* Adapt the interpolation for trajectory integration, #61

pyDMPC/ControlFramework/Init.py

@@ -71,7 +71,7 @@
 par_neigh.append(None)
 input_names.append(["coolerTemperature.T"])
 input_variables.append([r"variation.table[1,2]"])
-inputs.append([i for i in range(280,325,5)])
+inputs.append([i for i in range(280,325,1)])
 output_names.append(["supplyAirTemperature.T"])
 set_points.append([303])
 state_var_names.append(["heaterInitials[1].y"])
@@ -90,7 +90,7 @@
 commands.append([[0,0], [10,10], [30,30], [60,60], [80,80], [100,100]])
 traj_points.append([])
 traj_var.append([])
-cost_fac.append([0.5, 0.0, 1.0])
+cost_fac.append([0.1, 0.0, 1.0])
 
 sys_id.append(1)
 name.append("Cooler")
@@ -100,7 +100,7 @@
 par_neigh.append(None)
 input_names.append(["preHeaterTemperature.T"])
 input_variables.append([r"variation.table[1,2]"])
-inputs.append([i for i in range(280,325,5)])
+inputs.append([i for i in range(280,325,1)])
 output_names.append(["supplyAirTemperature.T"])
 set_points.append([303])
 state_var_names.append(["coolerInitials[1].y"])
@@ -116,7 +116,7 @@
 mod_path.append(f'{glob_res_path}\\cooler')
 command_names.append(["valveCooler"])
 command_variables.append(["decisionVariables.table[1,2]"])
-commands.append([[0,0], [10,10], [30,30], [60,60], [80,80], [100,100]])
+commands.append([[0,0], [2,2], [4,4], [6,6], [8,8], [10,10], [12,12], [14,14], [16,16], [18,18]])
 traj_points.append([])
 traj_var.append([])
-cost_fac.append([0.5, 1.0, 0])
+cost_fac.append([0.0, 1.0, 0])

pyDMPC/ControlFramework/Subsystem.py

@@ -148,6 +148,7 @@ def optimize(self, interp):
     def interp_minimize(self, interp):
 
         from scipy import interpolate as it
+        import time
 
         opt_costs = []
         opt_outputs =  []
@@ -239,12 +240,13 @@ def interp_minimize(self, interp):
             self.coup_vars_send = opt_outputs[0]
             self.command_send = opt_command[0]
 
-        #print(f"{self.name}: {self.command_send}")
-        #time.sleep(2)
-        #print(f"Cost: {self.cost_send}")
+        print(f"self.cost_send: {self.cost_send}")
+        time.sleep(2)
+        print(f"Command: {self.command_send}")
 
     def calc_cost(self, command, outputs):
         import scipy.interpolate
+        import numpy as np
 
         cost = self.cost_fac[0] * sum(command)
         #print(f"Cost after the 1st step: {cost}")
@@ -257,7 +259,8 @@ def calc_cost(self, command, outputs):
                     cost += self.cost_fac[1] * c(outputs)
                     #print(f"Interp. cost: {c(outputs)}")
                 elif type(c) is list:
-                    cost += self.cost_fac[1] * c[0]
+                    idx = self.find_nearest(np.asarray(self.inputs), outputs)
+                    cost += self.cost_fac[1] * c[idx]
                 else:
                     cost += self.cost_fac[1] * c
         #print(f"Cost after the 2nd step: {cost}")
@@ -286,6 +289,8 @@ def interp(self, iter_real):
             inp = self.model.states.inputs
 
         idx = self.find_nearest(np.asarray(self.inputs), inp[0])
+        #print(f"self.inputs): {self.inputs}")
+        #print(f"inp[0]: {inp[0]}")
 
         if self.command_send != []:
             if (type(self.command_send) is scipy.interpolate.interpolate.interp1d):
@@ -298,7 +303,8 @@ def interp(self, iter_real):
                 self.fin_coup_vars = self.coup_vars_send(inp[0])
             else:
                 self.fin_coup_vars = self.coup_vars_send[idx]
-
+        print(f"self.fin_command: {self.fin_command}")
+        print(f"idx: {idx}")
 
     def get_inputs(self):
 

pyDMPC/Utilities/mlp_train_modelica.py

@@ -8,7 +8,7 @@
 
 def main():
 
-    module = "heater"
+    module = "cooler"
     command = []        # The manipulated variable in the model
     T_cur = []          # The current inflow temperature
 
@@ -28,7 +28,7 @@ def main():
     sync_rate = 60  # Synchronisation rate of the FMU
 
     # Load exisiting FMU
-    model = load_fmu(f"C:\TEMP\Dymola\{module}.fmu")
+    model = load_fmu(f"D:\dymola\{module}.fmu")
 
     """ Initialize the FMU """
     model.set('valveOpening',0)
@@ -39,12 +39,12 @@ def main():
 
     """ Actual training sequence """
     for k in range(40):
-        for t in range(12000):
+        for t in range(1200):
             """Write random values to the controlled variables"""
             if t < 100:
                 command.append(0)
             elif t%120 == 0:
-                command.append(random.uniform(0.0,100.0))
+                command.append(random.uniform(0.0,10.0))
             else:
                 command.append(command[-1])