Commit cf843db1 authored by Ibrahim's avatar Ibrahim
Browse files

Current calculations; 

Added Motor.current_average() and Multirotor.current_average() methods for duty-cycle adjusted currents.
Refactored plotting function for DataLog in visualize.py
parent 966e85d6

Demo.ipynb

+30 −32
Original line number Diff line number Diff line 
%% Cell type:markdown id:d001f534 tags:



#### Notebook setup



%% Cell type:code id:be76bd53 tags:



``` python

%pip install -e .

```



%% Cell type:code id:5a776232 tags:



``` python

%reload_ext autoreload

%autoreload 2

%matplotlib inline

import time

import warnings

import os, sys

from copy import deepcopy

from types import SimpleNamespace



import matplotlib.pyplot as plt

import gym

import numpy as np

from tqdm.auto import tqdm, trange



from multirotor.helpers import control_allocation_matrix, DataLog

from multirotor.vehicle import MotorParams, VehicleParams, PropellerParams, SimulationParams, BatteryParams

from multirotor.controller import (

    PosController, VelController,

    AttController, RateController,

    AltController, AltRateController,

    Controller

)

from multirotor.simulation import Multirotor, Propeller, Motor, Battery

from multirotor.coords import body_to_inertial, inertial_to_body, direction_cosine_matrix, angular_to_euler_rate

from multirotor.env import SpeedsMultirotorEnv as LocalOctorotor

from multirotor.trajectories import Trajectory, GuidedTrajectory

```



%% Cell type:code id:421b284b tags:



``` python

# Plotting/display parameters

# https://stackoverflow.com/a/21009774/4591810

float_formatter = "{:.3f}".format

np.set_printoptions(formatter={'float_kind':float_formatter})



SMALL_SIZE = 16

MEDIUM_SIZE = 16

BIGGER_SIZE = 20



plt.rc('font', size=SMALL_SIZE)          # controls default text sizes

plt.rc('axes', titlesize=MEDIUM_SIZE)     # fontsize of the axes title

plt.rc('axes', labelsize=BIGGER_SIZE, titlesize=BIGGER_SIZE)    # fontsize of the x and y labels

plt.rc('xtick', labelsize=MEDIUM_SIZE)    # fontsize of the tick labels

plt.rc('ytick', labelsize=MEDIUM_SIZE)    # fontsize of the tick labels

plt.rc('legend', fontsize=SMALL_SIZE)    # legend fontsize

plt.rc('figure', titlesize=BIGGER_SIZE)  # fontsize of the figure title

```



%% Cell type:markdown id:9a31149f tags:



### Parameters



%% Cell type:code id:1ba2a2fe tags:



``` python

# Tarot T18 params

bp = BatteryParams(max_voltage=22.2)

mp = MotorParams(

    moment_of_inertia=5e-5,

#     resistance=0.27,

    # resistance=0.27,

    resistance=0.081,

    k_emf=0.0265,

    k_motor=0.0932,

    speed_voltage_scaling=0.0347

    # k_motor=0.0932,

    speed_voltage_scaling=0.0347,

    max_current=38.

)

pp = PropellerParams(

    moment_of_inertia=1.86e-6,

    use_thrust_constant=True,

    k_thrust=9.8419e-05, # 18-inch propeller

    # k_thrust=5.28847e-05, # 15 inch propeller

    k_drag=1.8503e-06, # 18-inch propeller

    # k_drag=1.34545e-06, # 15-inch propeller

    motor=mp

)

vp = VehicleParams(

    propellers=[pp] * 8,

    battery=bp,

    # angles in 45 deg increments, rotated to align with

    # model setup in gazebo sim (not part of this repo)

    angles=np.linspace(0, -2*np.pi, num=8, endpoint=False) + 0.375 * np.pi,

    distances=np.ones(8) * 0.635,

    clockwise=[-1,1,-1,1,-1,1,-1,1],

    mass=10.66,

    inertia_matrix=np.asarray([

        [0.2206, 0, 0],

        [0, 0.2206, 0.],

        [0, 0, 0.4238]

    ])

)

sp = SimulationParams(dt=0.001, g=9.81)

```



%% Cell type:markdown id:17f3b34d tags:



### Multirotor



%% Cell type:markdown id:0505e4f6 tags:



#### Motor



%% Cell type:code id:b3128c10 tags:



``` python

%matplotlib inline

# Plot motor speeds as a function of time and input voltage signal

plt.figure(figsize=(8,8))

motor = Motor(mp, sp)

for signal in [2, 4, 6, 8, 10, 12, 14, 16, 18, 20]:

    speeds = []

    motor.reset()

    for i in range(200):

        speeds.append(motor.step(signal))

    plt.plot(speeds, label='%dV' % signal)

plt.legend(ncol=2)

plt.ylabel('Speed rad/s')

plt.xlabel('Time /ms')

```



%% Cell type:code id:42ebfb97 tags:



``` python

from multirotor.helpers import learn_speed_voltage_scaling



def make_motor_fn(params, sp):

    from copy import deepcopy

    params = deepcopy(params)

    params.speed_voltage_scaling = 1.

    def motor_step(signal):

        m = Motor(params, sp)

        for i in range(100):

            s = m.step(signal)

        return s

    return motor_step



print('Voltage = %.5f * speed' % (learn_speed_voltage_scaling(make_motor_fn(mp, sp))))

```



%% Cell type:markdown id:6fb2f5c9 tags:



#### Propeller



%% Cell type:code id:1669687b tags:



``` python

%matplotlib inline

# Plot propeller speed by numerically solving the thrust equation,

# *if* accurate propeller measurements are given in params

pp_ = deepcopy(pp)

pp_.use_thrust_constant = False # Set to true to just use k_thrust

prop = Propeller(pp_, sp)

plt.figure(figsize=(8,8))

speeds = np.linspace(0, 600, num=100)

for a in np.linspace(0, 10, 10, endpoint=False):

    thrusts = []

    for s in speeds:

        thrusts.append(prop.thrust(s, np.asarray([0, 0, a])))

    plt.plot(speeds, thrusts, label='%.1f m/s' % a)

plt.xlabel('Speed rad/s')

plt.ylabel('Thrust /N')

plt.title('Thrust with airspeed')

plt.legend(ncol=2)

```



%% Cell type:markdown id:e7bb489d tags:



#### Vehicle



%% Cell type:code id:ecc23e14 tags:



``` python

# Combine propeller/motor/vehicle to get vehicle.

# Take off simulation

m = Multirotor(vp, sp)

log = DataLog(vehicle=m) # convenient logging class

m.reset()

m.state *= 0 # set to zero, reset() sets random values

action = m.allocate_control(

    thrust=m.weight * 1.1,

    torques=np.asarray([0, 0, 0])

)

for i in range(500):

    m.step_speeds(action)

    log.log()

log.done_logging()

plt.plot(log.z)

```



%% Cell type:markdown id:2c6535f4 tags:



### PID Controller



%% Cell type:code id:33984887 tags:



``` python

# From PID parameters file

def get_controller(m: Multirotor):

    pos = PosController(

        1.0, 0., 0., 1., dt=1e-3, vehicle=m)

        1.0, 0., 0., 1., dt=m.simulation.dt, vehicle=m)

    vel = VelController(

        2.0, 1.0, 0.5, 1000., dt=1e-3, vehicle=m)

        2.0, 1.0, 0.5, 1000., dt=m.simulation.dt, vehicle=m)

    att = AttController(

        [2.6875, 4.5, 4.5],

        0, 0.,

        1., dt=1e-3, vehicle=m)

        1., dt=m.simulation.dt, vehicle=m)

    rat = RateController(

        [0.1655, 0.1655, 0.5],

        [0.135, 0.135, 0.018],

        [0.01234, 0.01234, 0.],

        [0.5,0.5,0.5], dt=1e-3, vehicle=m)

        [0.5,0.5,0.5], dt=m.simulation.dt, vehicle=m)

    alt = AltController(

        1, 0, 0,

        1, dt=1e-3, vehicle=m)

        1, dt=m.simulation.dt, vehicle=m)

    alt_rate = AltRateController(

        5, 0, 0,

        1, dt=1e-3, vehicle=m)

        1, dt=m.simulation.dt, vehicle=m)

    ctrl = Controller(

        pos, vel, att, rat, alt, alt_rate

    )

    return ctrl

```



%% Cell type:code id:d21d73fe tags:



``` python

%matplotlib inline

m = Multirotor(vp, sp)

ctrl = get_controller(m)

log = DataLog(controller=ctrl)

for i in range(100):

    action = ctrl.step((1,1,1,0))

    log.log()

log.done_logging()



plt.plot(log.actions[:,0], ls=':', label='thrust')

lines = plt.gca().lines

plt.twinx()

for s, axis in zip(log.actions.T[1:], ('x','y','z')):

    plt.plot(s, label=axis + '-torque')

plt.legend(handles=plt.gca().lines + lines)

```



%% Cell type:markdown id:cfbc9c25 tags:



#### Attitude Angle Controller



%% Cell type:code id:f012e1f8 tags:



``` python

m = Multirotor(vp, sp)

fz = m.weight

att =  get_controller(m).ctrl_a

log = DataLog(vehicle=m, controller=att, other_vars=('err',))

for i in range(5000):

    ref = np.asarray([np.pi/18, 0, 0])

    # action is prescribed euler rate

    action = att.step(ref, m.orientation)

    # action = np.clip(action, a_min=-0.1, a_max=0.1)

    m.step_dynamics(np.asarray([0, 0, 0, *action]))

    log.log(err=att.err_p[0])

    log._actions[-1] = action

log.done_logging()



plt.plot(log.roll * 180 / np.pi)

plt.twinx()

plt.plot(log.actions[:,0], ls=':', label='Rate rad/s')

```



%% Cell type:markdown id:fdbd88c1 tags:



#### Attitude Rate Controller



%% Cell type:code id:9cc3b317 tags:



``` python

m = Multirotor(vp, sp)

fz = m.weight

ctrl = get_controller(m)

rat = ctrl.ctrl_r

att = ctrl.ctrl_a

log = DataLog(vehicle=m, controller=rat, other_vars=('err',))

for i in range(5000):

    ref = np.asarray([np.pi/18, 0, 0])

    rate = att.step(ref, m.orientation)

    action = rat.step(rate, m.euler_rate)

    action = np.clip(action, a_min=-0.1, a_max=0.1)

    m.step_dynamics(np.asarray([0, 0, 0, *action]))

    log.log(err=rat.err_p[0])

    log._actions[-1] = action

log.done_logging()



plt.plot(log.roll * 180 / np.pi)

plt.twinx()

plt.plot(log.actions[:,0], ls=':')

```



%% Cell type:markdown id:6370aa80 tags:



#### Altitude Controller



%% Cell type:code id:5fcd0d24 tags:



``` python

m = Multirotor(vp, sp)

ctrl = get_controller(m)

alt = ctrl.ctrl_z

alt_rate = ctrl.ctrl_vz

log = DataLog(vehicle=m, controller=alt, other_vars=('thrust',))

for i in range(5000):

    ref = np.asarray([1.])

    rate = alt.step(ref, m.position[2:])

    action = alt_rate.step(rate, m.world_velocity[2:])

    action = np.clip(action, a_min=-2*m.weight, a_max=2*m.weight)

    m.step_dynamics(np.asarray([0, 0, action[0], 0,0,0]))

    log.log(thrust=action)

    #log._actions[-1] = action

log.done_logging()



plt.plot(log.actions.squeeze())

plt.twinx()

plt.plot(log.z, ls=':')

```



%% Cell type:markdown id:f4278c17 tags:



#### Position Controller



%% Cell type:code id:91ae8919 tags:



``` python

m = Multirotor(vp, sp)

ctrl = get_controller(m)

pos = ctrl.ctrl_p

vel = ctrl.ctrl_v

rat = ctrl.ctrl_r

att = ctrl.ctrl_a

log = DataLog(vehicle=m, controller=pos, other_vars=('err', 'att_actions'))

for i in range(5000):

    ref = np.asarray([1.,0.])

    velocity = pos.step(ref, m.position[:2])

    angles = vel.step(velocity, m.velocity[:2])[::-1]

    rate = att.step(np.asarray([*angles, 0]), m.orientation)

    action = rat.step(rate, m.euler_rate)

    action = np.clip(action, a_min=-0.1, a_max=0.1)

    m.step_dynamics(np.asarray([0, 0, m.weight, *action]))

    log.log(err=pos.err_p[0], att_actions=action)

log.done_logging()



plt.plot(log.position[:,0])

plt.plot(log.err)

# plt.plot(log.position[:,1])

plt.twinx()

plt.plot(log.actions[:,0] * 180 / np.pi, ls=':')

plt.plot(log.pitch * 180 / np.pi, ls='-.')

# plt.plot(log.actions[:,0] * 180 / np.pi, ls=':')

```



%% Cell type:markdown id:9eb34672 tags:



### Simulation



%% Cell type:code id:f5f52df4 tags:



``` python

# def wind(t, m):

#     w_inertial = np.asarray([5 * np.sin(t * 2 * np.pi / 4000), 0, 0])

#     dcm = direction_cosine_matrix(*m.orientation)

#     return inertial_to_body(w_inertial, dcm)[:2]

wind = lambda t, m: [0, 0]

def wind(t, m, nominal=False):

    if nominal:

        return np.zeros(3)

    w_inertial = np.asarray([5 * np.sin(t * 2 * np.pi / 4000), 0, 0])

    dcm = direction_cosine_matrix(*m.orientation)

    return inertial_to_body(w_inertial, dcm)

```



%% Cell type:code id:d60f1ca5 tags:



``` python

from pyscurve import plot_trajectory

```



%% Cell type:code id:a98de44f tags:



``` python

m = Multirotor(vp, sp)

env = LocalOctorotor(vehicle=m)



# for _ in range(5000):

#     state, *_ = env.step(np.asarray([0., 0., m.weight * 1.01, 0., 0., 0.]))

env = LocalOctorotor(vehicle=Multirotor(vp, sp))



waypoints = [[0,50,2], [50,50,2], [50,0,2], [25,-25,2]]

traj = GuidedTrajectory(env.vehicle, waypoints, proximity=2)

# traj = Trajectory(env.vehicle, waypoints, proximity=2, resolution=None)



ctrl = get_controller(m)

ctrl = get_controller(env.vehicle)



errs = SimpleNamespace()

errs.pos = SimpleNamespace()

errs.pos.p, errs.pos.i, errs.pos.d = [], [], []

errs.att = SimpleNamespace()

errs.att.p, errs.att.i, errs.att.d = [], [], []



log = DataLog(env.vehicle, ctrl,

              other_vars=('speeds','target', 'alloc_errs',

                          'ctrl_p', 'leash', 'err_p', 'ff_vel',

                           'currents', 'voltages'))



for i, (pos, feed_forward_vel) in tqdm(enumerate(traj), leave=False, total=60000):

    if i==30000: break

    if i==1000: break

    # Generate reference for controller

    ref = np.asarray([*pos, 0.])

    # Get prescribed dynamics for system as thrust and torques

    dynamics = ctrl.step(ref, feed_forward_velocity=feed_forward_vel)

    thrust, torques = dynamics[0], dynamics[1:]

    # Allocate control: Convert dynamics into motor rad/s

    action = m.allocate_control(thrust, torques)

    action = env.vehicle.allocate_control(thrust, torques)

    # get any disturbances

    wind_force = wind(i, env.vehicle, nominal=False)

    # Send speeds to environment

    state, *_ = env.step(

        action, disturb_forces=0, disturb_torques=0

        action, disturb_forces=wind_force, disturb_torques=0

    )



    for (c, e) in zip((ctrl.ctrl_p, ctrl.ctrl_a), (errs.pos, errs.att)):

        e.p.append(c.err_p)

        e.i.append(c.err_i)

        e.d.append(c.err_d)

    alloc_errs = np.asarray([thrust, *torques]) - m.alloc @ action**2

    alloc_errs = np.asarray([thrust, *torques]) - env.vehicle.alloc @ action**2



    log.log(speeds=action, target=pos, alloc_errs=alloc_errs,

            ctrl_p=ctrl.ctrl_p.action, leash=ctrl.ctrl_p.leash,

            err_p=ctrl.ctrl_p.err, ff_vel=feed_forward_velocity,

            currents=[p.motor.current for p in m.propellers],

            voltages=[p.motor.voltage for p in m.propellers])

            err_p=ctrl.ctrl_p.err, ff_vel=feed_forward_vel,

            currents=[p.motor.current_average(env.vehicle.battery.params.max_voltage) for p in env.vehicle.propellers],

            voltages=[p.motor.voltage for p in env.vehicle.propellers])



    if np.any(np.abs(m.orientation[:2]) > np.pi/6): break

    if np.any(np.abs(env.vehicle.orientation[:2]) > np.pi/6): break



log.done_logging()

currents = np.asarray(currents)

```



%% Cell type:code id:2d1b0058 tags:



``` python

plt.plot(log.currents, ls=':')

plt.ylim(0, 30)

plt.ylabel('Motor current /A')

plt.xlabel('Time /ms')

plt.title('Rectangular trajectory')

plt.title('Individual motor currents')

```



%% Cell type:code id:f0aa49e1 tags:



``` python

plt.plot(log.voltages, ls=':')

plt.ylim(0, 30)

plt.ylabel('Motor voltage /A')

plt.xlabel('Time /ms')

plt.title('Rectangular trajectory')

plt.title('Voltages')

```



%% Cell type:code id:5d64dbce tags:



``` python

plot_trajectory(traj.trajs[-1], dt=0.1)

```



%% Cell type:code id:81a8043e tags:



``` python

%matplotlib inline

plt.figure(figsize=(21,10.5))

plot_grid = (3,3)

plt.subplot(*plot_grid,1)



n = len(log)



plt.plot(log.x, label='x', c='r')

plt.plot(log.target[:, 0], c='r', ls=':')

plt.plot(log.y, label='y', c='g')

plt.plot(log.target[:, 1], c='g', ls=':')

plt.plot(log.z, label='z', c='b')

lines = plt.gca().lines[::2]

plt.ylabel('Position /m')

plt.twinx()

plt.plot(log.roll * (180 / np.pi), label='roll', c='c', ls=':')

plt.plot(log.pitch * (180 / np.pi), label='pitch', c='m', ls=':')

plt.plot(log.yaw * (180 / np.pi), label='yaw', c='y', ls=':')

plt.ylabel('Orientation /deg')

plt.legend(handles=plt.gca().lines + lines, ncol=2)

plt.title('Position and Orientation')



plt.subplot(*plot_grid,2)

for i in range(log.speeds.shape[1]):

    l, = plt.plot(log.speeds[:,i], label='prop %d' % i)

#     plt.plot(speeds[:,i], c=l.get_c())

lines = plt.gca().lines

plt.legend(handles=lines, ncol=2)

plt.title('Motor speeds /RPM')





plt.subplot(*plot_grid,3)

v_world = np.zeros_like(log.velocity)

for i, (v, o) in enumerate(zip(log.velocity, log.orientation)):

    dcm = direction_cosine_matrix(*o)

    v_world[i] = body_to_inertial(v, dcm)

for i, c, a in zip(range(3), 'rgb', 'xyz'):

    plt.plot(v_world[:,i], label='Velocity %s' % a, c=c)

#     plt.plot(velocities[:,i], label='Velocity %s' % a, c=c)

plt.legend()

plt.title('Velocities')



plt.subplot(*plot_grid,4)

plt.title('Controller allocated dynamics')

l = plt.plot(log.actions[:,0], label='Ctrl Thrust')

plt.ylabel('Force /N')

plt.twinx()

for i, c, a in zip(range(3), 'rgb', 'xyz'):

    plt.plot(log.actions[:,1+i], label='Ctrl Torque %s' % a, c=c)

plt.ylabel('Torque /Nm')

plt.legend(handles=plt.gca().lines + l, ncol=2)



plt.subplot(*plot_grid,5)

lines = plt.plot(log.alloc_errs[:, 0], label='Thrust err', c='b')

plt.ylabel('Thrust /N')

plt.twinx()

plt.plot(log.alloc_errs[:, 1], label='Torque x err', ls=':')

plt.plot(log.alloc_errs[:, 2], label='Torque y err', ls=':')

plt.plot(log.alloc_errs[:, 3], label='Torque z err', ls=':')

plt.legend(handles = plt.gca().lines + lines, ncol=2)

plt.ylabel('Torque /Nm')

plt.title('Allocation Errors')



plt.subplot(*plot_grid,6)

plt.plot(log.target[:,0], log.target[:,1], label='Prescribed traj')

plt.plot(log.x, log.y, label='Actual traj', ls=':')

plt.gca().set_aspect('equal', 'box')

plt.title('XY positions /m')

plt.legend()



plt.tight_layout()

```



%% Cell type:code id:c17d8b15 tags:



``` python

%matplotlib inline

for e in (errs.pos, errs.att):

    e.p = np.asarray(e.p)

    e.i = np.asarray(e.i)

    e.d = np.asarray(e.d)

lines = []

plt.figure(figsize=(21,24))

plt.subplot(6,1,1)

plt.plot(errs.pos.p[:,0], label='Pos-x P', c='r', ls='-')

plt.plot(errs.pos.p[:,1], label='Pos-y P', c='g', ls='-')

lines += plt.gca().lines

plt.title('Position P errors')

plt.subplot(6,1, 2)

plt.plot(errs.pos.i[:, 0], label='Pos-x I', c='r', ls=':')

plt.plot(errs.pos.i[:, 1], label='Pos-y I', c='g', ls=':')

lines += plt.gca().lines

plt.title('Position I errors')

plt.subplot(6,1, 3)

plt.plot(errs.pos.d[:, 0], label='Pos-x D', c='r', ls='-.')

plt.plot(errs.pos.d[:, 1], label='Pos-y D', c='g', ls='-.')

lines += plt.gca().lines

plt.legend(handles=lines)

plt.title('Position D errors')

lines = []

plt.subplot(6,1,4)

plt.plot(errs.att.p[:,0], label='Att-x P', c='r', ls='-')

plt.plot(errs.att.p[:,1], label='Att-y P', c='g', ls='-')

lines += plt.gca().lines

plt.title('Attitude P errors')

plt.subplot(6,1, 5)

plt.plot(errs.att.i[:, 0], label='Att-x I', c='r', ls=':')

plt.plot(errs.att.i[:, 1], label='Att-y I', c='g', ls=':')

lines += plt.gca().lines

plt.title('Attitude I errors')

plt.subplot(6,1, 6)

plt.plot(errs.att.d[:, 0], label='Att-x D', c='r', ls='-.')

plt.plot(errs.att.d[:, 1], label='Att-y D', c='g', ls='-.')

lines += plt.gca().lines

plt.legend(handles=lines)

plt.title('Attitude D errors')

```



%% Cell type:code id:d9d99572 tags:



``` python

%matplotlib notebook

fig = plt.figure()

xlim = ylim = zlim = (np.min(log.position), np.max(log.position))

ax = fig.add_subplot(projection='3d', xlim=xlim, ylim=ylim, zlim=zlim)

ax.set_xlabel('x')

ax.set_ylabel('y')

ax.set_zlabel('z')

ax.plot(log.x, log.y, log.z)

```

multirotor/controller/guided.py

deleted100644 → 0
+0 −23
Original line number Diff line number Diff line 
"""

Guided mode control. Generates x,y,z,yaw references for PID controllers.

"""



import numpy as np







class GuidedTrajectory:





    def __init__(self, vehicle, controller) -> None:

        self.vehicle = vehicle

        self.controller = controller

        self.waypoints = []





    def add_waypoint(self, waypoint: np.ndarray):

        self.waypoints.append(np.asarray(waypoint))





    def __iter__(self):

        pass
 
 No newline at end of file

multirotor/controller/pid.py

+21 −13
Original line number Diff line number Diff line
@@ -147,7 +147,7 @@ class PosController(PIDController): 
    "Maximum acceleration in m/s/s"

    max_jerk: float = 100.0

    "Maximum jerk in m/s/s/s"

    square_root_scaling: bool = True

    square_root_scaling: bool = False

    "Whether to scale P-gain with the square root of the error"

    leashing: bool = False

    "Whether to limit proportional position error"
@@ -158,35 +158,43 @@ class PosController(PIDController): 
        # Att angle controller is strictly a P controller

        self.k_i = np.zeros(2) * np.asarray(self.k_i)

        self.k_d = np.zeros(2) * np.asarray(self.k_d)

        self.leash = 0 if self.leashing else np.inf

        if self.leashing or self.square_root_scaling:

            self.k_p[:] = 0.5 * self.max_jerk / self.max_acceleration

        super().__post_init__()





    def step(self, reference, measurement):

        # inertial frame velocity

        err = reference - measurement

        err_len = np.linalg.norm(err)

        k_p = 0.5 * self.max_jerk / self.max_acceleration

        if self.leashing:

    @property

    def leash(self) -> float:

        if not self.leashing:

            return np.inf

        # https://nrotella.github.io/journal/arducopter-flight-controllers.html

        acc = self.vehicle.inertial_acceleration[:2]

        acc_mag = np.linalg.norm(acc)

        vel = self.vehicle.inertial_velocity[:2]

        vel_mag = np.linalg.norm(vel)

            self.leash = np.abs(acc_mag / (2 * k_p**2) + vel_mag**2 / (2 * acc_mag + 1e-6))

            self.leash = np.inf if self.leash==0 else self.leash

        leash = np.abs(acc_mag / (2 * self.k_p[0]**2) + vel_mag**2 / (2 * acc_mag + 1e-6))

        leash = np.inf if leash==0 else leash

        return leash





    def step(self, reference, measurement):

        # inertial frame velocity

        err = reference - measurement

        err_len = np.linalg.norm(err)

        if self.leashing:

            err_unit = err / (err_len + 1e-6)

            err_len = min(err_len, self.leash)

            err = err_unit * err_len

            self.err = err

            velocity = k_p * err

            velocity = self.err_p = self.k_p * err

        if err_len > 0. and self.square_root_scaling:

            velocity = np.zeros_like(self.k_p)

            velocity[0] = sqrt_control(err[0], k_p, self.max_acceleration, self.dt)

            velocity[1] = sqrt_control(err[1], k_p, self.max_acceleration, self.dt)

            velocity[0] = sqrt_control(err[0], self.k_p[0], self.max_acceleration, self.dt)

            velocity[1] = sqrt_control(err[1], self.k_p[1], self.max_acceleration, self.dt)

            # scale velocity correction by error size

            # velocity = (np.abs(err) / err_len) * velocity

            self.err = err

            self.err_p = velocity

        else:

            velocity = super().step(reference, measurement)

        # convert to body-frame velocity

multirotor/env.py

+1 −1
Original line number Diff line number Diff line
@@ -129,7 +129,7 @@ class SpeedsMultirotorEnv(BaseMultirotorEnv): 
    """





    def __init__(self, vehicle) -> None:

    def __init__(self, vehicle: Multirotor) -> None:

        """



        Parameters

multirotor/simulation.py

+33 −2
Original line number Diff line number Diff line
@@ -133,6 +133,24 @@ class Motor: 
        self._last_angular_acc = 0.





    def current_average(self, max_voltage: float) -> float:

        """

        Average current consumption given the duty cycle of the speed controller.

        Duty cycle depends on max voltage which causes 100% duty cycle.



        Parameters

        ----------

        max_voltage : float

            The peak voltage corresponding to 100% duty cycle.



        Returns

        -------

        float

            Current consumption

        """

        duty_cycle = self.voltage / max_voltage

        return self.current * duty_cycle





    def apply_speed(self, u: float, max_voltage: float=np.inf) -> float:

        """
@@ -181,7 +199,7 @@ class Motor: 
            The speed of the motor (rad /s)

        """

        self.voltage = np.clip(self.params.speed_voltage_scaling * u, 0, max_voltage)

        self.current = max(0, (self.voltage - self.speed * self.params.k_emf) / self.params.resistance)

        self.current = np.clip((self.voltage - self.speed * self.params.k_emf) / self.params.resistance, 0, self.params.max_current)

        torque = self.params.k_torque * self.current

        # Subtract drag torque and dynamic friction from electrical torque

        net_torque = torque - \
@@ -348,6 +366,16 @@ class Multirotor: 
        return self.simulation.g * self.params.mass





    @property

    def current_average(self) -> float:

        """Duty-cucle adjusted currrent draw from battery."""

        peak_voltage = self.battery.params.max_voltage

        currents = np.asarray([p.motor.current for p in self.propellers])

        voltages = np.asarray([p.motor.voltage for p in self.propellers])

        duty_cycle = voltages / peak_voltage

        return np.sum(duty_cycle * currents)





    def get_forces_torques(self, speeds: np.ndarray, state: np.ndarray) -> Tuple[np.ndarray, np.ndarray]:

        """

        Calculate the forces and torques acting on the vehicle's center of gravity
@@ -518,7 +546,10 @@ class Multirotor: 
            The new state of the vehicle.

        """

        self.t += self.simulation.dt

        self._dxdt = self.dxdt_speeds(t=self.t, x=self.state, u=u)

        self._dxdt = self.dxdt_speeds(

            t=self.t, x=self.state, u=u,

            disturb_forces=disturb_forces, disturb_torques=disturb_torques

        )

        self.state = odeint(

            self.dxdt_speeds, self.state, (0, self.simulation.dt),

            args=(u, disturb_forces, disturb_torques),