Adaptive lookup table of arbitrary dimension

Simulink Design Optimization

The Adaptive Lookup Table (nD Stair-Fit) block creates an adaptive lookup table of arbitrary dimension by dynamically updating the underlying lookup table. The block uses the outputs of your system to do the adaptations.

Each indexing parameter may take a value within a set of adapting
data points, which are called *breakpoints. *Breakpoints
in each dimension define a *cell. *The set of all
breakpoints in one of the dimensions defines a *grid*.
In the n-dimensional case, each cell has two n breakpoints and is
an (n-1) hypersurface.

You can use the Adaptive Lookup Table (nD Stair-Fit) block to model time-varying systems with 2 or more inputs.

Doubles only

**Number of table dimensions**The number of dimensions for the adaptive lookup table.

**Table breakpoints (cell array)**A set of one-dimensional vectors that contains possible block input values for the input variables. Each input row must be monotonically increasing, but the rows do not have to be the same length. For example, if the

**Number of table dimensions**is`3`

, you can set the table breakpoints as follows:{[1 2 3], [5 7], [1 3 5 7]}

**Make initial table an input**Selecting this check box forces the Adaptive Lookup Table (nD Stair-Fit) block to ignore the

**Table data (initial)**parameter, and creates a new input port`Tin`

. Use this port to input the table data.**Table data (initial)**The initial table output values. This (n-D) array must be of size (n-1)-by-(n-1) ... -by- (n-1), (D times), where D is the number of dimensions and n is the number of input breakpoints.

**Table numbering data**Number values assigned to cells. This vector must be the same size as the table data array, and each value must be unique.

**Adaptation method**Choose

`Sample mean`

or`Sample mean with forgetting`

. Sample mean averages all the values received within a cell. Sample mean with forgetting gives more weight to the new data. How much weight is determined by the**Adaptation gain**parameter. For more information, see Selecting an Adaptation Method.**Adaptation gain (0 to 1)**A number from 0 to 1 that regulates the weight given to new data during the adaptation. A 0 means short memory (last data becomes the table value), and 1 means long memory (average all data received in a cell).

**Make adapted table an output**Selecting this check box creates an additional output port

`Tout`

for the adapted table.**Note:**The Adaptive Lookup Table (n-D Stair Fit) block cannot output a table of 3 or more dimensions.**Add adaptation enable/disable/reset port**Selecting this check box creates an additional input port

`Enable`

that enables, disables, or resets the adaptive lookup table. A signal value of`0`

applied to the port disables the adaptation, and signal value of`1`

enables the adaptation. Setting the signal value to`2`

resets the table values to the initial table data.**Add cell lock enable/disable port**Selecting this check box creates an additional input port

`Lock`

that provides the means for updating only specified cells during a simulation run. A signal value of`0`

unlocks the specified cells and signal value of`1`

locks the specified cells.**Action for out-of-range input**`Ignore`

or`Adapt`

by extrapolating beyond the extreme breakpoints.

Adaptive Lookup Table (1D Stair-Fit) | Adaptive Lookup Table (2D Stair-Fit)

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