init
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#include "DengFOC.h"
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#include "Can.h"
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#include "Timer.h"
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#include "adc.h"
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#include "ang_sensor.h"
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#include "initial.h"
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#include "pid.h"
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#include <cmath>
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#include <gd32c10x.h>
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#include <stdint.h>
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#include "motor.h"
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constexpr double PI = 3.1415926535897932384626433832795f;
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constexpr float ANGLE_FACTOR = 25.0f / 360.0f * 2.0f * 3.14159265358979323846f;
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constexpr float _1_SQRT3 = 0.57735026919f;
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constexpr float _2_SQRT3 = 1.15470053838f;
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constexpr float _3PI_2 = 4.71238898038f;
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constexpr u8 PP = 11;
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constexpr float DIR = 1.0;
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constexpr float sqrt3 = 1.73205080757f; // sqrt(3)的预计算值
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constexpr float sqrt3dv2 = 0.86602540378f; // sqrt(3)/2的预计算值
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constexpr float zero_electric_angle = 0.0f;
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constexpr u16 LUT_SCALE = (LUT_SIZE / (2.0f * PI));
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FOC_Controlroller FOC; // FOC控制初始化
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extern sampler sampler;
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extern angle_sensor KTH7823;
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extern CAN_transmiter CAN0_transmiter;
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// 初始变量及函数定义
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#define _constrain(amt, low, high) \
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((amt) < (low) ? (low) : ((amt) > (high) ? (high) : (amt)))
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#define constrain(value, min, max, target_min, target_max) \
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((value - min) / (max - min) * (target_max - target_min))
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/**
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* @brief 归一化角度
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*
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* @param angle
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* @return float
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*/
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inline float _normalizeAngle(float angle) {
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float a = fmod(angle, 2 * PI);
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// 取余运算可以用于归一化，列出特殊值例子算便知
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return a >= 0 ? a : (a + 2 * PI);
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}
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// 通过Ia,Ib,Ic计算Iq,Id(目前仅输出Iq)
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inline float FOC_Controlroller::cal_Iq_Id(float current_a, float current_b,
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float current_c) {
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// 计算电气角度
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float angle_el = _normalizeAngle(shaft_angle * PP);
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// Clarke变换 (使用三相电流)
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float I_alpha = (2.0f / 3.0f) * current_a - (1.0f / 3.0f) * current_b -
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(1.0f / 3.0f) * current_c;
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float I_beta = _1_SQRT3 * current_b - _1_SQRT3 * current_c;
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// Park变换
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float sin_el, cos_el;
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cos_el = cos_lut[(u16)(angle_el * LUT_SCALE) & LUT_MASK];
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sin_el = sin_lut[(u16)(angle_el * LUT_SCALE) & LUT_MASK];
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float I_q = I_beta * cos_el - I_alpha * sin_el;
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return I_q*1000.0f; // 返回Iq值，乘以1000以转换为mA
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}
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/**
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* @brief 电机控制类构造函数
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*
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*/
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FOC_Controlroller::FOC_Controlroller() { ; }
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/**
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* @brief 设置电机输出，使用优化的SVPWM算法
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*
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* @param Uq: q轴电压
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* @param Ud: d轴电压
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* @param angle_el: 电机轴角度
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*/
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inline void FOC_Controlroller::setPhaseVoltage(float Uq, float Ud) {
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// 计算电气角度
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float angle_el = _normalizeAngle(shaft_angle * PP);
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// 帕克逆变换 (直接计算，避免函数调用开销)
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float sin_el, cos_el;
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sin_el = sin_lut[(u16)(angle_el * LUT_SCALE) & LUT_MASK];
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cos_el = cos_lut[(u16)(angle_el * LUT_SCALE) & LUT_MASK];
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float Ualpha = Ud * cos_el - Uq * sin_el;
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float Ubeta = Ud * sin_el + Uq * cos_el;
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// 克拉克逆变换 (使用预计算常量优化)
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Ua = Ualpha + v_half;
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Ub = sqrt3dv2 * Ubeta - 0.5f * Ualpha + v_half;
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Uc = -0.5f * Ualpha - sqrt3dv2 * Ubeta + v_half;
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// 计算占空比并限制范围
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duty_a = _constrain(Ua / v_safe, 0.0f, 1.0f);
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duty_b = _constrain(Ub / v_safe, 0.0f, 1.0f);
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duty_c = _constrain(Uc / v_safe, 0.0f, 1.0f);
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// 设置PWM输出
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float voltage_exchange = limit_voltage / v_safe;
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duty_a = duty_a * voltage_exchange;
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duty_b = duty_b * voltage_exchange;
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duty_c = duty_c * voltage_exchange;
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Set_3Pwm(duty_a, duty_b, duty_c);
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// std::printf("PWM:%f,%f,%f\n", dc_a, dc_b, dc_c);
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}
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/**
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* @brief 电机关机
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*
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*/
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void FOC_Controlroller::shut_down() {
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is_shut_down = 1;
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motor_sleep();
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}
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/**
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* @brief 占空比置0
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*
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*/
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void FOC_Controlroller::drv_stop() { Set_3Pwm(0.0f, 0.0f, 0.0f); }
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/**
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* @brief 电机锁止
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*/
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void FOC_Controlroller::drv_hold(float duty) {
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if (duty > 0.95f) {
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duty = 0.95f;
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} else if (duty < 0.0f) {
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duty = 0.0f;
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}
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Set_3Pwm(duty, duty, duty);
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}
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/**
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* @brief 电机恢复
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*
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*/
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void FOC_Controlroller::resume() {
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over_current = false;
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voltage_error = false;
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is_shut_down = false;
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motor_resume();
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}
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/**
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* @brief 更新电源电压
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*
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*/
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void FOC_Controlroller::update_power(void) {
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voltage_power_supply = sampler.get_vbus_voltage();
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if (voltage_power_supply < 36.0f and voltage_power_supply > 8.0f) {
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voltage_error = false;
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v_half = voltage_power_supply * 0.5f;
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v_safe = voltage_power_supply * 0.95f;
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} else {
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voltage_error = true;
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}
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}
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/**
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* @brief 速度开环控制
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*
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* @param target_velocity: 目标速度
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* @return float: q轴电压
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*/
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float FOC_Controlroller::velocity_open_loop() {
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// 通过时间间隔和目标速度计算需要转动的机械角度，存储在shaft_angle中，在此之前，还需要对轴角度归一化
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// 预计算常量 1e-4 = 100微秒控制周期
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shaft_angle =
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_normalizeAngle(shaft_angle + target_velocity * ANGLE_FACTOR * 1e-4f);
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// 因为在开环控制中，Ud始终为0，只控制Uq
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const float Uq = voltage_power_supply / 2.0f;
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setPhaseVoltage(Uq, 0.0f);
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// CAN0_transmiter.testfloat_union.f =
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cal_Iq_Id(sampler.get_current('U'), sampler.get_current('V'), sampler.get_current('W'));
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return limit_voltage;
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}
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/**
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* @brief 电机初始化
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*
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* @param _PP: 电机极队数
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*/
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// void FOC_Controlroller::DFOC_alignSensor(int _PP) {
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// u8 PP = _PP;
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// setPhaseVoltage(3, 0, _3PI_2);
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// delay_1ms(3000);
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// zero_electric_angle = _electricalAngle();
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// setPhaseVoltage(0, 0, _3PI_2);
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// std::printf("0电角度:%f", zero_electric_angle);
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// }
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/**
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* @brief 角度闭环控制
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*
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* @param target_angle: 目标角度
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* @return float: 当前角度
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*/
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float FOC_Controlroller::angle_control(float target_angle) {
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// PID 控制计算
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float Uq = angle_loop(target_angle - rt_angle);
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// 获取电机轴角度
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shaft_angle = KTH7823.getcurrent_sensorangle() * DEG2RAD;
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// 设置相电压
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setPhaseVoltage(Uq, 0.0f);
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return shaft_angle;
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}
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/**
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* @brief 带速度限制的角度闭环控制
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*
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* @param target_angle: 目标角度
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* @param max_velocity: 最大速度限制 (单位: rad/s)
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* @return float: 当前角度
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*/
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float FOC_Controlroller::angle_control_with_velocity_limit(float target_angle) {
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// 计算角度误差
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float angle_error = target_angle - rt_angle;
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// 使用角度PID控制器计算目标速度
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float target_velocity = ang_inVelAngloop(angle_error);
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// 对目标速度进行限幅
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target_velocity = _constrain(target_velocity, -limit_velocity, limit_velocity);
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// 使用速度PID控制器计算最终输出电压
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float Uq = vel_inVelAngloop(target_velocity - rt_velocity);
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// CAN0_transmiter.testfloat_union.f = target_velocity - rt_velocity;
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// 获取电机轴角度
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shaft_angle = KTH7823.getcurrent_sensorangle() * DEG2RAD;
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// 设置相电压
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setPhaseVoltage(Uq, 0.0f);
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return shaft_angle;
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}
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/**
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* @brief 角度闭环控制
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*
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* @param target_angle: 目标角度
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* @return float: 当前角度
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*/
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float FOC_Controlroller::angle_control_NPID(float target_angle) {
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static float Kp = 20.0f;
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// 控制力矩计算
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float Uq = _constrain(Kp * (target_angle - rt_angle), -voltage_power_supply,
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voltage_power_supply);
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// 获取电机轴角度
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shaft_angle = KTH7823.getcurrent_sensorangle() * DEG2RAD;
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// 设置相电压
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setPhaseVoltage(Uq, 0.0f);
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return shaft_angle;
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}
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/**
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* @brief 速度闭环控制
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*
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* @param target_velocity: 目标速度
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* @return float: 当前速度
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*/
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float FOC_Controlroller::velocity_control(float target_velocity) {
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// PID 控制计算
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float Uq = vel_loop((target_velocity - rt_velocity)*25);
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// 获取电机轴角度
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shaft_angle = KTH7823.getcurrent_sensorangle() * DEG2RAD;
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// 设置相电压
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setPhaseVoltage(Uq, 0.0f);
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// CAN0_transmiter.testfloat_union.f =
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cal_Iq_Id(sampler.get_current('U'), sampler.get_current('V'), sampler.get_current('W'));
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return rt_velocity;
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}
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float FOC_Controlroller::current_control(float target_current) {
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// PID 控制计算
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float Iq = cal_Iq_Id(sampler.get_current('U'), sampler.get_current('V'), sampler.get_current('W'));
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float Uq = current_loop(target_current - Iq);
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CAN0_transmiter.testfloat_union.f = Iq;
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// 获取电机轴角度
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shaft_angle = KTH7823.getcurrent_sensorangle() * DEG2RAD;
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// 设置相电压
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setPhaseVoltage(Uq, 0.0f);
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return 1;
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}
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@@ -0,0 +1,411 @@
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// 函数声明
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#ifndef _DENGFOC_H
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#define _DENGFOC_H
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#include "pid.h"
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#include <stdint.h>
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class FOC_Controlroller {
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public:
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FOC_Controlroller();
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u8 control_mode = 0;
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float limit_voltage = 0.0f;
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float limit_velocity = 0.0f;
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float target_angle = 0.0f;
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float target_velocity = 0.0f;
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float rt_angle = 0.0f;
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float rt_velocity = 0.0f;
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bool over_current = false;
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bool voltage_error = false;
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bool is_shut_down = false;
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float voltage_power_supply = 24.0f; // 电源电压
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float v_safe = voltage_power_supply * 1.05f;
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float duty_a = 0, duty_b = 0, duty_c = 0;
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float Ua = 0, Ub = 0, Uc = 0;
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float velocity_open_loop();
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float angle_control(float target_angle);
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float angle_control_with_velocity_limit(float target_angle);
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float velocity_control(float target_velocity);
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float current_control(float target_current);
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float angle_control_NPID(float target_angle);
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void update_power(void);
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void DFOC_alignSensor(int _PP);
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void shut_down(void);
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void resume(void);
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void drv_stop(void);
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void drv_hold(float duty = 0.5f);
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protected:
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float shaft_angle = 0;
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float Ualpha, Ubeta = 0;
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float zero_electric_angle = 0;
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float v_half = voltage_power_supply * 0.5f; // 电源电压的一半
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PIDController vel_loop =
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PIDController{0.028f, 0.2f, 1e-4, 1000000, voltage_power_supply}; // 12V
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PIDController angle_loop = PIDController{20.0f, 100.0f, 0.2f, 10000000,
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voltage_power_supply}; // 12V
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PIDController current_loop =
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PIDController{0.006f, 0.02f, 0, 100000, voltage_power_supply}; // 12V
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PIDController vel_inVelAngloop =
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PIDController{0.35f, 5.0f,1e-3, 1000000, voltage_power_supply};
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PIDController ang_inVelAngloop =
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PIDController{30.0f, 0.0f, 1e-3, 1000000, 999};
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void setPhaseVoltage(float Uq, float Ud);
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float cal_Iq_Id(float current_a, float current_b, float current_c);
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};
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float _normalizeAngle(float angle);
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inline float _electricalAngle();
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constexpr u16 LUT_SIZE = 1024;
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constexpr u16 LUT_MASK = (LUT_SIZE - 1);
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__attribute__((aligned(4))) const float sin_lut[LUT_SIZE] = {
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0.000000f, 0.006136f, 0.012272f, 0.018407f, 0.024541f, 0.030675f,
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0.036807f, 0.042938f, 0.049068f, 0.055195f, 0.061321f, 0.067444f,
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0.073565f, 0.079682f, 0.085797f, 0.091909f, 0.098017f, 0.104122f,
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0.110222f, 0.116319f, 0.122411f, 0.128498f, 0.134581f, 0.140658f,
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0.146730f, 0.152797f, 0.158858f, 0.164913f, 0.170962f, 0.177004f,
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0.183040f, 0.189069f, 0.195090f, 0.201105f, 0.207111f, 0.213110f,
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0.219101f, 0.225084f, 0.231058f, 0.237024f, 0.242980f, 0.248928f,
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0.254866f, 0.260794f, 0.266713f, 0.272621f, 0.278520f, 0.284408f,
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0.290285f, 0.296151f, 0.302006f, 0.307850f, 0.313682f, 0.319502f,
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0.325310f, 0.331106f, 0.336890f, 0.342661f, 0.348419f, 0.354164f,
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0.359895f, 0.365613f, 0.371317f, 0.377007f, 0.382683f, 0.388345f,
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0.393992f, 0.399624f, 0.405241f, 0.410843f, 0.416430f, 0.422000f,
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0.427555f, 0.433094f, 0.438616f, 0.444122f, 0.449611f, 0.455084f,
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0.460539f, 0.465976f, 0.471397f, 0.476799f, 0.482184f, 0.487550f,
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0.492898f, 0.498228f, 0.503538f, 0.508830f, 0.514103f, 0.519356f,
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0.524590f, 0.529804f, 0.534998f, 0.540171f, 0.545325f, 0.550458f,
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0.555570f, 0.560662f, 0.565732f, 0.570781f, 0.575808f, 0.580814f,
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0.585798f, 0.590760f, 0.595699f, 0.600616f, 0.605511f, 0.610383f,
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0.615232f, 0.620057f, 0.624859f, 0.629638f, 0.634393f, 0.639124f,
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0.643832f, 0.648514f, 0.653173f, 0.657807f, 0.662416f, 0.667000f,
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0.671559f, 0.676093f, 0.680601f, 0.685084f, 0.689541f, 0.693971f,
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0.698376f, 0.702755f, 0.707107f, 0.711432f, 0.715731f, 0.720003f,
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0.724247f, 0.728464f, 0.732654f, 0.736817f, 0.740951f, 0.745058f,
|
||||
0.749136f, 0.753187f, 0.757209f, 0.761202f, 0.765167f, 0.769103f,
|
||||
0.773010f, 0.776888f, 0.780737f, 0.784557f, 0.788346f, 0.792107f,
|
||||
0.795837f, 0.799537f, 0.803208f, 0.806848f, 0.810457f, 0.814036f,
|
||||
0.817585f, 0.821103f, 0.824589f, 0.828045f, 0.831470f, 0.834863f,
|
||||
0.838225f, 0.841555f, 0.844854f, 0.848120f, 0.851355f, 0.854558f,
|
||||
0.857729f, 0.860867f, 0.863973f, 0.867046f, 0.870087f, 0.873095f,
|
||||
0.876070f, 0.879012f, 0.881921f, 0.884797f, 0.887640f, 0.890449f,
|
||||
0.893224f, 0.895966f, 0.898674f, 0.901349f, 0.903989f, 0.906596f,
|
||||
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|
||||
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|
||||
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|
||||
0.949528f, 0.951435f, 0.953306f, 0.955141f, 0.956940f, 0.958703f,
|
||||
0.960431f, 0.962121f, 0.963776f, 0.965394f, 0.966976f, 0.968522f,
|
||||
0.970031f, 0.971504f, 0.972940f, 0.974339f, 0.975702f, 0.977028f,
|
||||
0.978317f, 0.979570f, 0.980785f, 0.981964f, 0.983105f, 0.984210f,
|
||||
0.985278f, 0.986308f, 0.987301f, 0.988258f, 0.989177f, 0.990058f,
|
||||
0.990903f, 0.991710f, 0.992480f, 0.993212f, 0.993907f, 0.994565f,
|
||||
0.995185f, 0.995767f, 0.996313f, 0.996820f, 0.997290f, 0.997723f,
|
||||
0.998118f, 0.998476f, 0.998795f, 0.999078f, 0.999322f, 0.999529f,
|
||||
0.999699f, 0.999831f, 0.999925f, 0.999981f, 1.000000f, 0.999981f,
|
||||
0.999925f, 0.999831f, 0.999699f, 0.999529f, 0.999322f, 0.999078f,
|
||||
0.998795f, 0.998476f, 0.998118f, 0.997723f, 0.997290f, 0.996820f,
|
||||
0.996313f, 0.995767f, 0.995185f, 0.994565f, 0.993907f, 0.993212f,
|
||||
0.992480f, 0.991710f, 0.990903f, 0.990058f, 0.989177f, 0.988258f,
|
||||
0.987301f, 0.986308f, 0.985278f, 0.984210f, 0.983105f, 0.981964f,
|
||||
0.980785f, 0.979570f, 0.978317f, 0.977028f, 0.975702f, 0.974339f,
|
||||
0.972940f, 0.971504f, 0.970031f, 0.968522f, 0.966976f, 0.965394f,
|
||||
0.963776f, 0.962121f, 0.960431f, 0.958703f, 0.956940f, 0.955141f,
|
||||
0.953306f, 0.951435f, 0.949528f, 0.947586f, 0.945607f, 0.943593f,
|
||||
0.941544f, 0.939459f, 0.937339f, 0.935184f, 0.932993f, 0.930767f,
|
||||
0.928506f, 0.926210f, 0.923880f, 0.921514f, 0.919114f, 0.916679f,
|
||||
0.914210f, 0.911706f, 0.909168f, 0.906596f, 0.903989f, 0.901349f,
|
||||
0.898674f, 0.895966f, 0.893224f, 0.890449f, 0.887640f, 0.884797f,
|
||||
0.881921f, 0.879012f, 0.876070f, 0.873095f, 0.870087f, 0.867046f,
|
||||
0.863973f, 0.860867f, 0.857729f, 0.854558f, 0.851355f, 0.848120f,
|
||||
0.844854f, 0.841555f, 0.838225f, 0.834863f, 0.831470f, 0.828045f,
|
||||
0.824589f, 0.821103f, 0.817585f, 0.814036f, 0.810457f, 0.806848f,
|
||||
0.803208f, 0.799537f, 0.795837f, 0.792107f, 0.788346f, 0.784557f,
|
||||
0.780737f, 0.776888f, 0.773010f, 0.769103f, 0.765167f, 0.761202f,
|
||||
0.757209f, 0.753187f, 0.749136f, 0.745058f, 0.740951f, 0.736817f,
|
||||
0.732654f, 0.728464f, 0.724247f, 0.720003f, 0.715731f, 0.711432f,
|
||||
0.707107f, 0.702755f, 0.698376f, 0.693971f, 0.689541f, 0.685084f,
|
||||
0.680601f, 0.676093f, 0.671559f, 0.667000f, 0.662416f, 0.657807f,
|
||||
0.653173f, 0.648514f, 0.643832f, 0.639124f, 0.634393f, 0.629638f,
|
||||
0.624859f, 0.620057f, 0.615232f, 0.610383f, 0.605511f, 0.600616f,
|
||||
0.595699f, 0.590760f, 0.585798f, 0.580814f, 0.575808f, 0.570781f,
|
||||
0.565732f, 0.560662f, 0.555570f, 0.550458f, 0.545325f, 0.540171f,
|
||||
0.534998f, 0.529804f, 0.524590f, 0.519356f, 0.514103f, 0.508830f,
|
||||
0.503538f, 0.498228f, 0.492898f, 0.487550f, 0.482184f, 0.476799f,
|
||||
0.471397f, 0.465976f, 0.460539f, 0.455084f, 0.449611f, 0.444122f,
|
||||
0.438616f, 0.433094f, 0.427555f, 0.422000f, 0.416430f, 0.410843f,
|
||||
0.405241f, 0.399624f, 0.393992f, 0.388345f, 0.382683f, 0.377007f,
|
||||
0.371317f, 0.365613f, 0.359895f, 0.354164f, 0.348419f, 0.342661f,
|
||||
0.336890f, 0.331106f, 0.325310f, 0.319502f, 0.313682f, 0.307850f,
|
||||
0.302006f, 0.296151f, 0.290285f, 0.284408f, 0.278520f, 0.272621f,
|
||||
0.266713f, 0.260794f, 0.254866f, 0.248928f, 0.242980f, 0.237024f,
|
||||
0.231058f, 0.225084f, 0.219101f, 0.213110f, 0.207111f, 0.201105f,
|
||||
0.195090f, 0.189069f, 0.183040f, 0.177004f, 0.170962f, 0.164913f,
|
||||
0.158858f, 0.152797f, 0.146730f, 0.140658f, 0.134581f, 0.128498f,
|
||||
0.122411f, 0.116319f, 0.110222f, 0.104122f, 0.098017f, 0.091909f,
|
||||
0.085797f, 0.079682f, 0.073565f, 0.067444f, 0.061321f, 0.055195f,
|
||||
0.049068f, 0.042938f, 0.036807f, 0.030675f, 0.024541f, 0.018407f,
|
||||
0.012272f, 0.006136f, 0.000000f, -0.006136f, -0.012272f, -0.018407f,
|
||||
-0.024541f, -0.030675f, -0.036807f, -0.042938f, -0.049068f, -0.055195f,
|
||||
-0.061321f, -0.067444f, -0.073565f, -0.079682f, -0.085797f, -0.091909f,
|
||||
-0.098017f, -0.104122f, -0.110222f, -0.116319f, -0.122411f, -0.128498f,
|
||||
-0.134581f, -0.140658f, -0.146730f, -0.152797f, -0.158858f, -0.164913f,
|
||||
-0.170962f, -0.177004f, -0.183040f, -0.189069f, -0.195090f, -0.201105f,
|
||||
-0.207111f, -0.213110f, -0.219101f, -0.225084f, -0.231058f, -0.237024f,
|
||||
-0.242980f, -0.248928f, -0.254866f, -0.260794f, -0.266713f, -0.272621f,
|
||||
-0.278520f, -0.284408f, -0.290285f, -0.296151f, -0.302006f, -0.307850f,
|
||||
-0.313682f, -0.319502f, -0.325310f, -0.331106f, -0.336890f, -0.342661f,
|
||||
-0.348419f, -0.354164f, -0.359895f, -0.365613f, -0.371317f, -0.377007f,
|
||||
-0.382683f, -0.388345f, -0.393992f, -0.399624f, -0.405241f, -0.410843f,
|
||||
-0.416430f, -0.422000f, -0.427555f, -0.433094f, -0.438616f, -0.444122f,
|
||||
-0.449611f, -0.455084f, -0.460539f, -0.465976f, -0.471397f, -0.476799f,
|
||||
-0.482184f, -0.487550f, -0.492898f, -0.498228f, -0.503538f, -0.508830f,
|
||||
-0.514103f, -0.519356f, -0.524590f, -0.529804f, -0.534998f, -0.540171f,
|
||||
-0.545325f, -0.550458f, -0.555570f, -0.560662f, -0.565732f, -0.570781f,
|
||||
-0.575808f, -0.580814f, -0.585798f, -0.590760f, -0.595699f, -0.600616f,
|
||||
-0.605511f, -0.610383f, -0.615232f, -0.620057f, -0.624859f, -0.629638f,
|
||||
-0.634393f, -0.639124f, -0.643832f, -0.648514f, -0.653173f, -0.657807f,
|
||||
-0.662416f, -0.667000f, -0.671559f, -0.676093f, -0.680601f, -0.685084f,
|
||||
-0.689541f, -0.693971f, -0.698376f, -0.702755f, -0.707107f, -0.711432f,
|
||||
-0.715731f, -0.720003f, -0.724247f, -0.728464f, -0.732654f, -0.736817f,
|
||||
-0.740951f, -0.745058f, -0.749136f, -0.753187f, -0.757209f, -0.761202f,
|
||||
-0.765167f, -0.769103f, -0.773010f, -0.776888f, -0.780737f, -0.784557f,
|
||||
-0.788346f, -0.792107f, -0.795837f, -0.799537f, -0.803208f, -0.806848f,
|
||||
-0.810457f, -0.814036f, -0.817585f, -0.821103f, -0.824589f, -0.828045f,
|
||||
-0.831470f, -0.834863f, -0.838225f, -0.841555f, -0.844854f, -0.848120f,
|
||||
-0.851355f, -0.854558f, -0.857729f, -0.860867f, -0.863973f, -0.867046f,
|
||||
-0.870087f, -0.873095f, -0.876070f, -0.879012f, -0.881921f, -0.884797f,
|
||||
-0.887640f, -0.890449f, -0.893224f, -0.895966f, -0.898674f, -0.901349f,
|
||||
-0.903989f, -0.906596f, -0.909168f, -0.911706f, -0.914210f, -0.916679f,
|
||||
-0.919114f, -0.921514f, -0.923880f, -0.926210f, -0.928506f, -0.930767f,
|
||||
-0.932993f, -0.935184f, -0.937339f, -0.939459f, -0.941544f, -0.943593f,
|
||||
-0.945607f, -0.947586f, -0.949528f, -0.951435f, -0.953306f, -0.955141f,
|
||||
-0.956940f, -0.958703f, -0.960431f, -0.962121f, -0.963776f, -0.965394f,
|
||||
-0.966976f, -0.968522f, -0.970031f, -0.971504f, -0.972940f, -0.974339f,
|
||||
-0.975702f, -0.977028f, -0.978317f, -0.979570f, -0.980785f, -0.981964f,
|
||||
-0.983105f, -0.984210f, -0.985278f, -0.986308f, -0.987301f, -0.988258f,
|
||||
-0.989177f, -0.990058f, -0.990903f, -0.991710f, -0.992480f, -0.993212f,
|
||||
-0.993907f, -0.994565f, -0.995185f, -0.995767f, -0.996313f, -0.996820f,
|
||||
-0.997290f, -0.997723f, -0.998118f, -0.998476f, -0.998795f, -0.999078f,
|
||||
-0.999322f, -0.999529f, -0.999699f, -0.999831f, -0.999925f, -0.999981f,
|
||||
-1.000000f, -0.999981f, -0.999925f, -0.999831f, -0.999699f, -0.999529f,
|
||||
-0.999322f, -0.999078f, -0.998795f, -0.998476f, -0.998118f, -0.997723f,
|
||||
-0.997290f, -0.996820f, -0.996313f, -0.995767f, -0.995185f, -0.994565f,
|
||||
-0.993907f, -0.993212f, -0.992480f, -0.991710f, -0.990903f, -0.990058f,
|
||||
-0.989177f, -0.988258f, -0.987301f, -0.986308f, -0.985278f, -0.984210f,
|
||||
-0.983105f, -0.981964f, -0.980785f, -0.979570f, -0.978317f, -0.977028f,
|
||||
-0.975702f, -0.974339f, -0.972940f, -0.971504f, -0.970031f, -0.968522f,
|
||||
-0.966976f, -0.965394f, -0.963776f, -0.962121f, -0.960431f, -0.958703f,
|
||||
-0.956940f, -0.955141f, -0.953306f, -0.951435f, -0.949528f, -0.947586f,
|
||||
-0.945607f, -0.943593f, -0.941544f, -0.939459f, -0.937339f, -0.935184f,
|
||||
-0.932993f, -0.930767f, -0.928506f, -0.926210f, -0.923880f, -0.921514f,
|
||||
-0.919114f, -0.916679f, -0.914210f, -0.911706f, -0.909168f, -0.906596f,
|
||||
-0.903989f, -0.901349f, -0.898674f, -0.895966f, -0.893224f, -0.890449f,
|
||||
-0.887640f, -0.884797f, -0.881921f, -0.879012f, -0.876070f, -0.873095f,
|
||||
-0.870087f, -0.867046f, -0.863973f, -0.860867f, -0.857729f, -0.854558f,
|
||||
-0.851355f, -0.848120f, -0.844854f, -0.841555f, -0.838225f, -0.834863f,
|
||||
-0.831470f, -0.828045f, -0.824589f, -0.821103f, -0.817585f, -0.814036f,
|
||||
-0.810457f, -0.806848f, -0.803208f, -0.799537f, -0.795837f, -0.792107f,
|
||||
-0.788346f, -0.784557f, -0.780737f, -0.776888f, -0.773010f, -0.769103f,
|
||||
-0.765167f, -0.761202f, -0.757209f, -0.753187f, -0.749136f, -0.745058f,
|
||||
-0.740951f, -0.736817f, -0.732654f, -0.728464f, -0.724247f, -0.720003f,
|
||||
-0.715731f, -0.711432f, -0.707107f, -0.702755f, -0.698376f, -0.693971f,
|
||||
-0.689541f, -0.685084f, -0.680601f, -0.676093f, -0.671559f, -0.667000f,
|
||||
-0.662416f, -0.657807f, -0.653173f, -0.648514f, -0.643832f, -0.639124f,
|
||||
-0.634393f, -0.629638f, -0.624859f, -0.620057f, -0.615232f, -0.610383f,
|
||||
-0.605511f, -0.600616f, -0.595699f, -0.590760f, -0.585798f, -0.580814f,
|
||||
-0.575808f, -0.570781f, -0.565732f, -0.560662f, -0.555570f, -0.550458f,
|
||||
-0.545325f, -0.540171f, -0.534998f, -0.529804f, -0.524590f, -0.519356f,
|
||||
-0.514103f, -0.508830f, -0.503538f, -0.498228f, -0.492898f, -0.487550f,
|
||||
-0.482184f, -0.476799f, -0.471397f, -0.465976f, -0.460539f, -0.455084f,
|
||||
-0.449611f, -0.444122f, -0.438616f, -0.433094f, -0.427555f, -0.422000f,
|
||||
-0.416430f, -0.410843f, -0.405241f, -0.399624f, -0.393992f, -0.388345f,
|
||||
-0.382683f, -0.377007f, -0.371317f, -0.365613f, -0.359895f, -0.354164f,
|
||||
-0.348419f, -0.342661f, -0.336890f, -0.331106f, -0.325310f, -0.319502f,
|
||||
-0.313682f, -0.307850f, -0.302006f, -0.296151f, -0.290285f, -0.284408f,
|
||||
-0.278520f, -0.272621f, -0.266713f, -0.260794f, -0.254866f, -0.248928f,
|
||||
-0.242980f, -0.237024f, -0.231058f, -0.225084f, -0.219101f, -0.213110f,
|
||||
-0.207111f, -0.201105f, -0.195090f, -0.189069f, -0.183040f, -0.177004f,
|
||||
-0.170962f, -0.164913f, -0.158858f, -0.152797f, -0.146730f, -0.140658f,
|
||||
-0.134581f, -0.128498f, -0.122411f, -0.116319f, -0.110222f, -0.104122f,
|
||||
-0.098017f, -0.091909f, -0.085797f, -0.079682f, -0.073565f, -0.067444f,
|
||||
-0.061321f, -0.055195f, -0.049068f, -0.042938f, -0.036807f, -0.030675f,
|
||||
-0.024541f, -0.018407f, -0.012272f, -0.006136f};
|
||||
__attribute__((aligned(4))) const float cos_lut[LUT_SIZE] = {
|
||||
1.000000f, 0.999981f, 0.999925f, 0.999831f, 0.999699f, 0.999529f,
|
||||
0.999322f, 0.999078f, 0.998795f, 0.998476f, 0.998118f, 0.997723f,
|
||||
0.997290f, 0.996820f, 0.996313f, 0.995767f, 0.995185f, 0.994565f,
|
||||
0.993907f, 0.993212f, 0.992480f, 0.991710f, 0.990903f, 0.990058f,
|
||||
0.989177f, 0.988258f, 0.987301f, 0.986308f, 0.985278f, 0.984210f,
|
||||
0.983105f, 0.981964f, 0.980785f, 0.979570f, 0.978317f, 0.977028f,
|
||||
0.975702f, 0.974339f, 0.972940f, 0.971504f, 0.970031f, 0.968522f,
|
||||
0.966976f, 0.965394f, 0.963776f, 0.962121f, 0.960431f, 0.958703f,
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|
||||
0.978317f, 0.979570f, 0.980785f, 0.981964f, 0.983105f, 0.984210f,
|
||||
0.985278f, 0.986308f, 0.987301f, 0.988258f, 0.989177f, 0.990058f,
|
||||
0.990903f, 0.991710f, 0.992480f, 0.993212f, 0.993907f, 0.994565f,
|
||||
0.995185f, 0.995767f, 0.996313f, 0.996820f, 0.997290f, 0.997723f,
|
||||
0.998118f, 0.998476f, 0.998795f, 0.999078f, 0.999322f, 0.999529f,
|
||||
0.999699f, 0.999831f, 0.999925f, 0.999981f};
|
||||
#endif
|
||||
@@ -0,0 +1,151 @@
|
||||
#include "Filter.h"
|
||||
#include "Can.h"
|
||||
#include "ang_sensor.h"
|
||||
#include <algorithm>
|
||||
#include <cstring>
|
||||
#include <stdint.h>
|
||||
|
||||
extern angle_sensor KTH7823;
|
||||
extern CAN_transmiter CAN0_transmiter;
|
||||
extern u32 system_runtime_us;
|
||||
EncoderAngleKalman Angle_kalman(0, 1.0f, 1e-4f, 0.25f);
|
||||
EncoderVelocityKalman Vel_kalman(0, 1e-5f, 1e-6f, 0.02f);
|
||||
|
||||
constexpr u8 SIZE_FLOAT = sizeof(float);
|
||||
|
||||
/*!
|
||||
\brief 中值滤波器函数
|
||||
\param[in] values 待滤波的数据数组
|
||||
\param[in] size 数组大小
|
||||
\retval 滤波后的中值
|
||||
\note 使用部分排序优化算法提高效率
|
||||
*/
|
||||
float medium_filter(float values[], u8 size) {
|
||||
// 使用局部数组避免动态内存分配
|
||||
float sorted[size];
|
||||
memcpy(sorted, values, size * SIZE_FLOAT);
|
||||
|
||||
// 这比完整排序更高效，时间复杂度从O(n log n)降低到O(n)
|
||||
std::nth_element(sorted, sorted + size / 2, sorted + size);
|
||||
|
||||
return sorted[size / 2]; // 返回中值
|
||||
}
|
||||
|
||||
// EncoderVelocityKalman类的实现
|
||||
/*!
|
||||
\brief 构造函数，初始化编码器速度卡尔曼滤波器参数
|
||||
\param[in] initial_velocity 初始速度值 (rad/s)
|
||||
\param[in] T 控制周期(s)
|
||||
\param[in] Q 过程噪声协方差(典型值: 1e-4 ~ 1e-2)
|
||||
\param[in] R 测量噪声协方差(典型值: 速度范围的1%~5%)
|
||||
\retval none
|
||||
*/
|
||||
EncoderVelocityKalman::EncoderVelocityKalman(float initial_velocity, float T,
|
||||
float Q, float R)
|
||||
: kalman(initial_velocity, T, Q, R) {}
|
||||
|
||||
/*!
|
||||
\brief 更新卡尔曼滤波器状态
|
||||
\param[in] measured_velocity 测量的速度值 (rad/s)
|
||||
\retval 估计的速度值 (rad/s)
|
||||
\note 实现卡尔曼滤波的预测和更新步骤，假设速度变化符合随机游走模型
|
||||
*/
|
||||
float EncoderVelocityKalman::update(float measured_velocity) {
|
||||
// 1. 预测步骤 - 假设速度符合随机游走模型（加速度为0）
|
||||
// 由于速度变化缓慢，我们可以简单预测速度保持不变
|
||||
kalman.predict(kalman.getState());
|
||||
|
||||
// 2. 更新步骤 - 直接使用测量值更新
|
||||
return kalman.update(measured_velocity);
|
||||
}
|
||||
|
||||
/*!
|
||||
\brief 获取当前速度估计值
|
||||
\retval 当前速度估计值 (deg/s)
|
||||
*/
|
||||
float EncoderVelocityKalman::getVelocity() const { return kalman.getState(); }
|
||||
|
||||
/*!
|
||||
\brief 设置过程噪声协方差
|
||||
\param[in] q 过程噪声协方差值
|
||||
\retval none
|
||||
*/
|
||||
void EncoderVelocityKalman::setProcessNoise(float q) {
|
||||
kalman.setProcessNoise(q);
|
||||
}
|
||||
|
||||
/*!
|
||||
\brief 设置测量噪声协方差
|
||||
\param[in] r 测量噪声协方差值
|
||||
\retval none
|
||||
*/
|
||||
void EncoderVelocityKalman::setMeasurementNoise(float r) {
|
||||
kalman.setMeasurementNoise(r);
|
||||
}
|
||||
|
||||
// EncoderAngleKalman类的实现
|
||||
/*!
|
||||
\brief 构造函数，初始化编码器角度卡尔曼滤波器参数
|
||||
\param[in] initial_angle 初始角度值 (degree)
|
||||
\param[in] initial_error_covariance 初始误差协方差
|
||||
\param[in] process_noise 过程噪声协方差
|
||||
\param[in] measurement_noise 测量噪声协方差
|
||||
\retval none
|
||||
*/
|
||||
EncoderAngleKalman::EncoderAngleKalman(float initial_angle,
|
||||
float initial_error_covariance,
|
||||
float process_noise,
|
||||
float measurement_noise)
|
||||
: kalman(initial_angle, initial_error_covariance, process_noise,
|
||||
measurement_noise),
|
||||
last_angle(initial_angle), initialized(true) {}
|
||||
|
||||
/*!
|
||||
\brief 更新卡尔曼滤波器状态
|
||||
\param[in] measured_angle 测量的角度值 (degree)
|
||||
\retval 估计的角度值 (degree)
|
||||
\note 实现卡尔曼滤波的预测和更新步骤
|
||||
*/
|
||||
float EncoderAngleKalman::update(float measured_angle) {
|
||||
// 更新last_angle以支持速度计算
|
||||
last_angle = kalman.getState();
|
||||
// 1. 预测步骤 - 速度估计
|
||||
kalman.predict(last_angle);
|
||||
|
||||
// 2. 更新步骤 - 使用处理后的角度值更新
|
||||
float filtered_angle = kalman.update(measured_angle);
|
||||
return filtered_angle;
|
||||
}
|
||||
|
||||
/*!
|
||||
\brief 获取当前角度估计值
|
||||
\retval 当前角度估计值 (degree)
|
||||
*/
|
||||
float EncoderAngleKalman::getAngle() const { return kalman.getState(); }
|
||||
/*!
|
||||
\brief 获取当前角度估计值
|
||||
\retval 当前角度估计值 (degree)
|
||||
*/
|
||||
float EncoderAngleKalman::getVelocity() const {
|
||||
static u32 last_us100_counter = system_runtime_us;
|
||||
float vel = (kalman.getState() - last_angle) * 1e4 *
|
||||
(system_runtime_us - last_us100_counter);
|
||||
last_us100_counter = system_runtime_us;
|
||||
return vel;
|
||||
}
|
||||
|
||||
/*!
|
||||
\brief 设置过程噪声协方差
|
||||
\param[in] q 过程噪声协方差值
|
||||
\retval none
|
||||
*/
|
||||
void EncoderAngleKalman::setProcessNoise(float q) { kalman.setProcessNoise(q); }
|
||||
|
||||
/*!
|
||||
\brief 设置测量噪声协方差
|
||||
\param[in] r 测量噪声协方差值
|
||||
\retval none
|
||||
*/
|
||||
void EncoderAngleKalman::setMeasurementNoise(float r) {
|
||||
kalman.setMeasurementNoise(r);
|
||||
}
|
||||
@@ -0,0 +1,164 @@
|
||||
#ifndef _FILTER_H
|
||||
#define _FILTER_H
|
||||
|
||||
#ifdef __cplusplus
|
||||
extern "C" {
|
||||
#endif
|
||||
|
||||
// C风格函数声明可以放在这里
|
||||
// 例如: void some_c_function(float* data, int size);
|
||||
|
||||
#ifdef __cplusplus
|
||||
} // extern "C"
|
||||
#endif
|
||||
|
||||
#ifdef __cplusplus
|
||||
#include <cstring>
|
||||
#include <stdint.h>
|
||||
|
||||
float medium_filter(float values[], u8 size);
|
||||
|
||||
/*!
|
||||
\brief 通用卡尔曼滤波器模板类
|
||||
\note 可用于各种基于线性系统的状态估计
|
||||
*/
|
||||
template <typename T> class KalmanFilter {
|
||||
private:
|
||||
T P; // 估计误差协方差
|
||||
T Q; // 过程噪声协方差
|
||||
T R; // 测量噪声协方差
|
||||
|
||||
public:
|
||||
T x; // 状态估计
|
||||
/*!
|
||||
\brief 构造函数
|
||||
\param[in] initial_state 初始状态值
|
||||
\param[in] initial_error_covariance 初始误差协方差
|
||||
\param[in] process_noise 过程噪声协方差
|
||||
\param[in] measurement_noise 测量噪声协方差
|
||||
*/
|
||||
KalmanFilter(T initial_state, T initial_error_covariance, T process_noise,
|
||||
T measurement_noise)
|
||||
: x(initial_state), P(initial_error_covariance), Q(process_noise),
|
||||
R(measurement_noise) {}
|
||||
|
||||
/*!
|
||||
\brief 预测步骤
|
||||
\param[in] state_prediction 状态预测值
|
||||
\retval none
|
||||
*/
|
||||
void predict(T state_prediction) {
|
||||
x = state_prediction;
|
||||
P += Q;
|
||||
}
|
||||
|
||||
/*!
|
||||
\brief 更新步骤
|
||||
\param[in] measurement 测量值
|
||||
\param[in] measurement_prediction 测量预测值
|
||||
\retval 估计的状态值
|
||||
*/
|
||||
T update(T measurement, T measurement_prediction) {
|
||||
T y = measurement - measurement_prediction; // 测量残差
|
||||
T S = P + R; // 残差协方差
|
||||
T K = P / S; // 卡尔曼增益
|
||||
|
||||
x += K * y; // 更新状态估计
|
||||
P = (1 - K) * P; // 更新误差协方差
|
||||
|
||||
return x;
|
||||
}
|
||||
|
||||
/*!
|
||||
\brief 直接更新步骤（适用于状态直接可测的情况）
|
||||
\param[in] measurement 测量值
|
||||
\retval 估计的状态值
|
||||
*/
|
||||
T update(T measurement) {
|
||||
T K = P / (P + R); // 卡尔曼增益
|
||||
|
||||
x += K * (measurement - x); // 更新状态估计
|
||||
P = (1 - K) * P; // 更新误差协方差
|
||||
return x;
|
||||
}
|
||||
|
||||
/*!
|
||||
\brief 获取当前状态估计值
|
||||
\retval 当前状态估计值
|
||||
*/
|
||||
T getState() const { return x; }
|
||||
|
||||
/*!
|
||||
\brief 设置过程噪声协方差
|
||||
\param[in] process_noise 过程噪声协方差值
|
||||
\retval none
|
||||
*/
|
||||
void setProcessNoise(T process_noise) { Q = process_noise; }
|
||||
|
||||
/*!
|
||||
\brief 设置测量噪声协方差
|
||||
\param[in] measurement_noise 测量噪声协方差值
|
||||
\retval none
|
||||
*/
|
||||
void setMeasurementNoise(T measurement_noise) { R = measurement_noise; }
|
||||
};
|
||||
|
||||
/*!
|
||||
\brief 编码器速度卡尔曼滤波器类
|
||||
\note 用于滤除编码器速度测量噪声的卡尔曼滤波器实现
|
||||
*/
|
||||
class EncoderVelocityKalman {
|
||||
private:
|
||||
KalmanFilter<float> kalman;
|
||||
|
||||
public:
|
||||
EncoderVelocityKalman(float initial_velocity,
|
||||
float initial_error_covariance, float process_noise,
|
||||
float measurement_noise);
|
||||
|
||||
float update(float measured_velocity);
|
||||
|
||||
float getVelocity() const;
|
||||
|
||||
void setProcessNoise(float q);
|
||||
|
||||
void setMeasurementNoise(float r);
|
||||
|
||||
u8 init(float init_velocity) {
|
||||
kalman.x = init_velocity;
|
||||
return 0;
|
||||
}
|
||||
};
|
||||
|
||||
/*!
|
||||
\brief 编码器角度卡尔曼滤波器类
|
||||
\note 用于滤除编码器角度测量噪声的卡尔曼滤波器实现
|
||||
*/
|
||||
class EncoderAngleKalman {
|
||||
private:
|
||||
KalmanFilter<float> kalman;
|
||||
bool initialized;
|
||||
float last_angle;
|
||||
|
||||
public:
|
||||
EncoderAngleKalman(float initial_angle, float initial_error_covariance,
|
||||
float process_noise, float measurement_noise);
|
||||
|
||||
float update(float measured_angle);
|
||||
|
||||
float getAngle() const;
|
||||
float getVelocity() const;
|
||||
|
||||
void setProcessNoise(float q);
|
||||
float getstate() const { return kalman.getState(); };
|
||||
|
||||
void setMeasurementNoise(float r);
|
||||
u8 init(float init_angle) {
|
||||
kalman.x = init_angle;
|
||||
return 0;
|
||||
}
|
||||
};
|
||||
|
||||
#endif // __cplusplus
|
||||
|
||||
#endif // _FILTER_H
|
||||
@@ -0,0 +1,60 @@
|
||||
#include "pid.h"
|
||||
#define _constrain(amt, low, high) \
|
||||
((amt) < (low) ? (low) : ((amt) > (high) ? (high) : (amt)))
|
||||
#include "Can.h"
|
||||
#include "math.h"
|
||||
|
||||
extern CAN_transmiter CAN0_transmiter;
|
||||
constexpr float TIME_SLICE = 1e-4;
|
||||
|
||||
PIDController::PIDController(float P, float I, float D, float ramp, float limit)
|
||||
: P(P), I(I), D(D), output_ramp(ramp) // PID控制器加速度限幅
|
||||
,
|
||||
limit(limit) // PID控制器输出限幅
|
||||
,
|
||||
error_prev(0.0f), output_prev(0.0f), integral_prev(0.0f) {}
|
||||
|
||||
// PID 控制器函数
|
||||
float PIDController::operator()(float error) {
|
||||
// P环
|
||||
float proportional = P * error;
|
||||
|
||||
// Tustin 散点积分（I环）
|
||||
// 添加积分限幅，防止积分饱和
|
||||
float integral = integral_prev + I * TIME_SLICE * 0.5f * (error + error_prev);
|
||||
integral = _constrain(integral, -limit, limit);
|
||||
|
||||
// D环（微分环节）
|
||||
float derivative = D * (error - error_prev) / TIME_SLICE;
|
||||
|
||||
// 将P,I,D三环的计算值加起来
|
||||
float output = proportional + integral + derivative;
|
||||
output = _constrain(output, -limit, limit);
|
||||
|
||||
// 输出斜坡限制
|
||||
// 简化的斜坡限制（单行逻辑）
|
||||
if (output_ramp > 0) {
|
||||
float max_delta = output_ramp * TIME_SLICE;
|
||||
output = output_prev + fmaxf(-max_delta, fminf(max_delta, output - output_prev));
|
||||
}
|
||||
// 保存值（为了下一次循环）
|
||||
integral_prev = integral;
|
||||
output_prev = output;
|
||||
error_prev = error;
|
||||
|
||||
return output;
|
||||
}
|
||||
|
||||
/**
|
||||
* @brief 设置PID参数
|
||||
*
|
||||
* @param P: P参数
|
||||
* @param I: I参数
|
||||
* @param D: D参数
|
||||
* @return void
|
||||
*/
|
||||
void PIDController::set_PID(float P, float I, float D) {
|
||||
this->P = P;
|
||||
this->I = I;
|
||||
this->D = D;
|
||||
}
|
||||
@@ -0,0 +1,25 @@
|
||||
#ifndef PID_H
|
||||
#define PID_H
|
||||
|
||||
class PIDController
|
||||
{
|
||||
public:
|
||||
PIDController(float P, float I, float D, float ramp, float limit);
|
||||
~PIDController() = default;
|
||||
|
||||
float operator() (float error);
|
||||
void set_PID(float P, float I, float D);
|
||||
|
||||
float P; //!< 比例增益(P环增益)
|
||||
float I; //!< 积分增益（I环增益）
|
||||
float D; //!< 微分增益（D环增益）
|
||||
float output_ramp;
|
||||
float limit;
|
||||
protected:
|
||||
float error_prev; //!< 最后的跟踪误差值
|
||||
float output_prev; //!< 最后一个 pid 输出值
|
||||
float integral_prev; //!< 最后一个积分分量值
|
||||
unsigned long timestamp_prev; //!< 上次执行时间戳
|
||||
};
|
||||
|
||||
#endif
|
||||
@@ -0,0 +1,7 @@
|
||||
#ifndef THERMAL_H
|
||||
#define THERMAL_H
|
||||
|
||||
|
||||
|
||||
|
||||
#endif
|
||||
Reference in New Issue
Block a user