Unify controls and polynomial controls

benchmark/benchmark_balanced_field.py

@@ -66,8 +66,8 @@ def _run_balanced_field_length_problem(tx=dm.GaussLobatto, timeseries=True, sim=
     rotate.set_time_options(fix_initial=False, duration_bounds=(1.0, 5), duration_ref=1.0)
     rotate.add_state('r', fix_initial=False, lower=0, ref=1000.0, defect_ref=1000.0)
     rotate.add_state('v', fix_initial=False, lower=0, ref=100.0, defect_ref=100.0)
-    rotate.add_polynomial_control('alpha', order=1, opt=True, units='deg', lower=0, upper=10,
-                                  ref=10, val=[0, 10])
+    rotate.add_control('alpha', order=1, opt=True, units='deg', lower=0, upper=10,
+                                  ref=10, val=[0, 10], control_type='polynomial')
 
     if timeseries:
         rotate.add_timeseries_output('*')
@@ -229,7 +229,7 @@ def _run_balanced_field_length_problem(tx=dm.GaussLobatto, timeseries=True, sim=
     p.set_val('traj.rotate.t_duration', 5)
     p.set_val('traj.rotate.states:r', rotate.interp('r', [1750, 1800.0]))
     p.set_val('traj.rotate.states:v', rotate.interp('v', [80, 85.0]))
-    p.set_val('traj.rotate.polynomial_controls:alpha', 0.0, units='deg')
+    p.set_val('traj.rotate.controls:alpha', 0.0, units='deg')
 
     p.set_val('traj.climb.t_initial', 75)
     p.set_val('traj.climb.t_duration', 15)

docs/dymos_book/examples/balanced_field/balanced_field.ipynb

@@ -513,7 +513,8 @@
     "rotate.set_time_options(fix_initial=False, duration_bounds=(1.0, 5), duration_ref=1.0)\n",
     "rotate.add_state('r', fix_initial=False, lower=0, ref=1000.0, defect_ref=1000.0)\n",
     "rotate.add_state('v', fix_initial=False, lower=0, ref=100.0, defect_ref=100.0)\n",
-    "rotate.add_polynomial_control('alpha', order=1, opt=True, units='deg', lower=0, upper=10, ref=10, val=[0, 10])\n",
+    "rotate.add_control('alpha', order=1, opt=True, units='deg', lower=0, upper=10,\n",
+    "                   ref=10, val=[0, 10], control_type='polynomial')\n",
     "rotate.add_timeseries_output('*')\n",
     "\n",
     "# Fifth Phase: Climb to target speed and altitude at end of runway.\n",
@@ -687,7 +688,7 @@
     "rotate.set_time_val(initial=35.0, duration=5.0)\n",
     "rotate.set_state_val('r', [1750, 1800.0])\n",
     "rotate.set_state_val('v', [80, 85.0])\n",
-    "rotate.set_polynomial_control_val('alpha', 0.0, units='deg')\n",
+    "rotate.set_control_val('alpha', 0.0, units='deg')\n",
     "\n",
     "climb.set_time_val(initial=30.0, duration=20.0)\n",
     "climb.set_state_val('r', [5000, 5500.0], units='ft')\n",

docs/dymos_book/examples/balanced_field/balanced_field_funccomp.ipynb

@@ -248,19 +248,19 @@
    ]
   },
   {
-    "cell_type": "code",
-    "execution_count": null,
-    "metadata": {
-     "tags": [
-      "active-ipynb",
-      "remove-input",
-      "remove-output"
-     ]
-    },
-    "outputs": [],
-    "source": [
-     "%matplotlib inline"
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": [
+     "active-ipynb",
+     "remove-input",
+     "remove-output"
     ]
+   },
+   "outputs": [],
+   "source": [
+    "%matplotlib inline"
+   ]
   },
   {
    "cell_type": "code",
@@ -328,7 +328,9 @@
     "rotate.set_time_options(fix_initial=False, duration_bounds=(1.0, 5), duration_ref=1.0)\n",
     "rotate.add_state('r', fix_initial=False, lower=0, ref=1000.0, defect_ref=1000.0)\n",
     "rotate.add_state('v', fix_initial=False, lower=0, ref=100.0, defect_ref=100.0)\n",
-    "rotate.add_polynomial_control('alpha', order=1, opt=True, units='deg', lower=0, upper=10, ref=10, val=[0, 10])\n",
+    "rotate.add_control('alpha', order=1, opt=True, units='deg', lower=0, upper=10,\n",
+    "ref=10,\n",
+    "                   val=[0, 10], control_type='polynomial')\n",
     "rotate.add_timeseries_output('*')\n",
     "\n",
     "# Fifth Phase: Climb to target speed and altitude at end of runway.\n",
@@ -437,7 +439,7 @@
     "rotate.set_time_val(initial=35.0, duration=5.0)\n",
     "rotate.set_state_val('r', [1750, 1800.0])\n",
     "rotate.set_state_val('v', [80, 85.0])\n",
-    "rotate.set_polynomial_control_val('alpha', 0.0, units='deg')\n",
+    "rotate.set_control_val('alpha', 0.0, units='deg')\n",
     "\n",
     "climb.set_time_val(initial=30.0, duration=20.0)\n",
     "climb.set_state_val('r', [5000, 5500.0], units='ft')\n",

docs/dymos_book/examples/ssto_moon_polynomial_controls/ssto_moon_polynomial_controls.ipynb

@@ -80,19 +80,19 @@
    ]
   },
   {
-    "cell_type": "code",
-    "execution_count": null,
-    "metadata": {
-     "tags": [
-      "active-ipynb",
-      "remove-input",
-      "remove-output"
-     ]
-    },
-    "outputs": [],
-    "source": [
-     "%matplotlib inline"
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": [
+     "active-ipynb",
+     "remove-input",
+     "remove-output"
     ]
+   },
+   "outputs": [],
+   "source": [
+    "%matplotlib inline"
+   ]
   },
   {
    "cell_type": "code",
@@ -286,8 +286,8 @@
     "#\n",
     "# The tangent of theta is modeled as a linear polynomial over the duration of the phase.\n",
     "#\n",
-    "phase.add_polynomial_control('tan_theta', order=1, units=None, opt=True,\n",
-    "                             targets=['guidance.tan_theta'])\n",
+    "phase.add_control('tan_theta', order=1, units=None, opt=True,\n",
+    "                             targets=['guidance.tan_theta'], control_type='polynomial')\n",
     "\n",
     "#\n",
     "# Parameters values for thrust and specific impulse are design parameters. They are\n",
@@ -339,7 +339,7 @@
     "phase.set_state_val('vx', [0, 1627.0])\n",
     "phase.set_state_val('vy', [1.0E-6, 0.0])\n",
     "phase.set_state_val('m', 50000)\n",
-    "phase.set_polynomial_control_val('tan_theta', [[0.5 * np.pi], [0.0]])\n",
+    "phase.set_control_val('tan_theta', [[0.5 * np.pi], [0.0]])\n",
     "\n",
     "#\n",
     "# Solve the problem.\n",

docs/dymos_book/features/phases/variables.ipynb

@@ -245,37 +245,13 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## Polynomial Controls\n",
+    "### Polynomial Controls\n",
     "\n",
     "Sometimes it can be easier to optimize a problem by reducing the freedom in the controls.\n",
     "For instance, one might want the control to be linearly or quadratically varying throughout a phase, rather than having a different value specified at each node.\n",
     "In Dymos, this role is filled by the PolynomialControl.\n",
     "Polynomial controls are specified at some limited number of points throughout a _phase_, and then have their values interpolated to each node in each segment.\n",
-    "\n",
-    "### Options for Polynomial Control Variables"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "om.show_options_table(\"dymos.phase.options.PolynomialControlOptionsDictionary\")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Polynomial values are connected to the ODE using the `targets` argument.\n",
-    "The values of this argument obey the same rules as those for states.\n",
-    "\n",
-    "The polynomial control first and second derivatives w.r.t. time may also be connected to the ODE.\n",
-    "First derivatives of controls in Dymos assume the name `<control_name>_rate`.\n",
-    "Second derivatives of controls in Dymos assume the name `<control_name>_rate2`.\n",
-    "Control rates are automatically connected if a top-level input of the ODE is named `<control_name>_rate` or `<control_name>_rate2`.\n",
-    "These variables are available in the timeseries output as `timeseries.polynomial_control_rates.<control_name>_rate` and `timeseries.polynomial_control_rates.<control_name>_rate2`, respectively."
+    "Controls added with `control_type='polynomial'` are added as polynomial controls."
    ]
   },
   {

dymos/examples/balanced_field/doc/test_doc_balanced_field_length.py

@@ -65,7 +65,8 @@ def test_balanced_field_length_for_docs(self):
         rotate.set_time_options(fix_initial=False, duration_bounds=(1.0, 5), duration_ref=1.0)
         rotate.add_state('r', fix_initial=False, lower=0, ref=1000.0, defect_ref=1000.0)
         rotate.add_state('v', fix_initial=False, lower=0, ref=100.0, defect_ref=100.0)
-        rotate.add_polynomial_control('alpha', order=1, opt=True, units='deg', lower=0, upper=10, ref=10, val=[0, 10])
+        rotate.add_control('alpha', order=1, opt=True, units='deg', lower=0, upper=10, ref=10, val=[0, 10],
+                           control_type='polynomial')
         rotate.add_timeseries_output('*')
 
         # Fifth Phase: Climb to target speed and altitude at end of runway.
@@ -225,7 +226,7 @@ def test_balanced_field_length_for_docs(self):
         rotate.set_time_val(initial=70.0, duration=5.0)
         rotate.set_state_val('r', [1750, 1800.0])
         rotate.set_state_val('v', [80, 85.0])
-        rotate.set_polynomial_control_val('alpha', 0.0, units='deg')
+        rotate.set_control_val('alpha', 0.0, units='deg')
 
         climb.set_time_val(initial=75.0, duration=15.0)
         climb.set_state_val('r', [5000, 5500.0], units='ft')

dymos/examples/balanced_field/test/test_balanced_field_func_comp.py

@@ -197,7 +197,8 @@ def _run_problem(self, tx):
         rotate.set_time_options(fix_initial=False, duration_bounds=(1.0, 5), duration_ref=1.0)
         rotate.add_state('r', fix_initial=False, lower=0, ref=1000.0, defect_ref=1000.0)
         rotate.add_state('v', fix_initial=False, lower=0, ref=100.0, defect_ref=100.0)
-        rotate.add_polynomial_control('alpha', order=1, opt=True, units='deg', lower=0, upper=10, ref=10, val=[0, 10])
+        rotate.add_control('alpha', order=1, opt=True, units='deg', lower=0, upper=10, ref=10,
+                           val=[0, 10], control_type='polynomial')
         rotate.add_timeseries_output('*')
 
         # Fifth Phase: Climb to target speed and altitude at end of runway.
@@ -306,7 +307,7 @@ def _run_problem(self, tx):
         rotate.set_time_val(initial=35.0, duration=5.0)
         rotate.set_state_val('r', [1750, 1800.0])
         rotate.set_state_val('v', [80, 85.0])
-        rotate.set_polynomial_control_val('alpha', 0.0, units='deg')
+        rotate.set_control_val('alpha', 0.0, units='deg')
 
         climb.set_time_val(initial=30.0, duration=20.0)
         climb.set_state_val('r', [5000, 5500.0], units='ft')

dymos/examples/balanced_field/test/test_balanced_field_length.py

@@ -59,7 +59,8 @@ def _make_problem(self):
         rotate.set_time_options(fix_initial=False, duration_bounds=(1.0, 5), duration_ref=1.0)
         rotate.add_state('r', fix_initial=False, lower=0, ref=1000.0, defect_ref=1000.0)
         rotate.add_state('v', fix_initial=False, lower=0.0001, ref=100.0, defect_ref=100.0)
-        rotate.add_polynomial_control('alpha', order=1, opt=True, units='deg', lower=0, upper=10, ref=10, val=[0, 10])
+        rotate.add_control('alpha', order=1, opt=True, units='deg', lower=0, upper=10, ref=10,
+                           val=[0, 10], control_type='polynomial')
         rotate.add_timeseries_output('*')
 
         # Fifth Phase: Climb to target speed and altitude at end of runway.
@@ -204,7 +205,7 @@ def _make_problem(self):
         rotate.set_time_val(initial=35.0, duration=5.0)
         rotate.set_state_val('r', [1750, 1800.0])
         rotate.set_state_val('v', [80, 85.0])
-        rotate.set_polynomial_control_val('alpha', 0.0, units='deg')
+        rotate.set_control_val('alpha', 0.0, units='deg')
 
         climb.set_time_val(initial=30.0, duration=20.0)
         climb.set_state_val('r', [5000, 5500.0], units='ft')
@@ -321,7 +322,8 @@ def test_default_vals_stick(self):
                          val=rotate.interp(ys=[1750, 1800.0], nodes='state_input'))
         rotate.add_state('v', fix_initial=False, lower=0.0001, ref=100.0, defect_ref=100.0,
                          val=rotate.interp(ys=[80, 85.0], nodes='state_input'))
-        rotate.add_polynomial_control('alpha', order=1, opt=True, units='deg', lower=0, upper=10, ref=10, val=[0, 10])
+        rotate.add_control('alpha', order=1, opt=True, units='deg', lower=0, upper=10, ref=10,
+                           val=[0, 10], control_type='polynomial')
         rotate.add_timeseries_output('*')
 
         # Fifth Phase: Climb to target speed and altitude at end of runway.
@@ -456,7 +458,7 @@ def test_default_vals_stick(self):
 
         assert_near_equal(p.get_val('traj.rotate.t_initial'), 70)
         assert_near_equal(p.get_val('traj.rotate.t_duration'), 5)
-        assert_near_equal(p.get_val('traj.rotate.polynomial_controls:alpha'), np.array([[0, 10]]).T)
+        assert_near_equal(p.get_val('traj.rotate.controls:alpha'), np.array([[0, 10]]).T)
         assert_near_equal(p.get_val('traj.climb.controls:alpha'),
                           p.model.traj.phases.climb.interp('', [0.01, 0.01], nodes='control_input'))
         assert_near_equal(p.get_val('traj.climb.states:gam'),

dymos/examples/brachistochrone/test/test_brachistochrone_control_rate_targets.py

@@ -530,8 +530,8 @@ def test_brachistochrone_polynomial_control_rate_targets_gauss_lobatto(self):
                         units='m/s',
                         fix_initial=True, fix_final=False, solve_segments=False)
 
-        phase.add_polynomial_control('theta', order=3, units='deg*s', lower=0.01, upper=179.9,
-                                     fix_initial=True)
+        phase.add_control('theta', order=3, units='deg*s', lower=0.01, upper=179.9,
+                          fix_initial=True, control_type='polynomial')
 
         phase.add_parameter('g', units='m/s**2', opt=False, val=9.80665)
 
@@ -547,7 +547,7 @@ def test_brachistochrone_polynomial_control_rate_targets_gauss_lobatto(self):
         phase.set_state_val('x', [0, 10])
         phase.set_state_val('y', [10, 5])
         phase.set_state_val('v', [0, 9.9])
-        phase.set_polynomial_control_val('theta', [0, 100])
+        phase.set_control_val('theta', [0, 100])
 
         # Solve for the optimal trajectory
         p.run_driver()
@@ -624,8 +624,8 @@ def test_brachistochrone_polynomial_control_rate_targets_radau(self):
                         units='m/s',
                         fix_initial=True, fix_final=False, solve_segments=False)
 
-        phase.add_polynomial_control('theta', order=3, units='deg*s', lower=0.01, upper=179.9,
-                                     fix_initial=True)
+        phase.add_control('theta', order=3, units='deg*s', lower=0.01, upper=179.9,
+                          fix_initial=True, control_type='polynomial')
 
         phase.add_parameter('g', units='m/s**2', opt=False, val=9.80665)
 
@@ -641,7 +641,7 @@ def test_brachistochrone_polynomial_control_rate_targets_radau(self):
         phase.set_state_val('x', [0, 10])
         phase.set_state_val('y', [10, 5])
         phase.set_state_val('v', [0, 9.9])
-        phase.set_polynomial_control_val('theta', [0, 100])
+        phase.set_control_val('theta', [0, 100])
 
         # Solve for the optimal trajectory
         p.run_driver()
@@ -721,8 +721,8 @@ def test_brachistochrone_polynomial_control_rate_targets_gauss_lobatto(self):
                         units='m/s',
                         fix_initial=True, fix_final=False, solve_segments=False)
 
-        phase.add_polynomial_control('theta', order=3, units='deg*s', lower=0.01, upper=179.9,
-                                     rate_targets=['theta_rate'], fix_initial=True)
+        phase.add_control('theta', order=3, units='deg*s', lower=0.01, upper=179.9,
+                          rate_targets=['theta_rate'], fix_initial=True, control_type='polynomial')
 
         phase.add_parameter('g', units='m/s**2', opt=False, val=9.80665)
 
@@ -738,7 +738,7 @@ def test_brachistochrone_polynomial_control_rate_targets_gauss_lobatto(self):
         phase.set_state_val('x', [0, 10])
         phase.set_state_val('y', [10, 5])
         phase.set_state_val('v', [0, 9.9])
-        phase.set_polynomial_control_val('theta', [0, 100])
+        phase.set_control_val('theta', [0, 100])
 
         # Solve for the optimal trajectory
         p.run_driver()
@@ -815,8 +815,8 @@ def test_brachistochrone_polynomial_control_rate_targets_radau(self):
                         units='m/s',
                         fix_initial=True, fix_final=False, solve_segments=False)
 
-        phase.add_polynomial_control('theta', order=3, units='deg*s', lower=0.01, upper=179.9,
-                                     rate_targets=['theta_rate'], fix_initial=True)
+        phase.add_control('theta', order=3, units='deg*s', lower=0.01, upper=179.9,
+                          rate_targets=['theta_rate'], fix_initial=True, control_type='polynomial')
 
         phase.add_parameter('g', units='m/s**2', opt=False, val=9.80665)
 
@@ -832,7 +832,7 @@ def test_brachistochrone_polynomial_control_rate_targets_radau(self):
         phase.set_state_val('x', [0, 10])
         phase.set_state_val('y', [10, 5])
         phase.set_state_val('v', [0, 9.9])
-        phase.set_polynomial_control_val('theta', [0, 100])
+        phase.set_control_val('theta', [0, 100])
 
         # Solve for the optimal trajectory
         p.run_driver()
@@ -912,8 +912,8 @@ def test_brachistochrone_polynomial_control_rate_targets_gauss_lobatto(self):
                         units='m/s',
                         fix_initial=True, fix_final=False, solve_segments=False)
 
-        phase.add_polynomial_control('theta', order=5, units='deg*s**2', lower=0.01, upper=179.9,
-                                     rate_targets=None, rate2_targets=['theta_rate'], fix_initial=True)
+        phase.add_control('theta', order=5, units='deg*s**2', lower=0.01, upper=179.9,
+                          rate_targets=None, rate2_targets=['theta_rate'], fix_initial=True, control_type='polynomial')
 
         phase.add_parameter('g', units='m/s**2', opt=False, val=9.80665)
 
@@ -929,8 +929,8 @@ def test_brachistochrone_polynomial_control_rate_targets_gauss_lobatto(self):
         phase.set_state_val('x', [0, 10])
         phase.set_state_val('y', [10, 5])
         phase.set_state_val('v', [0, 9.9])
-        phase.set_polynomial_control_val('theta', [0, 10, 40, 60, 80, 100],
-                                         time_vals=[0, 0.4, 0.8, 1.2, 1.6, 2.0])
+        phase.set_control_val('theta', [0, 10, 40, 60, 80, 100],
+                              time_vals=[0, 0.4, 0.8, 1.2, 1.6, 2.0])
 
         # Solve for the optimal trajectory
         dm.run_problem(p, simulate=True)