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[wpimath] Add time-varying RKDP (#7362)
This makes the ground truth for the Taylor series AQ discretization more accurate.
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@@ -51,6 +51,26 @@ T RK4(F&& f, T x, U u, units::second_t dt) {
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return x + h / 6.0 * (k1 + 2.0 * k2 + 2.0 * k3 + k4);
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}
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/**
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* Performs 4th order Runge-Kutta integration of dy/dt = f(t, y) for dt.
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*
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* @param f The function to integrate. It must take two arguments t and y.
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* @param t The initial value of t.
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* @param y The initial value of y.
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* @param dt The time over which to integrate.
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*/
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template <typename F, typename T>
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T RK4(F&& f, units::second_t t, T y, units::second_t dt) {
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const auto h = dt.to<double>();
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T k1 = f(t, y);
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T k2 = f(t + dt * 0.5, y + h * k1 * 0.5);
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T k3 = f(t + dt * 0.5, y + h * k2 * 0.5);
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T k4 = f(t + dt, y + h * k3);
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return y + h / 6.0 * (k1 + 2.0 * k2 + 2.0 * k3 + k4);
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}
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/**
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* Performs adaptive Dormand-Prince integration of dx/dt = f(x, u) for dt.
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*
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@@ -134,4 +154,87 @@ T RKDP(F&& f, T x, U u, units::second_t dt, double maxError = 1e-6) {
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return x;
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}
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/**
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* Performs adaptive Dormand-Prince integration of dy/dt = f(t, y) for dt.
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*
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* @param f The function to integrate. It must take two arguments t and
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* y.
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* @param t The initial value of t.
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* @param y The initial value of y.
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* @param dt The time over which to integrate.
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* @param maxError The maximum acceptable truncation error. Usually a small
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* number like 1e-6.
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*/
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template <typename F, typename T>
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T RKDP(F&& f, units::second_t t, T y, units::second_t dt,
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double maxError = 1e-6) {
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// See https://en.wikipedia.org/wiki/Dormand%E2%80%93Prince_method for the
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// Butcher tableau the following arrays came from.
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constexpr int kDim = 7;
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// clang-format off
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constexpr double A[kDim - 1][kDim - 1]{
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{ 1.0 / 5.0},
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{ 3.0 / 40.0, 9.0 / 40.0},
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{ 44.0 / 45.0, -56.0 / 15.0, 32.0 / 9.0},
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{19372.0 / 6561.0, -25360.0 / 2187.0, 64448.0 / 6561.0, -212.0 / 729.0},
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{ 9017.0 / 3168.0, -355.0 / 33.0, 46732.0 / 5247.0, 49.0 / 176.0, -5103.0 / 18656.0},
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{ 35.0 / 384.0, 0.0, 500.0 / 1113.0, 125.0 / 192.0, -2187.0 / 6784.0, 11.0 / 84.0}};
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// clang-format on
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constexpr std::array<double, kDim> b1{
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35.0 / 384.0, 0.0, 500.0 / 1113.0, 125.0 / 192.0, -2187.0 / 6784.0,
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11.0 / 84.0, 0.0};
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constexpr std::array<double, kDim> b2{5179.0 / 57600.0, 0.0,
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7571.0 / 16695.0, 393.0 / 640.0,
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-92097.0 / 339200.0, 187.0 / 2100.0,
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1.0 / 40.0};
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constexpr std::array<double, kDim - 1> c{1.0 / 5.0, 3.0 / 10.0, 4.0 / 5.0,
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8.0 / 9.0, 1.0, 1.0};
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T newY;
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double truncationError;
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double dtElapsed = 0.0;
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double h = dt.to<double>();
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// Loop until we've gotten to our desired dt
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while (dtElapsed < dt.to<double>()) {
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do {
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// Only allow us to advance up to the dt remaining
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h = std::min(h, dt.to<double>() - dtElapsed);
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// clang-format off
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T k1 = f(t, y);
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T k2 = f(t + units::second_t{h} * c[0], y + h * (A[0][0] * k1));
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T k3 = f(t + units::second_t{h} * c[1], y + h * (A[1][0] * k1 + A[1][1] * k2));
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T k4 = f(t + units::second_t{h} * c[2], y + h * (A[2][0] * k1 + A[2][1] * k2 + A[2][2] * k3));
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T k5 = f(t + units::second_t{h} * c[3], y + h * (A[3][0] * k1 + A[3][1] * k2 + A[3][2] * k3 + A[3][3] * k4));
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T k6 = f(t + units::second_t{h} * c[4], y + h * (A[4][0] * k1 + A[4][1] * k2 + A[4][2] * k3 + A[4][3] * k4 + A[4][4] * k5));
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// clang-format on
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// Since the final row of A and the array b1 have the same coefficients
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// and k7 has no effect on newY, we can reuse the calculation.
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newY = y + h * (A[5][0] * k1 + A[5][1] * k2 + A[5][2] * k3 +
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A[5][3] * k4 + A[5][4] * k5 + A[5][5] * k6);
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T k7 = f(t + units::second_t{h} * c[5], newY);
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truncationError = (h * ((b1[0] - b2[0]) * k1 + (b1[1] - b2[1]) * k2 +
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(b1[2] - b2[2]) * k3 + (b1[3] - b2[3]) * k4 +
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(b1[4] - b2[4]) * k5 + (b1[5] - b2[5]) * k6 +
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(b1[6] - b2[6]) * k7))
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.norm();
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h *= 0.9 * std::pow(maxError / truncationError, 1.0 / 5.0);
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} while (truncationError > maxError);
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dtElapsed += h;
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y = newY;
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}
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return y;
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}
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} // namespace frc
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