Multivariable Control: System Theory and Applications
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Explores linear quadratic regulation for optimal control of linear systems, focusing on minimizing a quadratic cost function to move the system state towards zero.
Covers the computation of cost function for multivariable control systems using the LQR framework and applying gradient descent for controller improvement.
