Update Content - 2024-12-17

content/phdthesis/monkhorst04_dynam_error_budget.md

@@ -106,7 +106,7 @@ Find a controller \\(C\_{\mathcal{H}\_2}\\) which minimizes the \\(\mathcal{H}\_
 
 In order to synthesize an \\(\mathcal{H}\_2\\) controller that will minimize the output error, the total system including disturbances needs to be modeled as a system with zero mean white noise inputs.
 
-This is done by using weighting filter \\(V\_w\\), of which the output signal has a PSD \\(S\_w(f)\\) when the input is zero mean white noise (Figure [1](#figure--fig:monkhorst04-weighting-filter)).
+This is done by using weighting filter \\(V\_w\\), of which the output signal has a PSD \\(S\_w(f)\\) when the input is zero mean white noise ([Figure 1](#figure--fig:monkhorst04-weighting-filter)).
 
 <a id="figure--fig:monkhorst04-weighting-filter"></a>
 
@@ -119,7 +119,7 @@ The PSD \\(S\_w(f)\\) of the weighted signal is:
 Given \\(S\_w(f)\\), \\(V\_w(f)\\) can be obtained using a technique called _spectral factorization_.
 However, this can be avoided if the modeling of the disturbances is directly done in terms of weighting filters.
 
-Output weighting filters can also be used to scale different outputs relative to each other (Figure [2](#figure--fig:monkhorst04-general-weighted-plant)).
+Output weighting filters can also be used to scale different outputs relative to each other ([Figure 2](#figure--fig:monkhorst04-general-weighted-plant)).
 
 <a id="figure--fig:monkhorst04-general-weighted-plant"></a>
 
@@ -128,7 +128,7 @@ Output weighting filters can also be used to scale different outputs relative to
 
 #### Output scaling and the Pareto curve {#output-scaling-and-the-pareto-curve}
 
-In this research, the outputs of the closed loop system (Figure [3](#figure--fig:monkhorst04-closed-loop-H2)) are:
+In this research, the outputs of the closed loop system ([Figure 3](#figure--fig:monkhorst04-closed-loop-H2)) are:
 
 -   the performance (error) signal \\(e\\)
 -   the controller output \\(u\\)