from AlexRobotics.control import DPO ########################### # Objectives ########################### x_start = np.array([-3.0, 0.0]) x_goal = np.array([0.0, 0.0]) ########################### # Create objects ########################### Robot = Manipulator.OneLinkManipulator() PD = linear.PD(kp=5, kd=2) PID = linear.PID(kp=5, kd=2, ki=4) CTC = ComputedTorque.ComputedTorqueController(Robot) SLD = ComputedTorque.SlidingModeController(Robot) RRT = RandomTree.RRT(Robot, x_start) VI = DPO.ValueIteration1DOF(Robot, 'quadratic') ############################ # Params ############################ tmax = 8 # max motor torque Robot.u_ub = np.array([tmax]) # Control Upper Bounds Robot.u_lb = np.array([-tmax]) # Control Lower Bounds RRT.x_start = x_start RRT.discretizeactions(3)
""" from AlexRobotics.dynamic import Manipulator as M from AlexRobotics.control import linear as RCL import matplotlib.pyplot as plt import numpy as np """ Define system """ # Define dynamic system R = M.OneLinkManipulator() # Define controller kp = 20 kd = 10 PD_controller = RCL.PD(kp, kd) # Asign feedback law to the dynamic system R.ctl = PD_controller.ctl """ Simulation and plotting """ # Ploting a trajectory x_start = np.array([-3, 0]) tf = 8 n = int(tf / 0.01) + 1 R.plotAnimation(x_start, tf, n, solver='ode') # Time plot #R.Sim.plot_OL() R.Sim.plot_CL()
