Tools: PID debug toolchain from V0.1.x bring-up

test_run.py: judged closed-loop test over COM5 (fixed sequence, J1~J4
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2026-10-15 20:55:29 +08:00
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# -*- coding: utf-8 -*-
"""V1(已烧录 0.1.0)vs V2(连续 PI 候选)离线对比仿真。
V1 问题:err<0 硬切 0% + err>=0 只有 Kp*err,稳态维持功率全靠 Ki=0.05 慢慢填
(填到 ~10% 要几分钟)→ 目标附近等效"P+上侧死区"继电器 → ±1℃/15~20s 极限环
(真机 2026-10-15 截图实测形态)。
V2:连续 PID 公式覆盖 err<0(输出钳 [0,100] 天然处理"不能制冷"),
Ki 0.05→0.5、I_MAX 2000→200(Ki*I_MAX=100% 不变)。
热模型按本次实测标定:50℃ 处冷却 ~0.1 C/s、~12% 占空净升 ~0.12 C/s
→ a≈1.9 C/s@100%,b≈0.0036/s(50℃ 维持功率 ≈5%)。
"""
KP, KI, KD = 10.0, 0.05, 30.0 # V1
KP2, KI2, KD2 = 10.0, 0.5, 30.0 # V2 候选
RAMP_CPS = 0.8
SLOWBAND_C, SLOWBAND_DUTY = 7.0, 25.0
I_MAX, I_MAX2 = 2000.0, 200.0
PWM_PERIOD_MS, PWM_STEP, PID_PERIOD_MS = 2000, 5, 500
A, B, TA, TAU_S = 1.9, 0.0036, 22.0, 4.0
def plant_step(Tc, Ts, power, dt):
Tc += (A * power - B * (Tc - TA)) * dt
Ts += (Tc - Ts) / TAU_S * dt
return Tc, Ts
class Base:
_last_power = 0.0 # 上一拍 PWM 输出(传感器加热偏置建模用)
def __init__(self, init_temp=None):
self.enable = False
self.target = 0.0
self.duty = 0
self.integral = 0.0
self.phase_ms = 0
self.divider = 0
self.Tc = TA if init_temp is None else init_temp
self.Ts = self.Tc
def tick(self):
prev_duty = self.duty
self.phase_ms = (self.phase_ms + 10) % PWM_PERIOD_MS
self.divider += 10
if self.divider >= PID_PERIOD_MS:
self.divider = 0
self.pid_compute()
if self.duty > prev_duty:
self.phase_ms = 0
on_ms = self.duty * (PWM_PERIOD_MS // (100 // PWM_STEP))
power = 0.0 if self.duty == 0 else (
1.0 if self.duty >= 100 // PWM_STEP else (1.0 if self.phase_ms < on_ms else 0.0))
self.Tc, self.Ts = plant_step(self.Tc, self.Ts, power, 0.01)
self._last_power = power
return power
def quant(self, u):
u = max(0.0, min(100.0, u))
return int((u + PWM_STEP / 2.0) / PWM_STEP)
def ramp_to(self):
diff = self.target - self.ramp_target
step = RAMP_CPS * (PID_PERIOD_MS / 1000.0)
if diff > step:
self.ramp_target += step
elif diff < -step:
self.ramp_target -= step
else:
self.ramp_target = self.target
def set_enable(self, on):
if self.enable == on:
return
self.enable = on
if on:
self.ramp_target = max(0.0, self.Ts)
self.prev_temp = self.ramp_target
else:
self.ramp_target = self.duty = 0
self.integral = 0.0
class V1(Base):
"""已烧录 0.1.0:err<0 硬切 + 慢积分。"""
def pid_compute(self):
t = self.Ts
if not self.enable:
self.duty, self.integral, self.prev_temp = 0, 0.0, t
return
self.ramp_to()
err = self.ramp_target - t
d_t = t - self.prev_temp
if err < 0:
self.integral = max(0.0, self.integral + err)
self.prev_temp = t
self.duty = 0
return
u_pd = KP * err - KD * d_t
if err < SLOWBAND_C:
u_pd = min(SLOWBAND_DUTY, u_pd)
u_pd = max(0.0, u_pd)
u = u_pd + KI * self.integral
if u < 100.0:
self.integral = min(I_MAX, self.integral + err)
self.prev_temp = t
self.duty = self.quant(u)
class V2(Base):
"""候选:连续 PID(无 err<0 硬切)+ 快积分 + 执行器受限不吸收。
吸收条件:err>0 时仅当 P/D 未被钳(0 < u_pd_raw < 当前上限,即执行器
真实响应误差)才吸收——爬升/温和带钳位段不积分,防瞬态 windup;
err<0 时只要 u>0 就回退(维持功率受 P 负项与 D 共同压制)。
"""
def pid_compute(self):
t = self.Ts
if not self.enable:
self.duty, self.integral, self.prev_temp = 0, 0.0, t
return
self.ramp_to()
err = self.ramp_target - t
d_t = t - self.prev_temp
u_pd_raw = KP2 * err - KD2 * d_t
cap = SLOWBAND_DUTY if err < SLOWBAND_C else 100.0
u_pd = max(0.0, min(cap, u_pd_raw))
u = u_pd + KI2 * self.integral
if (err > 0 and 0.0 < u_pd_raw < cap) or (err < 0 and u > 0.0):
self.integral = max(0.0, min(I_MAX2, self.integral + err))
self.prev_temp = t
self.duty = self.quant(u)
class V3(Base):
"""V3:连续 PID + 积分吸收限定在目标近旁窄带(|err|<ZONE)。
远处/爬升段不积分(slowband 钳位 + P 已经在工作),只有贴近目标才允许
积分建立稳态功率——杜绝瞬态 windup;err<0 且 u>0 时照常回退。
参数从 V3_KP/KI/KD 全局取,便于扫参。"""
def pid_compute(self):
t = self.Ts
if not self.enable:
self.duty, self.integral, self.prev_temp = 0, 0.0, t
return
self.ramp_to()
err = self.ramp_target - t
d_t = t - self.prev_temp
u_pd_raw = V3_KP * err - V3_KD * d_t
cap = SLOWBAND_DUTY if err < SLOWBAND_C else 100.0
u_pd = max(0.0, min(cap, u_pd_raw))
u = u_pd + V3_KI * self.integral
if (0.0 < err < V3_ZONE and 0.0 < u_pd_raw < cap) or (err < 0 and u > 0.0):
self.integral = max(0.0, min(V3_IMAX, self.integral + err))
self.prev_temp = t
self.duty = self.quant(u)
V3_KP, V3_KI, V3_KD, V3_ZONE, V3_IMAX = 10.0, 0.25, 30.0, 2.0, 400.0
class V4(Base):
"""V4(final) = V3 + ① err<0 时 P 负项直接抵扣积分(总量钳 [0,100])
② 积分窄带 2.0->0.6(单次爬升最多喂 ~I=12 ≈ 真机维持功率,防膨胀)
③ 故障无扰恢复(<3s 且 |ΔT|<2℃ 还原暂存积分)
真机根因(2026-10-15 DAPLink 抓证 t=397~486s):积分爬升段膨胀到 65
(维持仅需 ~12)→ 过线后 P 钳 0、Ki·I 顶 10~20% 慢泄 → +2℃ 飙升 →
泄光下潜 → 再爬再喂,自持极限环(无毛刺也发生)。"""
def __init__(self, *a, **kw):
super().__init__(*a, **kw)
self.fault_beats = 0
self.stash_I = 0.0
self.stash_T = 0.0
self.glitch_now = False
self.noise = __import__("random").Random(20261015)
def sensor(self):
t = -273.15 if self.glitch_now else self.Ts
if t > -100.0:
t += self.noise.uniform(-0.05, 0.05) # 读数噪声
t -= 0.15 if self._last_power > 0.5 else 0.0 # 加热时鳍片梯度偏低读
return t
def pid_compute(self):
t = self.sensor()
if t <= -273.0:
if self.fault_beats < 255:
self.fault_beats += 1
if self.fault_beats == 3:
self.stash_I = self.integral
self.stash_T = self.prev_temp
if self.fault_beats >= 3:
self.duty = 0
self.integral = 0.0
self.prev_temp = t
return
if self.fault_beats >= 3:
dur = self.fault_beats * (PID_PERIOD_MS / 1000.0)
if dur <= 3.0 and abs(t - self.stash_T) < 2.0:
self.integral = min(V4_IMAX, self.stash_I)
self.fault_beats = 0
if not self.enable:
self.duty, self.integral, self.prev_temp = 0, 0.0, t
return
self.ramp_to()
err = self.ramp_target - t
d_t = t - self.prev_temp
u_pd_raw = V3_KP * err - V3_KD * d_t
cap = SLOWBAND_DUTY if err < SLOWBAND_C else 100.0
if err >= 0.0:
u_pd = max(0.0, min(cap, u_pd_raw))
u = u_pd + V3_KI * self.integral
else:
u = u_pd_raw + V3_KI * self.integral # P 负项直接抵扣积分
if (0.0 < err < V4_ZONE and 0.0 < u_pd_raw < cap) or (err < 0 and u > 0.0):
self.integral = max(0.0, min(V4_IMAX, self.integral + err))
u = max(0.0, min(100.0, u))
self.prev_temp = t
self.duty = self.quant(u)
V4_ZONE, V4_IMAX = 0.6, 160.0
class V4_OLD(Base):
"""V3 原样(err<0 积分独撑 + 窄带 2.0 + 故障清零重建),毛刺/噪声注入对照。"""
def __init__(self, *a, **kw):
super().__init__(*a, **kw)
self.fault_beats = 0
self.glitch_now = False
self.noise = __import__("random").Random(20261015)
def sensor(self):
t = -273.15 if self.glitch_now else self.Ts
if t > -100.0:
t += self.noise.uniform(-0.05, 0.05)
t -= 0.15 if self._last_power > 0.5 else 0.0
return t
def pid_compute(self):
t = self.sensor()
if t <= -273.0:
if self.fault_beats < 3:
self.fault_beats += 1
if self.fault_beats >= 3:
self.duty = 0
self.integral = 0.0
self.prev_temp = t
return
self.fault_beats = 0
if not self.enable:
self.duty, self.integral, self.prev_temp = 0, 0.0, t
return
self.ramp_to()
err = self.ramp_target - t
d_t = t - self.prev_temp
u_pd_raw = V3_KP * err - V3_KD * d_t
cap = SLOWBAND_DUTY if err < SLOWBAND_C else 100.0
u_pd = max(0.0, min(cap, u_pd_raw))
u = u_pd + V3_KI * self.integral # err<0:P 钳 0,积分独撑
if (0.0 < err < V3_ZONE and 0.0 < u_pd_raw < cap) or (err < 0 and u > 0.0):
self.integral = max(0.0, min(V3_IMAX, self.integral + err))
u = max(0.0, min(100.0, u))
self.prev_temp = t
self.duty = self.quant(u)
def run(cls, label, events, init_temp=None, end=420, plant=None, glitches=()):
global A, B, TAU_S
if plant:
A, B, TAU_S = plant
p = cls(init_temp)
samples = []
idx, t_sim = 0, 0.0
events = sorted(events, key=lambda e: e[0])
while t_sim < end:
if idx < len(events) and t_sim >= events[idx][0] - 1e-9:
_, act = events[idx]
if act == "enable":
p.set_enable(True)
elif act == "disable":
p.set_enable(False)
else:
p.target = act
idx += 1
if hasattr(p, "glitch_now"):
p.glitch_now = any(gs <= t_sim < gs + gd for gs, gd in glitches)
p.tick()
samples.append(p.Ts)
t_sim += 0.01
def stats(t0, t1, tgt):
seg = samples[int(t0 / 0.01):int(t1 / 0.01)]
if not seg:
return
reach = next((i * 0.01 for i, v in enumerate(seg) if abs(v - tgt) <= 0.3), None)
if reach is None:
print(f" [{t0:4.0f}-{t1:4.0f}s tgt={tgt:g}] 未进 ±0.3 带(段内 "
f"{min(seg):.2f}~{max(seg):.2f})")
return
r = int(reach / 0.01)
post = seg[r:]
tail = seg[max(r, len(seg) - 6000):]
print(f" [{t0:4.0f}-{t1:4.0f}s tgt={tgt:g}] 进入±0.3带 {reach:5.1f}s | 到达后 "
f"[{min(post):.2f},{max(post):.2f}] | 末60s [{min(tail):.2f},{max(tail):.2f}] "
f"±{(max(tail)-min(tail))/2:.2f}")
print(f"\n== {label} ==")
for i, (t0, act) in enumerate(events):
if isinstance(act, float) or isinstance(act, int):
t1 = events[i + 1][0] if i + 1 < len(events) else end
stats(t0 + 2, min(t1, end), act)
for gs, gd in glitches:
seg = samples[int(gs / 0.01):int(min(gs + 120, end) / 0.01)]
if seg:
print(f" [glitch @{gs:g}s +{gd:g}s] 120s 窗内 [{min(seg):.2f},{max(seg):.2f}] "
f"max|Δ|={max(abs(v - p.target) for v in seg):.2f}")
return samples
if __name__ == "__main__":
# 基准工况(按实测斜率标定):a=1.9 b=0.0036 tau=4
BASE = (1.9, 0.0036, 4.0)
# 恶劣工况:维持功率 ~11%(b=0.0075)+ 传感器滞后 8s
HARSH = (1.9, 0.0075, 8.0)
import sys
if len(sys.argv) > 1 and sys.argv[1] == "sweep":
# 扫参:V3 参数网格,两工况各跑 50C 阶跃 + 从上方使能
for kp, ki, kd in [(10, 0.5, 30), (10, 0.5, 10), (10, 0.5, 0),
(15, 0.5, 30), (10, 0.25, 30), (10, 1.0, 30),
(10, 0.5, 50), (15, 0.5, 10)]:
V3_KP, V3_KI, V3_KD = float(kp), float(ki), float(kd)
print(f"\n### V3 Kp={kp} Ki={ki} Kd={kd}")
run(V3, f"HARSH 50C 阶跃", [(0, "enable"), (1, 50.0)], end=420, plant=HARSH)
run(V3, f"HARSH 从上方使能", [(0, "enable"), (1, 50.0)], init_temp=51.0, end=420, plant=HARSH)
run(V3, f"BASE 50C 阶跃", [(0, "enable"), (1, 50.0)], end=420, plant=BASE)
sys.exit(0)
# C:镜像本次实测——从 51C(高于目标)使能,目标 50
GL = [(200, 1.4), (320, 1.4)] # 毛刺注入:1.4s NTC 开路 ×2(真机 DAPLink 抓证形态)
EV = [(0, "enable"), (1, 50.0)]
run(V4_OLD, "V3(旧) 毛刺注入 tgt=50(恶劣)", EV, init_temp=51.0, end=460, plant=HARSH, glitches=GL)
run(V4, "V4 毛刺注入 tgt=50(恶劣)", EV, init_temp=51.0, end=460, plant=HARSH, glitches=GL)
run(V4, "V4 毛刺注入 tgt=50(基准)", EV, init_temp=51.0, end=460, plant=BASE, glitches=GL)
# 回归:无毛刺主场景
run(V4, "V4 50C 阶跃(恶劣)", EV, end=420, plant=HARSH)
run(V4, "V4 30C 阶跃(基准)", [(0, "enable"), (1, 30.0)], plant=BASE)
run(V4, "V4 50->40 下调(恶劣)", [(0, "enable"), (1, 50.0), (400, 40.0)], end=700, plant=HARSH)