Fix references to Controls Engineering in FRC (#2559)

Supersedes #2540.

source/docs/software/advanced-controls/state-space/state-space-flywheel-walkthrough.rst

@@ -95,7 +95,7 @@ The ``LinearSystem`` class contains methods for easily creating state-space syst
 Modeling Using Flywheel Moment of Inertia and Gearing
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
-A flywheel can also be modeled without access to a physical robot, using information about the motors, gearing and flywheel's :term:`moment of inertia`. A full derivation of this model is presented in Section 8.2.1 of  `Controls Engineering in FRC <https://file.tavsys.net/control/controls-engineering-in-frc.pdf>`__.
+A flywheel can also be modeled without access to a physical robot, using information about the motors, gearing and flywheel's :term:`moment of inertia`. A full derivation of this model is presented in Section 12.3 of  `Controls Engineering in FRC <https://file.tavsys.net/control/controls-engineering-in-frc.pdf>`__.
 
 The ``LinearSystem`` class contains methods to easily create a model of a flywheel from the flywheel's motors, gearing and :term:`moment of inertia`. The moment of inertia can be calculated using :term:`CAD` software or using physics. The examples used here are detailed in the flywheel example project (`Java <https://github.com/wpilibsuite/allwpilib/tree/v2023.2.1/wpilibjExamples/src/main/java/edu/wpi/first/wpilibj/examples/statespaceflywheel>`__/`C++ <https://github.com/wpilibsuite/allwpilib/blob/v2023.2.1/wpilibcExamples/src/main/cpp/examples/StateSpaceFlywheel/cpp/Robot.cpp>`__).
 

source/docs/software/advanced-controls/state-space/state-space-intro.rst

@@ -10,7 +10,7 @@ When tuning PID controllers, we focus on fiddling with controller parameters rel
 
 Model-based control focuses on developing an accurate model of the :term:`system` (mechanism) we are trying to control. These models help inform :term:`gains <gain>` picked for feedback controllers based on the physical responses of the system, rather than an arbitrary proportional :term:`gain` derived through testing. This allows us not only to predict ahead of time how a system will react, but also test our controllers without a physical robot and save time debugging simple bugs.
 
-.. note:: State-space control makes extensive use of linear algebra. More on linear algebra in modern control theory, including an introduction to linear algebra and resources, can be found in Chapter 4 of `Controls Engineering in FRC <https://file.tavsys.net/control/controls-engineering-in-frc.pdf>`__.
+.. note:: State-space control makes extensive use of linear algebra. More on linear algebra in modern control theory, including an introduction to linear algebra and resources, can be found in Chapter 5 of `Controls Engineering in FRC <https://file.tavsys.net/control/controls-engineering-in-frc.pdf>`__.
 
 If you've used WPILib's feedforward classes for ``SimpleMotorFeedforward`` or its sister classes, or used SysId to pick PID :term:`gains <gain>` for you, you're already familiar with model-based control! The ``kv`` and ``ka`` :term:`gains <gain>` can be used to describe how a motor (or arm, or drivetrain) will react to voltage. We can put these constants into standard state-space notation using WPILib's ``LinearSystem``, something we will do in a later article.