diff --git a/lib/ControlSystemsBase/src/discrete.jl b/lib/ControlSystemsBase/src/discrete.jl
index 5247ca941..bd69ea75a 100644
--- a/lib/ControlSystemsBase/src/discrete.jl
+++ b/lib/ControlSystemsBase/src/discrete.jl
@@ -152,7 +152,7 @@ rstc(args...)=rst(args..., ;cont=true)
 
 Polynomial synthesis in discrete time.
 
-Polynomial synthesis according to CCS ch 10 to
+Polynomial synthesis according to "Computer-Controlled Systems" ch 10 to
 design a controller ``R(q) u(k) = T(q) r(k) - S(q) y(k)``
 
 Inputs:
diff --git a/lib/ControlSystemsBase/src/matrix_comps.jl b/lib/ControlSystemsBase/src/matrix_comps.jl
index 57d233a8a..000be285f 100644
--- a/lib/ControlSystemsBase/src/matrix_comps.jl
+++ b/lib/ControlSystemsBase/src/matrix_comps.jl
@@ -808,7 +808,7 @@ such that `feedback(sys, cont)` produces a closed-loop system with eigenvalues g
 
 This controller does not have a direct term, and corresponds to state feedback operating on state estimated by [`observer_predictor`](@ref). Use this form if the computed control signal is applied at the next sampling instant, or with an otherwise large delay in relation to the measurement fed into the controller.
 
-Ref: CCS Eq 4.37
+Ref: "Computer-Controlled Systems" Eq 4.37
 
 # If `direct = true`
 Return the observer_controller `cont` that is given by
@@ -819,7 +819,7 @@ This controller has a direct term, and corresponds to state feedback operating o
 !!! note
     To use this formulation, the observer gain `K` should have been designed for the pair `(A, CA)` rather than `(A, C)`. To do this, pass `direct = true` when calling [`place`](@ref) or [`kalman`](@ref).
 
-Ref: Ref: CCS pp 140 and CCS pp 162 prob 4.7
+Ref: Ref: "Computer-Controlled Systems" pp 140 and "Computer-Controlled Systems" pp 162 prob 4.7
 
 # Arguments:
 - `sys`: Model of system
@@ -861,7 +861,7 @@ The observer filter is equivalent to the [`observer_predictor`](@ref) for contin
 !!! note
     To use this formulation, the observer gain `K` should have been designed for the pair `(A, CA)` rather than `(A, C)`. To do this, pass `direct = true` when calling [`place`](@ref) or [`kalman`](@ref).
 
-Ref: CCS Eq 4.32
+Ref: "Computer-Controlled Systems" Eq 4.32
 """
 function observer_filter(sys::AbstractStateSpace{<:Discrete}, K::AbstractMatrix; output_state = false)
     A,B,C,D = ssdata(sys)
diff --git a/lib/ControlSystemsBase/src/synthesis.jl b/lib/ControlSystemsBase/src/synthesis.jl
index bcd14a9f3..25735d55f 100644
--- a/lib/ControlSystemsBase/src/synthesis.jl
+++ b/lib/ControlSystemsBase/src/synthesis.jl
@@ -78,7 +78,7 @@ end
 
 Calculate the optimal Kalman gain.
 
-If `direct = true`, the observer gain is computed for the pair `(A, CA)` instead of `(A,C)`. This option is intended to be used together with the option `direct = true` to [`observer_controller`](@ref). Ref: CCS pp 140.
+If `direct = true`, the observer gain is computed for the pair `(A, CA)` instead of `(A,C)`. This option is intended to be used together with the option `direct = true` to [`observer_controller`](@ref). Ref: "Computer-Controlled Systems" pp 140.
 
 The `args...; kwargs...` are sent to the Riccati solver, allowing specification of cross-covariance etc. See `?MatrixEquations.arec/ared` for more help.
 """
@@ -116,7 +116,7 @@ If `direct = true` and `opt = :o`, the the observer gain `K` is calculated such
 
 Note: only apply `direct = true` to discrete-time systems.
 
-Ref: CCS pp 140.
+Ref: "Computer-Controlled Systems" pp 140.
 
 Uses Ackermann's formula for SISO systems and [`place_knvd`](@ref) for MIMO systems.