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最近在研究姿态解算部分，之前实验室的四轴控制不涉及直接控制姿态角部分。心血来潮，研究过阿莫里面的四轴姿态算法，有个最流行的算法，做简单融合。如下所示：
//=====================================================================================================
// AHRS.c
// S.O.H. Madgwick
// 25th August 2010
//=====================================================================================================
// Description:
//
// Quaternion implementation of the 'DCM filter' [Mayhony et al]. Incorporates the magnetic distortion
// compensation algorithms from my filter [Madgwick] which eliminates the need for a reference
// direction of flux (bx bz) to be predefined and limits the effect of magnetic distortions to yaw
// axis only.
//
// User must define 'halfT' as the (sample period / 2), and the filter gains 'Kp' and 'Ki'.
//
// Global variables 'q0', 'q1', 'q2', 'q3' are the quaternion elements representing the estimated
// orientation. See my report for an overview of the use of quaternions in this application.
//
// User must call 'AHRSupdate()' every sample period and parse calibrated gyroscope ('gx', 'gy', 'gz'),
// accelerometer ('ax', 'ay', 'ay') and magnetometer ('mx', 'my', 'mz') data. Gyroscope units are
// radians/second, accelerometer and magnetometer units are irrelevant as the vector is normalised.
//
//=====================================================================================================
//----------------------------------------------------------------------------------------------------
// Header files
#include "AHRS.h"
#include <math.h>
//----------------------------------------------------------------------------------------------------
// Definitions
#define Kp 2.0f // proportional gain governs rate of convergence to accelerometer/magnetometer
#define Ki 0.005f // integral gain governs rate of convergence of gyroscope biases
#define halfT 0.5f // half the sample period
//---------------------------------------------------------------------------------------------------
// Variable definitions
float q0 = 1, q1 = 0, q2 = 0, q3 = 0; // quaternion elements representing the estimated orientation
float exInt = 0, eyInt = 0, ezInt = 0; // scaled integral error
//====================================================================================================
// Function
//====================================================================================================
void AHRSupdate(float gx, float gy, float gz, float ax, float ay, float az, float mx, float my, float mz) {
float norm;
float hx, hy, hz, bx, bz;
float vx, vy, vz, wx, wy, wz;
float ex, ey, ez;
// auxiliary variables to reduce number of repeated operations
float q0q0 = q0*q0;
float q0q1 = q0*q1;
float q0q2 = q0*q2;
float q0q3 = q0*q3;
float q1q1 = q1*q1;
float q1q2 = q1*q2;
float q1q3 = q1*q3;
float q2q2 = q2*q2;
float q2q3 = q2*q3;
float q3q3 = q3*q3;
// normalise the measurements
norm = sqrt(ax*ax + ay*ay + az*az);
ax = ax / norm;
ay = ay / norm;
az = az / norm;
norm = sqrt(mx*mx + my*my + mz*mz);
mx = mx / norm;
my = my / norm;
mz = mz / norm;
// compute reference direction of flux
hx = 2*mx*(0.5 - q2q2 - q3q3) + 2*my*(q1q2 - q0q3) + 2*mz*(q1q3 + q0q2);
hy = 2*mx*(q1q2 + q0q3) + 2*my*(0.5 - q1q1 - q3q3) + 2*mz*(q2q3 - q0q1);
hz = 2*mx*(q1q3 - q0q2) + 2*my*(q2q3 + q0q1) + 2*mz*(0.5 - q1q1 - q2q2);
bx = sqrt((hx*hx) + (hy*hy));
bz = hz;
// estimated direction of gravity and flux (v and w)
vx = 2*(q1q3 - q0q2);
vy = 2*(q0q1 + q2q3);
vz = q0q0 - q1q1 - q2q2 + q3q3;
wx = 2*bx*(0.5 - q2q2 - q3q3) + 2*bz*(q1q3 - q0q2);
wy = 2*bx*(q1q2 - q0q3) + 2*bz*(q0q1 + q2q3);
wz = 2*bx*(q0q2 + q1q3) + 2*bz*(0.5 - q1q1 - q2q2);
// error is sum of cross product between reference direction of fields and direction measured by sensors
ex = (ay*vz - az*vy) + (my*wz - mz*wy);
ey = (az*vx - ax*vz) + (mz*wx - mx*wz);
ez = (ax*vy - ay*vx) + (mx*wy - my*wx);
// integral error scaled integral gain
exInt = exInt + ex*Ki;
eyInt = eyInt + ey*Ki;
ezInt = ezInt + ez*Ki;
// adjusted gyroscope measurements
gx = gx + Kp*ex + exInt;
gy = gy + Kp*ey + eyInt;
gz = gz + Kp*ez + ezInt;
// integrate quaternion rate and normalise
q0 = q0 + (-q1*gx - q2*gy - q3*gz)*halfT;
q1 = q1 + (q0*gx + q2*gz - q3*gy)*halfT;
q2 = q2 + (q0*gy - q1*gz + q3*gx)*halfT;
q3 = q3 + (q0*gz + q1*gy - q2*gx)*halfT;
// normalise quaternion
norm = sqrt(q0*q0 + q1*q1 + q2*q2 + q3*q3);
q0 = q0 / norm;
q1 = q1 / norm;
q2 = q2 / norm;
q3 = q3 / norm;
}
//====================================================================================================
// END OF CODE
//====================================================================================================
本人用实际的飞行数据亲测了下，在matlab下做仿真。效果表明这个算法的误差还是有点大的，最大达到了10度了，而且好像调Kp、Ki对结果影响不大。希望大牛指导下这个是什么情况？这个算法只能做到这个效果吗？
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阿莫论坛20周年了！感谢大家的支持与爱护！！
曾经有一段真挚的爱情摆在我的面前，我没有珍惜，现在想起来，还好我没有珍惜……
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发表于 2014-3-11 16:34:49
楼主
