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Programmable linear-quadratic regulator

version 1.0.0.0 (39.7 KB) by Bartlomiej Ufnalski
A feedforward neural network is used to adjust LQR gains in the case of non-stationary state matrix.

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Updated Thu, 02 Oct 2014 18:55:16 +0000

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This model demonstrates that the LQR design approach can be effectively used also for plants characterized by a non-stationary state matrix. A set of controllers is designed for different working points and an FFNN is employed to store this knowledge. The gain matrix K is then adjusted on the fly if the state matrix A changes. In the case of induction motor some entries of the state matrix A are functions of e.g. the stator flux space vector angular velocity and the slip angular velocity of the rotor. More details can be found in Neural-Network-based Programmable State Feedback Controller for Induction Motor Drive (http://dx.doi.org/10.1109/IJCNN.2006.246811). It is also advisable to get familiar with LQR basics prior to playing with this model. See e.g. http://www.mathworks.com/help/control/ref/lqr.html .

Cite As

Bartlomiej Ufnalski (2022). Programmable linear-quadratic regulator (https://www.mathworks.com/matlabcentral/fileexchange/47988-programmable-linear-quadratic-regulator), MATLAB Central File Exchange. Retrieved .

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Created with R2013a
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