Merge pull request #449 from ChrisRackauckas-Claude/fix-docs-round-2

docs: namespace MTK analysis-point helpers and import ImplicitEuler

Author: ChrisRackauckas

docs/src/tutorials/dc_motor_pi.md

@@ -117,12 +117,12 @@ T(s) &= \dfrac{P(s)C(s)}{I + P(s)C(s)}
 using ControlSystemsBase
 # Get sensitivity function
 matrices_S,
-simplified_sys_S = Blocks.get_sensitivity(
+simplified_sys_S = ModelingToolkit.get_sensitivity(
     model, :y, op = Dict(unknowns(sys) .=> 0.0))
 So = ss(matrices_S...) |> minreal # The output-sensitivity function as a StateSpace system
 # Get complementary sensitivity function
 matrices_T,
-simplified_sys_T = Blocks.get_comp_sensitivity(
+simplified_sys_T = ModelingToolkit.get_comp_sensitivity(
     model, :y, op = Dict(unknowns(sys) .=> 0.0))
 To = ss(matrices_T...)# The output complementary sensitivity function as a StateSpace system
 bodeplot([So, To], label = ["S" "T"], plot_title = "Sensitivity functions",
@@ -133,7 +133,7 @@ Similarly, we may compute the loop-transfer function and plot its Nyquist curve
 
 ```@example dc_motor_pi
 matrices_L,
-simplified_sys_L = Blocks.get_looptransfer(
+simplified_sys_L = ModelingToolkit.get_looptransfer(
     model, :y, op = Dict(unknowns(sys) .=> 0.0))
 L = -ss(matrices_L...) # The loop-transfer function as a StateSpace system. The negative sign is to negate the built-in negative feedback
 Ms, ωMs = hinfnorm(So) # Compute the peak of the sensitivity function to draw a circle in the Nyquist plot

docs/src/tutorials/input_component.md

@@ -187,6 +187,7 @@ using ModelingToolkit
 using ModelingToolkit: t_nounits as t, D_nounits as D
 using ModelingToolkitStandardLibrary.Blocks
 using OrdinaryDiffEq
+using OrdinaryDiffEqSDIRK: ImplicitEuler
 
 const rdata = Ref{Vector{Float64}}()