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[wpimath] Add ImplicitModelFollower (#4056)
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// 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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package edu.wpi.first.math.controller;
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import edu.wpi.first.math.Matrix;
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import edu.wpi.first.math.Num;
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import edu.wpi.first.math.numbers.N1;
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import edu.wpi.first.math.system.Discretization;
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import edu.wpi.first.math.system.LinearSystem;
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import org.ejml.simple.SimpleMatrix;
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/**
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* Contains the controller coefficients and logic for an implicit model follower.
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*
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* <p>Implicit model following lets us design a feedback controller that erases the dynamics of our
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* system and makes it behave like some other system. This can be used to make a drivetrain more
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* controllable during teleop driving by making it behave like a slower or more benign drivetrain.
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*
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* <p>For more on the underlying math, read appendix B.3 in
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* https://file.tavsys.net/control/controls-engineering-in-frc.pdf.
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*/
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@SuppressWarnings("ClassTypeParameterName")
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public class ImplicitModelFollower<States extends Num, Inputs extends Num, Outputs extends Num> {
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// Computed controller output
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@SuppressWarnings("MemberName")
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private Matrix<Inputs, N1> m_u;
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// State space conversion gain
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@SuppressWarnings("MemberName")
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private Matrix<Inputs, States> m_A;
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// Input space conversion gain
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@SuppressWarnings("MemberName")
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private Matrix<Inputs, Inputs> m_B;
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/**
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* Constructs a controller with the given coefficients and plant.
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*
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* @param plant The plant being controlled.
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* @param plantRef The plant whose dynamics should be followed.
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* @param dtSeconds Discretization timestep.
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*/
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public ImplicitModelFollower(
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LinearSystem<States, Inputs, Outputs> plant,
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LinearSystem<States, Inputs, Outputs> plantRef,
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double dtSeconds) {
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this(plant.getA(), plant.getB(), plantRef.getA(), plantRef.getB(), dtSeconds);
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}
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/**
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* Constructs a controller with the given coefficients and plant.
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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 Aref Continuous system matrix whose dynamics should be followed.
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* @param Bref Continuous input matrix whose dynamics should be followed.
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* @param dtSeconds Discretization timestep.
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*/
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@SuppressWarnings("ParameterName")
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public ImplicitModelFollower(
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Matrix<States, States> A,
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Matrix<States, Inputs> B,
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Matrix<States, States> Aref,
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Matrix<States, Inputs> Bref,
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double dtSeconds) {
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m_u = new Matrix<>(new SimpleMatrix(B.getNumCols(), 1));
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// Discretize real dynamics
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var discABPair = Discretization.discretizeAB(A, B, dtSeconds);
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var discA = discABPair.getFirst();
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var discB = discABPair.getSecond();
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// Discretize desired dynamics
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var discABrefPair = Discretization.discretizeAB(Aref, Bref, dtSeconds);
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var discAref = discABrefPair.getFirst();
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var discBref = discABrefPair.getSecond();
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// Find u_imf that makes real model match reference model.
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//
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// x_k+1 = Ax_k + Bu_imf
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// z_k+1 = Aref z_k + Bref u_k
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//
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// Let x_k = z_k.
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//
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// x_k+1 = z_k+1
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// Ax_k + Bu_imf = Aref x_k + Bref u_k
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// Bu_imf = Aref x_k - Ax_k + Bref u_k
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// Bu_imf = (Aref - A)x_k + Bref u_k
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// u_imf = B^+ ((Aref - A)x_k + Bref u_k)
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// u_imf = -B^+ (A - Aref)x_k + B^+ Bref u_k
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// The first term makes the open-loop poles that of the reference
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// system, and the second term makes the input behave like that of the
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// reference system.
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m_A = discB.solve(discA.minus(discAref)).times(-1.0);
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m_B = discB.solve(discBref);
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reset();
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}
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/**
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* Returns the control input vector u.
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*
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* @return The control input.
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*/
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public Matrix<Inputs, N1> getU() {
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return m_u;
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}
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/**
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* Returns an element of the control input vector u.
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*
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* @param i Row of u.
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* @return The row of the control input vector.
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*/
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public double getU(int i) {
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return m_u.get(i, 0);
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}
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/** Resets the controller. */
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public void reset() {
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m_u.fill(0.0);
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}
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/**
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* Returns the next output of the controller.
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*
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* @param x The current state x.
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* @param u The current input for the original model.
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* @return The next controller output.
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*/
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public Matrix<Inputs, N1> calculate(Matrix<States, N1> x, Matrix<Inputs, N1> u) {
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m_u = m_A.times(x).plus(m_B.times(u));
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return m_u;
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}
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}
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