[wpimath] Add ImplicitModelFollower (#4056)

This commit is contained in:
Tyler Veness
2022-03-20 00:36:12 -07:00
committed by GitHub
parent 78108c2aba
commit 8d79dc8738
4 changed files with 493 additions and 0 deletions

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