python-control · murrayrm · Mar 20, 2021 · Mar 20, 2021 · Mar 20, 2021
diff --git a/doc/optimal.rst b/doc/optimal.rst
@@ -66,7 +66,7 @@ intended to hold at all instants in time along the trajectory.
 
 A common use of optimization-based control techniques is the implementation
 of model predictive control (also called receding horizon control).  In
-model predict control, a finite horizon optimal control problem is solved,
+model predictive control, a finite horizon optimal control problem is solved,
 generating open-loop state and control trajectories.  The resulting control
 trajectory is applied to the system for a fraction of the horizon
 length. This process is then repeated, resulting in a sampled data feedback

diff --git a/examples/pvtol-lqr-nested.ipynb b/examples/pvtol-lqr-nested.ipynb
@@ -20,9 +20,9 @@
     "## System Description\n",
     "This example uses a simplified model for a (planar) vertical takeoff and landing aircraft (PVTOL), as shown below:\n",
     "\n",
-    "![PVTOL diagram](http://www.cds.caltech.edu/~murray/wiki/images/7/7d/Pvtol-diagram.png)\n",
+    "![PVTOL diagram](https://murray.cds.caltech.edu/images/murray.cds/7/7d/Pvtol-diagram.png)\n",
     "\n",
-    "![PVTOL dynamics](http://www.cds.caltech.edu/~murray/wiki/images/b/b7/Pvtol-dynamics.png)\n",
+    "![PVTOL dynamics](https://murray.cds.caltech.edu/images/murray.cds/b/b7/Pvtol-dynamics.png)\n",
     "\n",
     "The position and orientation of the center of mass of the aircraft is denoted by $(x,y,\\theta)$,  $m$ is the mass of the vehicle, $J$ the moment of inertia, $g$ the gravitational constant and $c$ the damping coefficient. The forces generated by the main downward thruster and the maneuvering thrusters are modeled as a pair of forces $F_1$ and $F_2$ acting at a distance $r$ below the aircraft (determined by the geometry of the thrusters).\n",
     "\n",
@@ -307,11 +307,10 @@
     "\n",
     "To design a controller for the lateral dynamics of the vectored thrust aircraft, we make use of a \"inner/outer\" loop design methodology. We begin by representing the dynamics using the block diagram\n",
     "\n",
-    "<img src=http://www.cds.caltech.edu/~murray/wiki/images/3/3f/Pvtol-lateraltf.png>\n",
-    "where\n",
-    "<img src=http://www.cds.caltech.edu/~murray/wiki/images/math/3/6/4/364e56f7893637e12edb0e0ac6c45722.png>  \n",
+    "<img src=https://murray.cds.caltech.edu/images/murray.cds/3/3f/Pvtol-lateraltf.png>\n",
+    "\n",
     "The controller is constructed by splitting the process dynamics and controller into two components: an inner loop consisting of the roll dynamics $P_i$ and control $C_i$ and an outer loop consisting of the lateral position dynamics $P_o$ and controller $C_o$.\n",
-    "<img src=http://www.cds.caltech.edu/~murray/wiki/images/f/f1/Pvtol-nested-1.png>\n",
+    "<img src=https://murray.cds.caltech.edu/images/murray.cds/f/f1/Pvtol-nested-1.png>\n",
     "The closed inner loop dynamics $H_i$ control the roll angle of the aircraft using the vectored thrust while the outer loop controller $C_o$ commands the roll angle to regulate the lateral position.\n",
     "\n",
     "The following code imports the libraries that are required and defines the dynamics:"
@@ -547,7 +546,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.9"
+   "version": "3.9.1"
   }
  },
  "nbformat": 4,