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The following Python code can also be used to calculate and plot the root locus of the closed-loop transfer function using the Python Control Systems Library [14] and Matplotlib [15]. import control as ct import matplotlib.pyplot as plt # Define the transfer function sys = ct .
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The phrase H ∞ control comes from the name of the mathematical space over which the optimization takes place: H ∞ is the Hardy space of matrix-valued functions that are analytic and bounded in the open right-half of the complex plane defined by Re(s) > 0; the H ∞ norm is the supremum singular value of the matrix over that space.
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It is often difficult to find a control-Lyapunov function for a given system, but if one is found, then the feedback stabilization problem simplifies considerably. For the control affine system ( 2 ), Sontag's formula (or Sontag's universal formula ) gives the feedback law k : R n → R m {\displaystyle k:\mathbb {R} ^{n}\to \mathbb {R} ^{m ...
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Bode's sensitivity integral, discovered by Hendrik Wade Bode, is a formula that quantifies some of the limitations in feedback control of linear parameter invariant systems. Let L be the loop transfer function and S be the sensitivity function. In the diagram, P is a dynamical process that has a transfer function P(s).
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