration (current State vector, x(k)).
output	Is the real output of the system in the current iteration.
covariance	Is the noise covariance matrix estimated from the hope operator.
P	Is the covariance matrix of the filter.
Phi	Is the Jacobian matrix that relates the parameters to be set with the following value of these parameters. Usually this will be an identity matrix of appropriate dimensions.

Returns: Returns the error vector of the iteration, or an empty vector if there was some error.

Model and P will be changed according to the Kalman discrete filte algorithm.

Examples:: matlab_utilities/Kalmanconseq.cpp.

TNT::Array1D< double > FLT::KalmanConseq	(	System &	Model,
		TNT::Array1D< double > &	input,
		TNT::Array1D< double > &	output,
		TNT::Array2D< double > &	covariance,
		TNT::Array2D< double > &	P
	)

Computes consequents adjust by the discrete extended Kalman filter where Phi is assumed to be the identity matrix.

Parameters

Model	Is the fuzzy system whose consequents will be adjusted.
input	Is the input applied to the system in the current iteration (current State vector, x(k)).
output	Is the real output of the system in the current iteration.
covariance	Is the noise covariance matrix estimated from the hope operator.
P	Is the covariance matrix of the filter.

Returns: Returns the error vector of the iteration, or an empty vector if there was some error.

Model and P will be changed according to the Kalman discrete filte algorithm.

TNT::Array1D< double > FLT::KalmanFuz	(	System &	Model,
		TNT::Array1D< double > &	input,
		TNT::Array1D< double > &	output,
		TNT::Array2D< double > &	covariance,
		TNT::Array2D< double > &	P,
		TNT::Array2D< double > &	Phi
	)

Computes the simultaneous adjustment of antecedets and consequents by the discrete extended Kalman filter.

Parameters

Model	Is the fuzzy system whose parameters will be adjusted.
input	Is the input applied to the system in the current iteration.
output	Is the real output of the system in the current iteration.
covariance	Is the noise covariance matrix estimated from the hope operator.
P	Is the covariance matrix of the filter.
Phi	Is the Jacobian matrix that relates the parameters to be set with the following value of these parameters. Usually this will be an identity matrix of appropriate dimensions.

Returns: Returns the error vector of the iteration, or an empty vector if there was some error.

Model and P will be changed according to the Kalman discrete filte algorithm.

Examples:: matlab_utilities/Kalmanfuz.cpp.

TNT::Array1D< double > FLT::KalmanFuz	(	System &	Model,
		TNT::Array1D< double > &	input,
		TNT::Array1D< double > &	output,
		TNT::Array2D< double > &	covariance,
		TNT::Array2D< double > &	P
	)

Computes the simultaneous adjustment of antecedets and consequents by the discrete extended Kalman filter where Phi is assumed to be the identity matrix.

Parameters

Model	Is the fuzzy system whose parameters will be adjusted.
input	Is the input applied to the system in the current iteration.
output	Is the real output of the system in the current iteration.
covariance	Is the noise covariance matrix estimated from the hope operator.
P	Is the covariance matrix of the filter.

Returns: Returns the error vector of the iteration, or an empty vector if there was some error.

Model and P will be changed according to the Kalman discrete filte algorithm.

int FLT::printSystem	(	const char *	file,
		System &	S,
		char *	inputs[] = `NULL`,
		char *	outputs[] = `NULL`,
		int	accuracy = `10`
	)

Writes a fuzzy system in its linguistic form.

"IF temperature is high and pressure is ... THEN valve is ..."

You can specify the name of the variables and the number of decimals that will be used to represent the system.

Examples:: matlab_utilities/fuzprint.cpp.

int FLT::readModel	(	const mxArray *	model,
		System &	S
	)

Reads a Fuzzy Model (TXT, FIS file or FIS variable)

Returns 0 if no errors.

Examples:: matlab_utilities/activation.cpp, matlab_utilities/antec2mat.cpp, matlab_utilities/aproxjac.cpp, matlab_utilities/aproxlinear.cpp, matlab_utilities/conseq2mat.cpp, matlab_utilities/extractPoints.cpp, matlab_utilities/fis2txt.cpp, matlab_utilities/fuz2mat.cpp, matlab_utilities/fuzcomb.cpp, matlab_utilities/fuzderaffine.cpp, matlab_utilities/fuzderantec.cpp, matlab_utilities/fuzderconseq.cpp, matlab_utilities/fuzderparam.cpp, matlab_utilities/fuzeval.cpp, matlab_utilities/fuzjac.cpp, matlab_utilities/fuzlinear.cpp, matlab_utilities/fuzprint.cpp, matlab_utilities/fuzsubsystem.cpp, matlab_utilities/initializeController.cpp, matlab_utilities/Kalmanantec.cpp, matlab_utilities/Kalmanconseq.cpp, matlab_utilities/Kalmanfuz.cpp, matlab_utilities/mat2antec.cpp, matlab_utilities/mat2conseq.cpp, and matlab_utilities/mat2fuz.cpp.

void FLT::row2col_major	(	const double *const	rowM,
		double *	colM,
		size_t	num_rows,
		size_t	num_cols
	)

inline

Converts a row-major matrix in a column-major one.

Examples:: matlab_utilities/Kalmanantec.cpp, matlab_utilities/Kalmanconseq.cpp, and matlab_utilities/Kalmanfuz.cpp.

int FLT::sign ( double x )

inline

Implementation of the sign function.

Returns: Returns 0 if x=0, 1 if x>0 and -1 if x<0.

System FLT::subSystem	(	System &	S,
		size_t	nrules,
		size_t *	outputs,
		size_t *	rules
	)

Extracts a subsystem from a fuzzy System.

Returns: Returns an empty System if error.

Examples:: matlab_utilities/fuzsubsystem.cpp.

int FLT::System2FIS	(	System &	S,
		mxArray *	FIS
	)

Writes the Fuzzy Model in a FIS variable.

Returns 0 if no errors.

Examples:: matlab_utilities/fuzcomb.cpp, matlab_utilities/fuzsubsystem.cpp, matlab_utilities/initializeController.cpp, matlab_utilities/Kalmanantec.cpp, matlab_utilities/Kalmanconseq.cpp, matlab_utilities/Kalmanfuz.cpp, matlab_utilities/mat2antec.cpp, matlab_utilities/mat2conseq.cpp, matlab_utilities/mat2fuz.cpp, and matlab_utilities/txt2fis.cpp.

int FLT::System2TXT	(	System &	S,
		const char *	file
	)

Saves the fuzzy System S in a text file.

Returns: Returns 0 if no errors.

See also: See TXT2System to see the template for the TXT file.

Examples:: matlab_utilities/fis2txt.cpp, and matlab_utilities/fuzcomb.cpp.

System FLT::TXT2System ( const char * file )

Reads a fuzzy System from a text file.

Returns: Returns an empty System if error.

Template for the TXT file: The text in italics is only helpful, should not appear in the template.

'Number of inputs' 'Number of outputs' 'Number of rules for the 1st ouput' 'Number of rules for the 2nd ouput' ...

Rules: For each output, for each rule in this output:
Antecedents. For each input:
'Type membership function' 'Parameters separated by spaces'
Consequents:
'Affine term' and for each input 'consequents terms separated by spaces' 'lower limit for input 1' 'upper limit for input 1' 'lower limit for input 2' 'upper limit for input 2'
... for all the inputs

'lower limit for output 1' 'upper limit for output 1' 'lower limit for output 2' 'upper limit for output 2'
... for all the outputs

Examples:: example.cpp, and matlab_utilities/txt2fis.cpp.

Variable Documentation

FLT::MF_NAMES

static

Initial value:

=
  {
    "ANYMF",
    "CONSTMF",
    "GAUSSMF",
    "GAUSS2MF",
    "GBELLMF",
    "PIMF",
    "PSIGMF",
    "SMF",
    "SIGMF",
    "SIG2MF",
    "TRAPMF",
    "TRIMF",
    "ZMF"
  }

Names of the Membership functions.

Remarks: FLT::TYPE_MF, FLT::MF_NAMES and FLT::MF_PARAM_NUMBER must be consistent.

FLT::MF_PARAM_NUMBER

static

Initial value:

Initial number of parameters of each Membership function in FLT::TYPE_MF.

Remarks: These values are used for initialization, in the code is better use the num_params function from Membership class.; FLT::TYPE_MF, FLT::MF_NAMES and FLT::MF_PARAM_NUMBER must be consistent.

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