Einstein Filho
/
MANGUEBAJA2019_FRONT2
Mangue Baja team's code to frontal ECU
Kalman/Kalman.h
- Committer:
- einsteingustavo
- Date:
- 2019-07-24
- Revision:
- 0:12fb9cbcabcc
File content as of revision 0:12fb9cbcabcc:
/* Copyright (C) 2012 Kristian Lauszus, TKJ Electronics. All rights reserved. This software may be distributed and modified under the terms of the GNU General Public License version 2 (GPL2) as published by the Free Software Foundation and appearing in the file GPL2.TXT included in the packaging of this file. Please note that GPL2 Section 2[b] requires that all works based on this software must also be made publicly available under the terms of the GPL2 ("Copyleft"). Contact information ------------------- Kristian Lauszus, TKJ Electronics Web : http://www.tkjelectronics.com e-mail : kristianl@tkjelectronics.com */ #ifndef KALMAN_H #define KALMAN_H class Kalman { public: Kalman(); // The angle should be in degrees and the rate should be in degrees per second and the delta time in seconds float getAngle(float newAngle, float newRate, float dt); void setAngle(float angle); // Used to set angle, this should be set as the starting angle float getRate(); // Return the unbiased rate /* These are used to tune the Kalman filter */ void setQangle(float Q_angle); /** * setQbias(float Q_bias) * Default value (0.003f) is in Kalman.cpp. * Raise this to follow input more closely, * lower this to smooth result of kalman filter. */ void setQbias(float Q_bias); void setRmeasure(float R_measure); float getQangle(); float getQbias(); float getRmeasure(); private: /* Kalman filter variables */ float Q_angle; // Process noise variance for the accelerometer float Q_bias; // Process noise variance for the gyro bias float R_measure; // Measurement noise variance - this is actually the variance of the measurement noise float angle; // The angle calculated by the Kalman filter - part of the 2x1 state vector float bias; // The gyro bias calculated by the Kalman filter - part of the 2x1 state vector float rate; // Unbiased rate calculated from the rate and the calculated bias - you have to call getAngle to update the rate float P[2][2]; // Error covariance matrix - This is a 2x2 matrix }; #endif