From fa8364356ba7ec3add9d5e859ce3f00266c8ad98 Mon Sep 17 00:00:00 2001 From: mcarfagno Date: Fri, 29 Nov 2019 15:50:12 +0000 Subject: [PATCH] cvxpy full sim --- .ipynb_checkpoints/MPC_cvxpy-checkpoint.ipynb | 183 +++++++++++++++++- MPC_cvxpy.ipynb | 183 +++++++++++++++++- 2 files changed, 350 insertions(+), 16 deletions(-) diff --git a/.ipynb_checkpoints/MPC_cvxpy-checkpoint.ipynb b/.ipynb_checkpoints/MPC_cvxpy-checkpoint.ipynb index 8088e2a..9e65dbe 100644 --- a/.ipynb_checkpoints/MPC_cvxpy-checkpoint.ipynb +++ b/.ipynb_checkpoints/MPC_cvxpy-checkpoint.ipynb @@ -291,8 +291,8 @@ "name": "stdout", "output_type": "stream", "text": [ - "CPU times: user 4.18 ms, sys: 92 µs, total: 4.27 ms\n", - "Wall time: 3.79 ms\n" + "CPU times: user 4.51 ms, sys: 390 µs, total: 4.9 ms\n", + "Wall time: 4.39 ms\n" ] } ], @@ -390,8 +390,8 @@ "name": "stdout", "output_type": "stream", "text": [ - "CPU times: user 2.34 ms, sys: 1.92 ms, total: 4.26 ms\n", - "Wall time: 1.24 ms\n" + "CPU times: user 1.31 ms, sys: 5.59 ms, total: 6.91 ms\n", + "Wall time: 2.05 ms\n" ] } ], @@ -805,7 +805,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 14, "metadata": {}, "outputs": [ { @@ -819,8 +819,8 @@ "name": "stdout", "output_type": "stream", "text": [ - "CPU times: user 277 ms, sys: 0 ns, total: 277 ms\n", - "Wall time: 276 ms\n" + "CPU times: user 329 ms, sys: 173 ms, total: 502 ms\n", + "Wall time: 281 ms\n" ] } ], @@ -916,7 +916,7 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 15, "metadata": {}, "outputs": [ { @@ -975,6 +975,173 @@ "plt.show()" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "full track demo" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/marcello/.local/lib/python3.5/site-packages/ipykernel_launcher.py:18: RuntimeWarning: invalid value encountered in true_divide\n" + ] + } + ], + "source": [ + "\n", + "track = compute_path_from_wp([0,5,7.5,10,12,13,13,10],\n", + " [0,0,2.5,2.5,0,0,5,10])\n", + "\n", + "sim_duration =100 \n", + "\n", + "x_sim = np.zeros((N,sim_duration))\n", + "u_sim = np.zeros((M,sim_duration-1))\n", + "\n", + "MAX_SPEED = 2.5\n", + "MIN_SPEED = 0.5\n", + "MAX_STEER_SPEED = 1.57/2\n", + "\n", + "# Starting Condition\n", + "x0 = np.zeros(N)\n", + "x0[0] = 0\n", + "x0[1] = -0.5\n", + "x0[2] = np.radians(-0)\n", + "_,psi,cte = calc_err(x0,track)\n", + "x0[3]=psi\n", + "x0[4]=cte\n", + "\n", + "x_sim[:,0]=x0\n", + " \n", + "#starting guess\n", + "u_bar = np.zeros((M,T))\n", + "u_bar[0,:]=0.5*(MAX_SPEED+MIN_SPEED)\n", + "u_bar[1,:]=0.01\n", + "\n", + "for sim_time in range(sim_duration-1):\n", + " \n", + " # Prediction\n", + " x_bar=np.zeros((N,T+1))\n", + " x_bar[:,0]=x_sim[:,sim_time]\n", + "\n", + " for t in range (1,T+1):\n", + " xt=x_bar[:,t-1].reshape(5,1)\n", + " ut=u_bar[:,t-1].reshape(2,1)\n", + "\n", + " A,B,C=get_linear_model(xt,ut)\n", + "\n", + " xt_plus_one = np.squeeze(np.dot(A,xt)+np.dot(B,ut)+C)\n", + "\n", + " _,psi,cte = calc_err(xt_plus_one,track)\n", + " xt_plus_one[3]=psi\n", + " xt_plus_one[4]=cte\n", + "\n", + " x_bar[:,t]= xt_plus_one\n", + "\n", + "\n", + " #CVXPY Linear MPC problem statement\n", + " cost = 0\n", + " constr = []\n", + "\n", + " for t in range(T):\n", + "\n", + " # Cost function\n", + " #cost += 5*cp.sum_squares( x[3, t]) # psi\n", + " #cost += 100*cp.sum_squares( x[4, t]) # cte\n", + "\n", + " # Tracking\n", + " idx,_,_ = calc_err(x_bar[:,t],track)\n", + " delta_x = track[:,idx]-x[0:3,t]\n", + " cost+= cp.quad_form(delta_x,10*np.eye(3))\n", + "\n", + " # Tracking 5 states\n", + " #delta_x = np.append(track[:,idx],[0,0])\n", + " #cost+= cp.quad_form(delta_x-x[:,t],500*np.eye(N))\n", + "\n", + " # Actuation effort\n", + " cost += cp.quad_form( u[:, t],1*np.eye(M))\n", + "\n", + " # Actuation rate of change\n", + " if t < (T - 1):\n", + " cost += cp.quad_form(u[:, t + 1] - u[:, t], 5*np.eye(M))\n", + "\n", + " #constrains\n", + " A,B,C=get_linear_model(x_bar[:,t],u_bar[:,t])\n", + " constr += [x[:,t+1] == A*x[:,t] + B*u[:,t] + C.flatten()]\n", + "\n", + " # sums problem objectives and concatenates constraints.\n", + " constr += [x[:,0] == x_sim[:,sim_time]]\n", + " constr += [u[0, :] <= MAX_SPEED]\n", + " constr += [u[0, :] >= MIN_SPEED]\n", + " constr += [cp.abs(u[1, :]) <= MAX_STEER_SPEED]\n", + " \n", + " # Solve\n", + " prob = cp.Problem(cp.Minimize(cost), constr)\n", + " solution = prob.solve(solver=cp.ECOS, verbose=False)\n", + " \n", + " #retrieved optimized U and assign to u_bar to linearize in next step\n", + " u_bar=np.vstack((np.array(u.value[0, :]).flatten(),\n", + " (np.array(u.value[1, :]).flatten())))\n", + " \n", + " u_sim[:,sim_time] = u_bar[:,0]\n", + " \n", + " # move simulation to t+1\n", + " tspan = [0,dt]\n", + " x_sim[:,sim_time+1] = odeint(kinematics_model,\n", + " x_sim[:,sim_time],\n", + " tspan,\n", + " args=(u_bar[:,0],))[1]\n" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "#plot trajectory\n", + "grid = plt.GridSpec(2, 3, wspace=0.4, hspace=0.3)\n", + "\n", + "plt.figure(figsize=(15,10))\n", + "\n", + "plt.subplot(grid[0:2, 0:2])\n", + "plt.plot(track[0,:],track[1,:],\"b*\")\n", + "plt.plot(x_sim[0,:],x_sim[1,:])\n", + "plt.axis(\"equal\")\n", + "plt.ylabel('y')\n", + "plt.xlabel('x')\n", + "\n", + "plt.subplot(grid[0, 2])\n", + "plt.plot(np.degrees(u_sim[0,:]))\n", + "plt.ylabel('v(t) [m/s]')\n", + "\n", + "plt.subplot(grid[1, 2])\n", + "plt.plot(np.degrees(u_sim[1,:]))\n", + "plt.ylabel('w(t) [rad/s]')\n", + "\n", + "plt.show()" + ] + }, { "cell_type": "code", "execution_count": null, diff --git a/MPC_cvxpy.ipynb b/MPC_cvxpy.ipynb index 8088e2a..9e65dbe 100644 --- a/MPC_cvxpy.ipynb +++ b/MPC_cvxpy.ipynb @@ -291,8 +291,8 @@ "name": "stdout", "output_type": "stream", "text": [ - "CPU times: user 4.18 ms, sys: 92 µs, total: 4.27 ms\n", - "Wall time: 3.79 ms\n" + "CPU times: user 4.51 ms, sys: 390 µs, total: 4.9 ms\n", + "Wall time: 4.39 ms\n" ] } ], @@ -390,8 +390,8 @@ "name": "stdout", "output_type": "stream", "text": [ - "CPU times: user 2.34 ms, sys: 1.92 ms, total: 4.26 ms\n", - "Wall time: 1.24 ms\n" + "CPU times: user 1.31 ms, sys: 5.59 ms, total: 6.91 ms\n", + "Wall time: 2.05 ms\n" ] } ], @@ -805,7 +805,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 14, "metadata": {}, "outputs": [ { @@ -819,8 +819,8 @@ "name": "stdout", "output_type": "stream", "text": [ - "CPU times: user 277 ms, sys: 0 ns, total: 277 ms\n", - "Wall time: 276 ms\n" + "CPU times: user 329 ms, sys: 173 ms, total: 502 ms\n", + "Wall time: 281 ms\n" ] } ], @@ -916,7 +916,7 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 15, "metadata": {}, "outputs": [ { @@ -975,6 +975,173 @@ "plt.show()" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "full track demo" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/marcello/.local/lib/python3.5/site-packages/ipykernel_launcher.py:18: RuntimeWarning: invalid value encountered in true_divide\n" + ] + } + ], + "source": [ + "\n", + "track = compute_path_from_wp([0,5,7.5,10,12,13,13,10],\n", + " [0,0,2.5,2.5,0,0,5,10])\n", + "\n", + "sim_duration =100 \n", + "\n", + "x_sim = np.zeros((N,sim_duration))\n", + "u_sim = np.zeros((M,sim_duration-1))\n", + "\n", + "MAX_SPEED = 2.5\n", + "MIN_SPEED = 0.5\n", + "MAX_STEER_SPEED = 1.57/2\n", + "\n", + "# Starting Condition\n", + "x0 = np.zeros(N)\n", + "x0[0] = 0\n", + "x0[1] = -0.5\n", + "x0[2] = np.radians(-0)\n", + "_,psi,cte = calc_err(x0,track)\n", + "x0[3]=psi\n", + "x0[4]=cte\n", + "\n", + "x_sim[:,0]=x0\n", + " \n", + "#starting guess\n", + "u_bar = np.zeros((M,T))\n", + "u_bar[0,:]=0.5*(MAX_SPEED+MIN_SPEED)\n", + "u_bar[1,:]=0.01\n", + "\n", + "for sim_time in range(sim_duration-1):\n", + " \n", + " # Prediction\n", + " x_bar=np.zeros((N,T+1))\n", + " x_bar[:,0]=x_sim[:,sim_time]\n", + "\n", + " for t in range (1,T+1):\n", + " xt=x_bar[:,t-1].reshape(5,1)\n", + " ut=u_bar[:,t-1].reshape(2,1)\n", + "\n", + " A,B,C=get_linear_model(xt,ut)\n", + "\n", + " xt_plus_one = np.squeeze(np.dot(A,xt)+np.dot(B,ut)+C)\n", + "\n", + " _,psi,cte = calc_err(xt_plus_one,track)\n", + " xt_plus_one[3]=psi\n", + " xt_plus_one[4]=cte\n", + "\n", + " x_bar[:,t]= xt_plus_one\n", + "\n", + "\n", + " #CVXPY Linear MPC problem statement\n", + " cost = 0\n", + " constr = []\n", + "\n", + " for t in range(T):\n", + "\n", + " # Cost function\n", + " #cost += 5*cp.sum_squares( x[3, t]) # psi\n", + " #cost += 100*cp.sum_squares( x[4, t]) # cte\n", + "\n", + " # Tracking\n", + " idx,_,_ = calc_err(x_bar[:,t],track)\n", + " delta_x = track[:,idx]-x[0:3,t]\n", + " cost+= cp.quad_form(delta_x,10*np.eye(3))\n", + "\n", + " # Tracking 5 states\n", + " #delta_x = np.append(track[:,idx],[0,0])\n", + " #cost+= cp.quad_form(delta_x-x[:,t],500*np.eye(N))\n", + "\n", + " # Actuation effort\n", + " cost += cp.quad_form( u[:, t],1*np.eye(M))\n", + "\n", + " # Actuation rate of change\n", + " if t < (T - 1):\n", + " cost += cp.quad_form(u[:, t + 1] - u[:, t], 5*np.eye(M))\n", + "\n", + " #constrains\n", + " A,B,C=get_linear_model(x_bar[:,t],u_bar[:,t])\n", + " constr += [x[:,t+1] == A*x[:,t] + B*u[:,t] + C.flatten()]\n", + "\n", + " # sums problem objectives and concatenates constraints.\n", + " constr += [x[:,0] == x_sim[:,sim_time]]\n", + " constr += [u[0, :] <= MAX_SPEED]\n", + " constr += [u[0, :] >= MIN_SPEED]\n", + " constr += [cp.abs(u[1, :]) <= MAX_STEER_SPEED]\n", + " \n", + " # Solve\n", + " prob = cp.Problem(cp.Minimize(cost), constr)\n", + " solution = prob.solve(solver=cp.ECOS, verbose=False)\n", + " \n", + " #retrieved optimized U and assign to u_bar to linearize in next step\n", + " u_bar=np.vstack((np.array(u.value[0, :]).flatten(),\n", + " (np.array(u.value[1, :]).flatten())))\n", + " \n", + " u_sim[:,sim_time] = u_bar[:,0]\n", + " \n", + " # move simulation to t+1\n", + " tspan = [0,dt]\n", + " x_sim[:,sim_time+1] = odeint(kinematics_model,\n", + " x_sim[:,sim_time],\n", + " tspan,\n", + " args=(u_bar[:,0],))[1]\n" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "#plot trajectory\n", + "grid = plt.GridSpec(2, 3, wspace=0.4, hspace=0.3)\n", + "\n", + "plt.figure(figsize=(15,10))\n", + "\n", + "plt.subplot(grid[0:2, 0:2])\n", + "plt.plot(track[0,:],track[1,:],\"b*\")\n", + "plt.plot(x_sim[0,:],x_sim[1,:])\n", + "plt.axis(\"equal\")\n", + "plt.ylabel('y')\n", + "plt.xlabel('x')\n", + "\n", + "plt.subplot(grid[0, 2])\n", + "plt.plot(np.degrees(u_sim[0,:]))\n", + "plt.ylabel('v(t) [m/s]')\n", + "\n", + "plt.subplot(grid[1, 2])\n", + "plt.plot(np.degrees(u_sim[1,:]))\n", + "plt.ylabel('w(t) [rad/s]')\n", + "\n", + "plt.show()" + ] + }, { "cell_type": "code", "execution_count": null,