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taksug | Methods

class for implementing the taksug fuzzy functions

Syntax

    m=taksug(varargin)

    m=taksug(taksug_obj)

    m=taksug(structure)

    m=taksug(name, n_inputs, n_outputs)

Description

`m=taksug(varargin)` returns an empty taksug object.

`m=taksug(taksug_obj)` returns a copy of the `taksug_obj` object.

`m=taksug(structure)` initializes a new taksug object with the appropriate fields set according to the values defined in the fields of `structure`.

`m=taksug(name, n_inputs, n_outputs)` initializes a new taksug object called `name`, with number of inputs `n_inputs` and number of outputs `n_outputs`.

Remarks

The taksug class is a child of the mapping class and allows the definition of a static system using a fuzzy rule based Takagi-Sugeno (TS) representation. The class inherits all the fields of the mapping class and defined a series of new attibutes required for implementing the TS representation of a model. At the top level the following fields are defined:

- `n_rules` defines the number of fuzzy rules of the model
- `model_code` defines the structure of the fuzzy rules
- `centers` position of the center of each rule
- `ivariances` inverse of the projected covariance matrix of the cluster associated to each rule. In other words, it is the quadratic matrix defining the local metric (or the shape) of the rule
- `linears` hyperplane associated to each rule (consequence of the rule)
- `m` index of the fuzzyness of the model
- `mfs` description of the fuzzy sets while they are defined along each dimension.
- `rls` description of the rules base.

Methods

- add_rules adds specified number of rules
- add_sets Add fuzzy sets along one or more dimensions of the input space
- check checks the consistency of all the field of a taksug object
- denormalize denormalizes the model
- display Display an object of class taksug
- drawcontrols Draw controls which allow to control the plot behaviour
- eval computes the value of the model
- fit_linears identifies the consequent part of a fuzzy model from data
- get gets the value of the attribute of an object
- identify identifies a fuzzy model from data
- interp_model Computes a local fuzzy combination of the consequents of the rules
- jacob_inputs computes the jacobian of the model
- jacob_params computes the jacobian of the model
- lev_marq Performs a Levenbergh Marquardt optimisation of the mapping
- membership returns the membership of a rule
- normalise normalises the model M
- plot performs a plot of the a taksug model
- plot performs a plot of the a taksug model
- rem_rules remove the specified rules from the taksug object
- set set object properties
- sets_grid Remove every fuzzy sets and replace them by evenly spaced ones

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