Controller functions

adding new folder for controller specific functions. So far I have added the tuning of the pitch PI controller with pole placement

wetb/control/control.py

+# -*- coding: utf-8 -*-
+"""
+Created on Thu Aug 04 09:24:51 2016
+
+@author: tlbl
+"""
+
+from __future__ import division
+from __future__ import print_function
+from __future__ import unicode_literals
+from __future__ import absolute_import
+
+import numpy as np
+
+
+class Control(object):
+
+    def pitch_controller_tuning(self, pitch, I, dQdt, P, Omr, om, csi):
+        """
+
+        Function to compute the gains of the pitch controller of the Basic DTU
+        Wind Energy Controller with the pole placement technique implemented
+        in HAWCStab2.
+
+        Parameters
+        ----------
+        pitch: array
+            Pitch angle [deg]. The values should only be those of the full load
+            region.
+        I: array
+            Drivetrain inertia [kg*m**2]
+        dQdt: array
+            Partial derivative of the aerodynamic torque with respect to the
+            pitch angle [kNm/deg]. Can be computed with HAWCStab2.
+        P: float
+            Rated power [kW]. Set to zero in case of constant torque regulation
+        Omr: float
+            Rated rotational speed [rpm]
+        om: float
+            Freqeuncy of regulator mode [Hz]
+        csi: float
+            Damping ratio of regulator mode
+
+        Returns
+        -------
+        kp: float
+            Proportional gain [rad/(rad/s)]
+        ki: float
+            Intagral gain [rad/rad]
+        K1: float
+            Linear term of the gain scheduling [deg]
+        K2: float
+            Quadratic term of the gain shceduling [deg**2]
+
+
+        """
+        pitch = pitch * np.pi/180.
+        I = I * 1e-3
+        dQdt = dQdt * 180./np.pi
+        Omr = Omr * np.pi/30.
+        om = om * 2.*np.pi
+
+        # Quadratic fitting of dQdt
+        A = np.ones([dQdt.shape[0], 3])
+        A[:, 0] = pitch**2
+        A[:, 1] = pitch
+        b = dQdt
+        ATA = np.dot(A.T, A)
+        iATA = np.linalg.inv(ATA)
+        iATAA = np.dot(iATA, A.T)
+        x = np.dot(iATAA, b)
+
+        kp = -(2*csi*om*I[0] - P/(Omr**2))/x[2]
+        ki = -(om**2*I[0])/x[2]
+
+        K1 = x[2]/x[1]*(180./np.pi)
+        K2 = x[2]/x[0]*(180./np.pi)**2
+
+        return kp, ki, K1, K2
+
+    def K_omega2(V, P, R, TSR):
+
+        Va = np.array(V)
+        Pa = np.array(P)
+        Ra = np.array(R)
+        TSRa = np.array(TSR)
+        K = Ra**3 * np.mean(Pa/(TSRa*Va)**3)
+
+        return K
+
+    def select_regions(self, pitch, omega, power):
+
+        i12 = 0
+
+        n = len(pitch)
+
+        for i in range(n-1):
+            if (abs(power[i]/power[i+1] - 1.) > 0.01):
+                if (abs(omega[i] / omega[i+1] - 1.) > 0.01):
+                    i12 = i
+                    break
+        i23 = n-1
+        for i in range(i12, n-1):
+            if (abs(omega[i] / omega[i+1] - 1.) < 0.01):
+                i23 = i
+                break
+
+        i34 = i23
+        for i in range(i23, n-1):
+            if (abs(power[i]/power[i+1] - 1.) > 0.01):
+                if (abs(omega[i] / omega[i+1] - 1.) < 0.01):
+                    i34 = i+1
+
+        return i12, i23, i34
+
+
+if __name__ == '__main__':
+
+    pass