MATLAB: Does the neural network predictive controller support multiple inputs

model predictive controlmpcneural networksimulink

I'm trying to implement a model predictive control system in Simulink using the NN Predictive Controller. When carrying out plant identification it only seems to let me select one input array, does it only support SISO systems?

Best Answer

I don't know the answer. However, MATLAB is a matrix/vector based language. Therefore it is hard for me to believe that if it makes sense to have multiple inputs to any device, then MATLAB would not provide a matrix/vector way to provide it.

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MATLAB: Nonlinear Model Predictive controller toolbox

Hi Cesar,

as I read through this topic, only linear MPC are available. Reason is that they are similar to a state feedback law and can be calculated fast. If you only look for nonlinear-MPC because your plant is nonlinear, Matlab helps by supplying a lot of awesome linearization tools. Recently, the MPC toolbox supports changing the linearization point during runtime so even though your model is linearized, it will be pretty close to the real solution. It is called multiple MPC:

 http://de.mathworks.com/help/mpc/ug/nonlinear-control-using-multiple-models.html

If you need a nonlinear MPC because of you needing a very special cost function or other nonlinear (cool, awesome) stuff, the Toolboxes don't help. Then you need to make your own nonlinear MPC. Be aware that such things run very slow!

MATLAB: Using NARX model with Neural Network Predictive Control

Hi Chris,

It is my understanding that you are trying to use your NARX Model in one of the Deep Learning Control System Blocks.

To import your Neural Network model, you can perform the following steps,

Double-Click on the Block > File > Import Network.

Multi-Input or (and) Multi Output systems are not supported under the Neural Network Prediction controller as of now.

When using the Model Reference Controller, the plant model and the controller model can be imported.

The plant output signal is fed back to calculate the error with the reference (in order for convergence), if the NARX estimate is used, the model may converge to the estimate value itself. In other words, if the control signal provided by your controller is same as the output of the plant, then your NARX estimate can be used as the plant output signal.

Hope this Helps

Kiran Felix Robert

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Related Solutions

MATLAB: Nonlinear Model Predictive controller toolbox

MATLAB: Using NARX model with Neural Network Predictive Control

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