[wpimath] Clean up NumericalIntegration and add Discretization tests (#3489)

* Rename Butcher tableau sections in NumericalIntegration such that
  top-left is c, top-right is A, and bottom-right is b
* Move edu.wpi.first.math.Discretization to
  edu.wpi.first.math.system.Discretization
* Sort Java Discretization to match C++ function order
* Add tests for Java Discretization
  * Required adding Runge-Kutta time-varying impl to tests
* Move C++ Runge-Kutta time-varying impl to tests only
  * Users don't need it
This commit is contained in:
Tyler Veness
2021-07-25 07:42:59 -07:00
committed by GitHub
parent bfc209b120
commit 50af74c38f
20 changed files with 641 additions and 310 deletions

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@@ -12,6 +12,7 @@ import edu.wpi.first.math.geometry.Pose2d;
import edu.wpi.first.math.geometry.Rotation2d;
import edu.wpi.first.math.numbers.N1;
import edu.wpi.first.math.numbers.N2;
import edu.wpi.first.math.system.Discretization;
import java.util.ArrayList;
import java.util.List;
import org.ejml.dense.row.MatrixFeatures_DDRM;

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@@ -8,7 +8,6 @@ import static org.junit.jupiter.api.Assertions.assertDoesNotThrow;
import static org.junit.jupiter.api.Assertions.assertEquals;
import static org.junit.jupiter.api.Assertions.assertTrue;
import edu.wpi.first.math.Discretization;
import edu.wpi.first.math.Matrix;
import edu.wpi.first.math.Nat;
import edu.wpi.first.math.StateSpaceUtil;
@@ -19,6 +18,7 @@ import edu.wpi.first.math.numbers.N1;
import edu.wpi.first.math.numbers.N2;
import edu.wpi.first.math.numbers.N4;
import edu.wpi.first.math.numbers.N6;
import edu.wpi.first.math.system.Discretization;
import edu.wpi.first.math.system.NumericalIntegration;
import edu.wpi.first.math.system.NumericalJacobian;
import edu.wpi.first.math.system.plant.DCMotor;

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@@ -0,0 +1,215 @@
// Copyright (c) FIRST and other WPILib contributors.
// Open Source Software; you can modify and/or share it under the terms of
// the WPILib BSD license file in the root directory of this project.
package edu.wpi.first.math.system;
import static org.junit.jupiter.api.Assertions.assertEquals;
import static org.junit.jupiter.api.Assertions.assertTrue;
import edu.wpi.first.math.MatBuilder;
import edu.wpi.first.math.Matrix;
import edu.wpi.first.math.Nat;
import edu.wpi.first.math.VecBuilder;
import edu.wpi.first.math.numbers.N2;
import org.junit.jupiter.api.Test;
public class DiscretizationTest {
// Check that for a simple second-order system that we can easily analyze
// analytically,
@Test
public void testDiscretizeA() {
final var contA = new MatBuilder<>(Nat.N2(), Nat.N2()).fill(0, 1, 0, 0);
final var x0 = VecBuilder.fill(1, 1);
final var discA = Discretization.discretizeA(contA, 1.0);
final var x1Discrete = discA.times(x0);
// We now have pos = vel = 1 and accel = 0, which should give us:
final var x1Truth =
VecBuilder.fill(
1.0 * x0.get(0, 0) + 1.0 * x0.get(1, 0), 0.0 * x0.get(0, 0) + 1.0 * x0.get(1, 0));
assertEquals(x1Truth, x1Discrete);
}
// Check that for a simple second-order system that we can easily analyze
// analytically,
@Test
public void testDiscretizeAB() {
final var contA = new MatBuilder<>(Nat.N2(), Nat.N2()).fill(0, 1, 0, 0);
final var contB = new MatBuilder<>(Nat.N2(), Nat.N1()).fill(0, 1);
final var x0 = VecBuilder.fill(1, 1);
final var u = VecBuilder.fill(1);
var discABPair = Discretization.discretizeAB(contA, contB, 1.0);
var discA = discABPair.getFirst();
var discB = discABPair.getSecond();
var x1Discrete = discA.times(x0).plus(discB.times(u));
// We now have pos = vel = accel = 1, which should give us:
final var x1Truth =
VecBuilder.fill(
1.0 * x0.get(0, 0) + 1.0 * x0.get(1, 0) + 0.5 * u.get(0, 0),
0.0 * x0.get(0, 0) + 1.0 * x0.get(1, 0) + 1.0 * u.get(0, 0));
assertEquals(x1Truth, x1Discrete);
}
// Test that the discrete approximation of Q is roughly equal to
// integral from 0 to dt of e^(A tau) Q e^(A.T tau) dtau
@Test
public void testDiscretizeSlowModelAQ() {
final var contA = new MatBuilder<>(Nat.N2(), Nat.N2()).fill(0, 1, 0, 0);
final var contQ = new MatBuilder<>(Nat.N2(), Nat.N2()).fill(1, 0, 0, 1);
final double dt = 1.0;
final var discQIntegrated =
RungeKuttaTimeVarying.rungeKuttaTimeVarying(
(Double t, Matrix<N2, N2> x) ->
contA.times(t).exp().times(contQ).times(contA.transpose().times(t).exp()),
0.0,
new Matrix<>(Nat.N2(), Nat.N2()),
dt);
var discAQPair = Discretization.discretizeAQ(contA, contQ, dt);
var discQ = discAQPair.getSecond();
assertTrue(
discQIntegrated.minus(discQ).normF() < 1e-10,
"Expected these to be nearly equal:\ndiscQ:\n"
+ discQ
+ "\ndiscQIntegrated:\n"
+ discQIntegrated);
}
// Test that the discrete approximation of Q is roughly equal to
// integral from 0 to dt of e^(A tau) Q e^(A.T tau) dtau
@Test
public void testDiscretizeFastModelAQ() {
final var contA = new MatBuilder<>(Nat.N2(), Nat.N2()).fill(0, 1, 0, -1406.29);
final var contQ = new MatBuilder<>(Nat.N2(), Nat.N2()).fill(0.0025, 0, 0, 1);
final var dt = 0.005;
final var discQIntegrated =
RungeKuttaTimeVarying.rungeKuttaTimeVarying(
(Double t, Matrix<N2, N2> x) ->
contA.times(t).exp().times(contQ).times(contA.transpose().times(t).exp()),
0.0,
new Matrix<>(Nat.N2(), Nat.N2()),
dt);
var discAQPair = Discretization.discretizeAQ(contA, contQ, dt);
var discQ = discAQPair.getSecond();
assertTrue(
discQIntegrated.minus(discQ).normF() < 1e-3,
"Expected these to be nearly equal:\ndiscQ:\n"
+ discQ
+ "\ndiscQIntegrated:\n"
+ discQIntegrated);
}
// Test that the Taylor series discretization produces nearly identical results.
@Test
public void testDiscretizeSlowModelAQTaylor() {
final var contA = new MatBuilder<>(Nat.N2(), Nat.N2()).fill(0, 1, 0, 0);
final var contQ = new MatBuilder<>(Nat.N2(), Nat.N2()).fill(1, 0, 0, 1);
final var dt = 1.0;
// Continuous Q should be positive semidefinite
final var esCont = contQ.getStorage().eig();
for (int i = 0; i < contQ.getNumRows(); ++i) {
assertTrue(esCont.getEigenvalue(i).real >= 0);
}
final var discQIntegrated =
RungeKuttaTimeVarying.rungeKuttaTimeVarying(
(Double t, Matrix<N2, N2> x) ->
contA.times(t).exp().times(contQ).times(contA.transpose().times(t).exp()),
0.0,
new Matrix<>(Nat.N2(), Nat.N2()),
dt);
var discA = Discretization.discretizeA(contA, dt);
var discAQPair = Discretization.discretizeAQ(contA, contQ, dt);
var discATaylor = discAQPair.getFirst();
var discQTaylor = discAQPair.getSecond();
assertTrue(
discQIntegrated.minus(discQTaylor).normF() < 1e-10,
"Expected these to be nearly equal:\ndiscQTaylor:\n"
+ discQTaylor
+ "\ndiscQIntegrated:\n"
+ discQIntegrated);
assertTrue(discA.minus(discATaylor).normF() < 1e-10);
// Discrete Q should be positive semidefinite
final var esDisc = discQTaylor.getStorage().eig();
for (int i = 0; i < discQTaylor.getNumRows(); ++i) {
assertTrue(esDisc.getEigenvalue(i).real >= 0);
}
}
// Test that the Taylor series discretization produces nearly identical results.
@Test
public void testDiscretizeFastModelAQTaylor() {
final var contA = new MatBuilder<>(Nat.N2(), Nat.N2()).fill(0, 1, 0, -1500);
final var contQ = new MatBuilder<>(Nat.N2(), Nat.N2()).fill(0.0025, 0, 0, 1);
final var dt = 0.005;
// Continuous Q should be positive semidefinite
final var esCont = contQ.getStorage().eig();
for (int i = 0; i < contQ.getNumRows(); ++i) {
assertTrue(esCont.getEigenvalue(i).real >= 0);
}
final var discQIntegrated =
RungeKuttaTimeVarying.rungeKuttaTimeVarying(
(Double t, Matrix<N2, N2> x) ->
contA.times(t).exp().times(contQ).times(contA.transpose().times(t).exp()),
0.0,
new Matrix<>(Nat.N2(), Nat.N2()),
dt);
var discA = Discretization.discretizeA(contA, dt);
var discAQPair = Discretization.discretizeAQ(contA, contQ, dt);
var discATaylor = discAQPair.getFirst();
var discQTaylor = discAQPair.getSecond();
assertTrue(
discQIntegrated.minus(discQTaylor).normF() < 1e-3,
"Expected these to be nearly equal:\ndiscQTaylor:\n"
+ discQTaylor
+ "\ndiscQIntegrated:\n"
+ discQIntegrated);
assertTrue(discA.minus(discATaylor).normF() < 1e-10);
// Discrete Q should be positive semidefinite
final var esDisc = discQTaylor.getStorage().eig();
for (int i = 0; i < discQTaylor.getNumRows(); ++i) {
assertTrue(esDisc.getEigenvalue(i).real >= 0);
}
}
// Test that DiscretizeR() works
@Test
public void testDiscretizeR() {
var contR = Matrix.mat(Nat.N2(), Nat.N2()).fill(2.0, 0.0, 0.0, 1.0);
var discRTruth = Matrix.mat(Nat.N2(), Nat.N2()).fill(4.0, 0.0, 0.0, 2.0);
var discR = Discretization.discretizeR(contR, 0.5);
assertTrue(
discRTruth.minus(discR).normF() < 1e-10,
"Expected these to be nearly equal:\ndiscR:\n" + discR + "\ndiscRTruth:\n" + discRTruth);
}
}

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@@ -14,11 +14,9 @@ import org.junit.jupiter.api.Test;
public class NumericalIntegrationTest {
@Test
@SuppressWarnings({"ParameterName", "LocalVariableName"})
public void testExponential() {
Matrix<N1, N1> y0 = VecBuilder.fill(0.0);
//noinspection SuspiciousNameCombination
var y1 =
NumericalIntegration.rk4(
(Matrix<N1, N1> x) -> {
@@ -33,11 +31,9 @@ public class NumericalIntegrationTest {
}
@Test
@SuppressWarnings({"ParameterName", "LocalVariableName"})
public void testExponentialRKF45() {
Matrix<N1, N1> y0 = VecBuilder.fill(0.0);
//noinspection SuspiciousNameCombination
var y1 =
NumericalIntegration.rkf45(
(x, u) -> {
@@ -53,11 +49,9 @@ public class NumericalIntegrationTest {
}
@Test
@SuppressWarnings({"ParameterName", "LocalVariableName"})
public void testExponentialRKDP() {
Matrix<N1, N1> y0 = VecBuilder.fill(0.0);
//noinspection SuspiciousNameCombination
var y1 =
NumericalIntegration.rkdp(
(x, u) -> {

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@@ -0,0 +1,41 @@
// Copyright (c) FIRST and other WPILib contributors.
// Open Source Software; you can modify and/or share it under the terms of
// the WPILib BSD license file in the root directory of this project.
package edu.wpi.first.math.system;
import edu.wpi.first.math.Matrix;
import edu.wpi.first.math.Num;
import java.util.function.BiFunction;
public final class RungeKuttaTimeVarying {
private RungeKuttaTimeVarying() {
// Utility class
}
/**
* Performs 4th order Runge-Kutta integration of dx/dt = f(t, y) for dt.
*
* @param <Rows> Rows in y.
* @param <Cols> Columns in y.
* @param f The function to integrate. It must take two arguments t and y.
* @param t The initial value of t.
* @param y The initial value of y.
* @param dtSeconds The time over which to integrate.
*/
@SuppressWarnings("MethodTypeParameterName")
public static <Rows extends Num, Cols extends Num> Matrix<Rows, Cols> rungeKuttaTimeVarying(
BiFunction<Double, Matrix<Rows, Cols>, Matrix<Rows, Cols>> f,
double t,
Matrix<Rows, Cols> y,
double dtSeconds) {
final var h = dtSeconds;
Matrix<Rows, Cols> k1 = f.apply(t, y);
Matrix<Rows, Cols> k2 = f.apply(t + dtSeconds * 0.5, y.plus(k1.times(h * 0.5)));
Matrix<Rows, Cols> k3 = f.apply(t + dtSeconds * 0.5, y.plus(k2.times(h * 0.5)));
Matrix<Rows, Cols> k4 = f.apply(t + dtSeconds, y.plus(k3.times(h)));
return y.plus((k1.plus(k2.times(2.0)).plus(k3.times(2.0)).plus(k4)).times(h / 6.0));
}
}

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@@ -0,0 +1,43 @@
// Copyright (c) FIRST and other WPILib contributors.
// Open Source Software; you can modify and/or share it under the terms of
// the WPILib BSD license file in the root directory of this project.
package edu.wpi.first.math.system;
import static org.junit.jupiter.api.Assertions.assertEquals;
import edu.wpi.first.math.MatBuilder;
import edu.wpi.first.math.Matrix;
import edu.wpi.first.math.Nat;
import edu.wpi.first.math.numbers.N1;
import org.junit.jupiter.api.Test;
public class RungeKuttaTimeVaryingTest {
private static Matrix<N1, N1> rungeKuttaTimeVaryingSolution(double t) {
return new MatBuilder<>(Nat.N1(), Nat.N1())
.fill(12.0 * Math.exp(t) / (Math.pow(Math.exp(t) + 1.0, 2.0)));
}
// Tests RK4 with a time varying solution. From
// http://www2.hawaii.edu/~jmcfatri/math407/RungeKuttaTest.html:
// x' = x (2 / (e^t + 1) - 1)
//
// The true (analytical) solution is:
//
// x(t) = 12 * e^t / ((e^t + 1)^2)
@Test
public void rungeKuttaTimeVaryingTest() {
final var y0 = rungeKuttaTimeVaryingSolution(5.0);
final var y1 =
RungeKuttaTimeVarying.rungeKuttaTimeVarying(
(Double t, Matrix<N1, N1> x) -> {
return new MatBuilder<>(Nat.N1(), Nat.N1())
.fill(x.get(0, 0) * (2.0 / (Math.exp(t) + 1.0) - 1.0));
},
5.0,
y0,
1.0);
assertEquals(rungeKuttaTimeVaryingSolution(6.0).get(0, 0), y1.get(0, 0), 1e-3);
}
}