# 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) RRT.dt = 0.1 RRT.goal_radius = 0.3 RRT.max_nodes = 5000
Created on Sat Mar 5 20:24:50 2016 @author: alex """ from AlexRobotics.dynamic import Manipulator as M from AlexRobotics.control import ComputedTorque as CTC import matplotlib.pyplot as plt """ Define system """ # Define dynamic system R = M.TwoLinkManipulator() # Define controller CTC_controller = CTC.SlidingModeController(R) CTC_controller.lam = 1 CTC_controller.nab = 1 CTC_controller.D = 0 # Asign feedback law to the dynamic system R.ctl = CTC_controller.ctl """ Simulation and plotting """ # Ploting a trajectory x0 = [3, -1, 0, 0] tf = 10 dt = 0.01 n = int(tf / dt) + 1 R.plotAnimation(x0, tf, n, solver='euler')