Generate linear models in base workspace at specific times
This block calls linmod or dlinmod to create a linear model for the system when the simulation clock reaches the time specified by the Linearization time parameter. No trimming is performed. The linear model is stored in the base workspace as a structure, along with information about the operating point at which the snapshot was taken. Multiple snapshots are appended to form an array of structures.
The block sets the following model parameters to the indicated values:
BufferReuse = 'off'
RTWInlineParameters = 'on'
BlockReductionOpt = 'off'
The name of the structure used to save the snapshots is the name of the model appended by _Timed_Based_Linearization, for example, vdp_Timed_Based_Linearization. The structure has the following fields:
The A matrix of the linearization
The B matrix of the linearization
The C matrix of the linearization
The D matrix of the linearization
Names of the model's states
Names of the model's output ports
Names of the model's input ports
A structure that specifies the operating point of the linearization. The structure specifies the operating point time (OperPoint.t). The states (OperPoint.x) and inputs (OperPoint.u) fields are not used.
The sample time of the linearization for a discrete linearization
Use the Trigger-Based Linearization block if you need to generate linear models conditionally.
You can use state and simulation time logging to extract the model states and inputs at operating points. For example, suppose that you want to get the states of the f14 example model at linearization times of 2 seconds and 5 seconds.
At the end of the simulation, the following variables appear in the MATLAB® workspace: f14_Timed_Based_Linearization, tout, and xout.
ind1 = find(f14_Timed_Based_Linearization(1).OperPoint.t==tout); ind2 = find(f14_Timed_Based_Linearization(1).OperPoint.t==tout);
x1 = xout(ind1,:); x2 = xout(ind2,:);
Time at which you want the block to generate a linear model. Enter a vector of times if you want the block to generate linear models at more than one time step.
Specify a sample time to create discrete-time linearizations of the model (see Discrete-Time System Linearization).