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https://github.com/wpilibsuite/allwpilib
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163 lines
4.3 KiB
C++
163 lines
4.3 KiB
C++
// Copyright (c) FIRST and other WPILib contributors.
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// Open Source Software; you can modify and/or share it under the terms of
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// the WPILib BSD license file in the root directory of this project.
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#pragma once
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#include <array>
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#include <functional>
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#include <Eigen/QR>
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#include "frc/EigenCore.h"
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#include "frc/system/Discretization.h"
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#include "frc/system/LinearSystem.h"
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#include "units/time.h"
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namespace frc {
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/**
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* Constructs a plant inversion model-based feedforward from a LinearSystem.
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*
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* The feedforward is calculated as <strong> u_ff = B<sup>+</sup> (r_k+1 - A
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* r_k) </strong>, where <strong> B<sup>+</sup> </strong> is the pseudoinverse
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* of B.
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*
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* For more on the underlying math, read
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* https://file.tavsys.net/control/controls-engineering-in-frc.pdf.
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*
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* @tparam States The number of states.
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* @tparam Inputs The number of inputs.
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*/
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template <int States, int Inputs>
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class LinearPlantInversionFeedforward {
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public:
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using StateVector = Vectord<States>;
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using InputVector = Vectord<Inputs>;
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/**
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* Constructs a feedforward with the given plant.
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*
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* @tparam Outputs The number of outputs.
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* @param plant The plant being controlled.
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* @param dt Discretization timestep.
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*/
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template <int Outputs>
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LinearPlantInversionFeedforward(
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const LinearSystem<States, Inputs, Outputs>& plant, units::second_t dt)
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: LinearPlantInversionFeedforward(plant.A(), plant.B(), dt) {}
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/**
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* Constructs a feedforward with the given coefficients.
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*
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* @param A Continuous system matrix of the plant being controlled.
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* @param B Continuous input matrix of the plant being controlled.
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* @param dt Discretization timestep.
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*/
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LinearPlantInversionFeedforward(const Matrixd<States, States>& A,
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const Matrixd<States, Inputs>& B,
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units::second_t dt)
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: m_dt(dt) {
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DiscretizeAB<States, Inputs>(A, B, dt, &m_A, &m_B);
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Reset();
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}
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/**
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* Returns the previously calculated feedforward as an input vector.
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*
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* @return The calculated feedforward.
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*/
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const InputVector& Uff() const { return m_uff; }
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/**
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* Returns an element of the previously calculated feedforward.
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*
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* @param i Row of uff.
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*
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* @return The row of the calculated feedforward.
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*/
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double Uff(int i) const { return m_uff(i); }
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/**
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* Returns the current reference vector r.
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*
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* @return The current reference vector.
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*/
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const StateVector& R() const { return m_r; }
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/**
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* Returns an element of the reference vector r.
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*
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* @param i Row of r.
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*
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* @return The row of the current reference vector.
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*/
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double R(int i) const { return m_r(i); }
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/**
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* Resets the feedforward with a specified initial state vector.
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*
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* @param initialState The initial state vector.
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*/
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void Reset(const StateVector& initialState) {
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m_r = initialState;
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m_uff.setZero();
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}
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/**
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* Resets the feedforward with a zero initial state vector.
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*/
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void Reset() {
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m_r.setZero();
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m_uff.setZero();
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}
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/**
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* Calculate the feedforward with only the desired
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* future reference. This uses the internally stored "current"
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* reference.
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*
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* If this method is used the initial state of the system is the one set using
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* Reset(const StateVector&). If the initial state is not
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* set it defaults to a zero vector.
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*
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* @param nextR The reference state of the future timestep (k + dt).
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*
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* @return The calculated feedforward.
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*/
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InputVector Calculate(const StateVector& nextR) {
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return Calculate(m_r, nextR);
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}
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/**
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* Calculate the feedforward with current and future reference vectors.
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*
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* @param r The reference state of the current timestep (k).
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* @param nextR The reference state of the future timestep (k + dt).
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*
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* @return The calculated feedforward.
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*/
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InputVector Calculate(const StateVector& r, const StateVector& nextR) {
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// rₖ₊₁ = Arₖ + Buₖ
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// Buₖ = rₖ₊₁ − Arₖ
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// uₖ = B⁺(rₖ₊₁ − Arₖ)
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m_uff = m_B.householderQr().solve(nextR - (m_A * r));
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m_r = nextR;
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return m_uff;
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}
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private:
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Matrixd<States, States> m_A;
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Matrixd<States, Inputs> m_B;
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units::second_t m_dt;
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// Current reference
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StateVector m_r;
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// Computed feedforward
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InputVector m_uff;
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};
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} // namespace frc
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