code: def predict(self, u=0):
          
  
          for f in self.filters:
              f.predict(u)
  
          # save prior
          self.x_prior = self.x.copy()
          self.P_prior = self.P.copy()
docs: Predict next position using the Kalman filter state propagation
          equations for each filter in the bank.
  
          Parameters
          ----------
  
          u : np.array
              Optional control vector. If non-zero, it is multiplied by B
              to create the control input into the system.