import numpy as np import time from controller import ControllerBase from casadi_opt import OpenLoopSolver class MPCController(ControllerBase): def __init__(self, N=20, T=1.0): super().__init__() self.t = None self.ols = OpenLoopSolver(N=N, T=T) self.ols.setup() self.control_rate = self.ols.T / self.ols.N self.mstep = 2 # integrator self.omega_max = 5.0 self.control_scaling = 0.4 def set_target_position(self, target_pos): super(MPCController, self).set_target_position(target_pos) self.t = time.time() def compute_control(self, state): x_pred = state error_pos = np.linalg.norm(x_pred[0:2] - self.target_pos[0:2]) angles_unwrapped = np.unwrap([x_pred[2], self.target_pos[2]]) # unwrap angle to avoid jump in data error_ang = np.abs(angles_unwrapped[0] - angles_unwrapped[1]) # if error_pos > 0.075 or error_ang > 0.35: if error_pos > 0.05: # solve mpc open loop problem res = self.ols.solve(x_pred, self.target_pos) us1 = res[0] * self.control_scaling us2 = res[1] * self.control_scaling dt_mpc = time.time() - self.t if dt_mpc < self.control_rate: # wait until next control can be applied time.sleep(self.control_rate - dt_mpc) else: us1 = [0] * self.mstep us2 = [0] * self.mstep return us1, us2 def apply_control(self, control): if self.robot is not None: for i in range(0, self.mstep): # option to use multistep mpc if len(range) > 1 u1 = control[0][i] u2 = control[1][i] self.robot.send_cmd(u1, u2) if i < self.mstep: time.sleep(self.control_rate) self.t = time.time() # save time the most recent control was applied else: raise Exception("error: controller cannot apply control!\n" " there is no robot attached to the controller!")