Fix/mpc stability empc lite

README.md

@@ -110,7 +110,6 @@ All parameters can be changed at any time via **Settings → Devices & Services
 | -------------------- | -------- | ---------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
 | **Deadband**         | `0.2°C`  | `0.0` – `5.0°C`  | Comfort zone around target — no action taken within this range. Increase to reduce fan changes.                                                                                     |
 | **Min Interval**     | `10 min` | `1` – `60 min`   | Minimum time between non-emergency fan changes. Prevents rapid oscillations.                                                                                                        |
-| **Limit Timeout**    | `15 min` | `10` – `120 min` | Fallback timeout used before learning calibrates the dead time.                                                                                                                     |
 | **Data Collection**  | `true`   | —                | Records one CSV row every 2 minutes in the HA config folder (`smart_fan_controller_data_XXXXXXXX.csv`, max 10 MB, auto-rotated). Useful for offline analysis.                       |
 | **Defrost Entity**   | *(none)* | —                | Optional entity (`binary_sensor`, `sensor`, or `input_boolean`) that reports when the heat pump is in defrost cycle. See [Defrost Detection](#defrost-detection).                   |
 | **Operating Entity** | *(none)* | —                | Optional entity (`binary_sensor`, `sensor`, or `input_boolean`) that reports whether the heat pump compressor is actively running. See [HVAC Idle Detection](#hvac-idle-detection). |
@@ -144,7 +143,7 @@ Each candidate fan mode is scored with:
 
 - **Hysteresis**: a recommendation that changes the fan must beat the current mode by a minimum cost margin. The margin is larger when near the target (0.30) and smaller when far away (0.10).
 - **Step-down hold**: blocks downward moves when still under target and the temperature slope hasn't established yet.
-- **Min interval**: non-emergency changes respect the effective timeout (learned dead time × 1.5 for the specified HVAC mode, or the configured limit timeout).
+- **Min interval**: non-emergency changes respect the configured minimum interval between fan changes.
 
 ### Phase Detection
 
@@ -199,14 +198,13 @@ The integration includes an **automatic learning system** that collects data dur
 
 **Parameters computed from data**:
 
-| Parameter       | Formula                                           |
-| --------------- | ------------------------------------------------- |
-| `deadband`      | `0.15 + (volatility_factor × 0.2)`                |
-| `limit_timeout` | rounded median of measured thermal response times |
+| Parameter  | Formula                            |
+| ---------- | ---------------------------------- |
+| `deadband` | `0.15 + (volatility_factor × 0.2)` |
 
 Where `volatility_factor = min(slope_stdev / slope_mean, 3.0)`.
 
-> **Important**: the learned `limit_timeout` is the stored base response estimate. At runtime, non-emergency decisions use `effective_timeout = max(min_interval, dead_time × 1.5)` once learning is ready.
+> **Note**: the `effective_timeout` diagnostic (`max(min_interval, dead_time × 1.5)` once learning is ready) is exposed as a sensor for insight into the learned thermal lag, but it does not gate control decisions — the minimum interval between fan changes does.
 
 Once learning is ready, parameters are **automatically applied** and the integration reloads. To apply manually, use the `apply_learned_settings` service. To start over, use `reset_learning`.
 
@@ -278,9 +276,8 @@ Entity IDs are scoped by the configured climate entity. For example, a controlle
 | `sensor.smart_fan_controller_living_room_learning_samples`         | count | Number of slope samples collected                   |
 | `sensor.smart_fan_controller_living_room_learning_response_events` | count | Number of thermal response time measurements        |
 | `sensor.smart_fan_controller_living_room_learned_dead_time`        | min   | Median learned thermal response delay (`dead_time`) |
-| `sensor.smart_fan_controller_living_room_effective_timeout`        | min   | Actual non-emergency timeout currently used         |
+| `sensor.smart_fan_controller_living_room_effective_timeout`        | min   | Advisory adaptive timeout (diagnostic only)         |
 | `sensor.smart_fan_controller_living_room_learned_deadband`         | °C    | Learned optimal deadband                            |
-| `sensor.smart_fan_controller_living_room_learned_limit_timeout`    | min   | Learned base timeout stored in config               |
 
 ### Learning Profile Sensors
 

custom_components/smart_fan_controller/__init__.py

@@ -19,14 +19,12 @@
     CONF_DATA_COLLECTION,
     CONF_DEADBAND,
     CONF_DEFROST_ENTITY,
-    CONF_LIMIT_TIMEOUT,
     CONF_MIN_INTERVAL,
     CONF_OPERATING_ENTITY,
     DEAD_TIME_SAFETY_FACTOR,
     DEFAULT_DATA_COLLECTION,
     DEFAULT_DEAD_TIME,
     DEFAULT_DEADBAND,
-    DEFAULT_LIMIT_TIMEOUT,
     DEFAULT_MIN_INTERVAL,
     DELTA_TIME_CONTROL_LOOP,
     DOMAIN,
@@ -233,16 +231,13 @@ async def _apply_optimal_parameters(
     new_data = {**entry.data}
     new_data["learning_auto_applied"] = True
     new_data[CONF_DEADBAND] = optimal["deadband"]
-    new_data[CONF_LIMIT_TIMEOUT] = optimal["limit_timeout"]
     new_options = {**entry.options}
     new_options[CONF_DEADBAND] = optimal["deadband"]
-    new_options[CONF_LIMIT_TIMEOUT] = optimal["limit_timeout"]
 
     _LOGGER.info(
-        "Applying learned settings for %s: deadband=%.2f limit_timeout=%d",
+        "Applying learned settings for %s: deadband=%.2f",
         entry.entry_id,
         optimal["deadband"],
-        optimal["limit_timeout"],
     )
 
     hass.config_entries.async_update_entry(entry, data=new_data, options=new_options)
@@ -558,7 +553,6 @@ async def async_setup_entry(hass: HomeAssistant, entry: ConfigEntry) -> bool:
         learning=learning,
         deadband=conf.get(CONF_DEADBAND, DEFAULT_DEADBAND),
         min_interval=conf.get(CONF_MIN_INTERVAL, DEFAULT_MIN_INTERVAL),
-        limit_timeout=conf.get(CONF_LIMIT_TIMEOUT, DEFAULT_LIMIT_TIMEOUT),
         fan_modes=initial_fan_modes or None,
     )
 
@@ -595,7 +589,9 @@ def _ensure_profile_sensors() -> None:
 
     # Mutable state shared between control-loop callbacks (closure variables)
     ctrl_state: dict = {
-        "last_change_time": time.time() - (conf.get(CONF_LIMIT_TIMEOUT, DEFAULT_LIMIT_TIMEOUT) * 60),
+        # Seed as if the min interval had just elapsed so the first cycle can act
+        # immediately instead of waiting out a fresh cooldown.
+        "last_change_time": time.time() - (conf.get(CONF_MIN_INTERVAL, DEFAULT_MIN_INTERVAL) * 60),
         "last_setpoint_drop_time": 0.0,
         "previous_slope": None,
         "last_hvac_mode": None,

custom_components/smart_fan_controller/config_flow.py

@@ -13,13 +13,11 @@
     CONF_CLIMATE_ENTITY,
     CONF_DEADBAND,
     CONF_MIN_INTERVAL,
-    CONF_LIMIT_TIMEOUT,
     CONF_DATA_COLLECTION,
     CONF_DEFROST_ENTITY,
     CONF_OPERATING_ENTITY,
     DEFAULT_DEADBAND,
     DEFAULT_MIN_INTERVAL,
-    DEFAULT_LIMIT_TIMEOUT,
     DEFAULT_DATA_COLLECTION,
 )
 
@@ -105,9 +103,6 @@ async def async_step_user(self, user_input: dict[str, Any] | None = None) -> Con
                 vol.Optional(CONF_MIN_INTERVAL, default=DEFAULT_MIN_INTERVAL): selector.NumberSelector(
                     selector.NumberSelectorConfig(min=1, max=60, step=1, mode=selector.NumberSelectorMode.BOX, unit_of_measurement="min")
                 ),
-                vol.Optional(CONF_LIMIT_TIMEOUT, default=DEFAULT_LIMIT_TIMEOUT): selector.NumberSelector(
-                    selector.NumberSelectorConfig(min=10, max=120, step=5, mode=selector.NumberSelectorMode.BOX, unit_of_measurement="min")
-                ),
                 vol.Optional(CONF_DATA_COLLECTION, default=DEFAULT_DATA_COLLECTION): selector.BooleanSelector(),
                 vol.Optional(CONF_DEFROST_ENTITY): selector.EntitySelector(selector.EntitySelectorConfig(domain=["binary_sensor", "sensor", "input_boolean"])),
                 vol.Optional(CONF_OPERATING_ENTITY): selector.EntitySelector(selector.EntitySelectorConfig(domain=["binary_sensor", "sensor", "input_boolean"])),
@@ -173,9 +168,6 @@ async def async_step_init(self, user_input: dict[str, Any] | None = None) -> Con
                 vol.Optional(CONF_MIN_INTERVAL, default=current_data.get(CONF_MIN_INTERVAL, DEFAULT_MIN_INTERVAL)): selector.NumberSelector(
                     selector.NumberSelectorConfig(min=1, max=60, step=1, mode=selector.NumberSelectorMode.BOX, unit_of_measurement="min")
                 ),
-                vol.Optional(CONF_LIMIT_TIMEOUT, default=current_data.get(CONF_LIMIT_TIMEOUT, DEFAULT_LIMIT_TIMEOUT)): selector.NumberSelector(
-                    selector.NumberSelectorConfig(min=10, max=120, step=5, mode=selector.NumberSelectorMode.BOX, unit_of_measurement="min")
-                ),
                 vol.Optional(CONF_DATA_COLLECTION, default=current_data.get(CONF_DATA_COLLECTION, DEFAULT_DATA_COLLECTION)): selector.BooleanSelector(),
                 vol.Optional(CONF_DEFROST_ENTITY, default=current_data.get(CONF_DEFROST_ENTITY, vol.UNDEFINED)): selector.EntitySelector(
                     selector.EntitySelectorConfig(domain=["binary_sensor", "sensor", "input_boolean"])

custom_components/smart_fan_controller/const.py

@@ -12,15 +12,13 @@
 CONF_CLIMATE_ENTITY = "climate_entity"
 CONF_DEADBAND = "deadband"
 CONF_MIN_INTERVAL = "min_interval"
-CONF_LIMIT_TIMEOUT = "limit_timeout"
 CONF_DATA_COLLECTION = "data_collection"
 CONF_DEFROST_ENTITY = "defrost_entity"
 CONF_OPERATING_ENTITY = "operating_entity"
 
 # Default values
 DEFAULT_DEADBAND = 0.2
 DEFAULT_MIN_INTERVAL = 10
-DEFAULT_LIMIT_TIMEOUT = 15
 DEFAULT_DATA_COLLECTION = True
 
 DELTA_TIME_CONTROL_LOOP = 2  # minutes between each control loop execution
@@ -43,7 +41,6 @@
 
 # Learning
 MIN_SAMPLES_LEARNING = 240  # Minimum slope samples required for initial readiness
-MIN_LIMIT_TIMEOUT = 5  # Minimum limit_timeout (minutes) derived from learning
 MIN_MODE_PROFILE_SAMPLES = 10  # Minimum samples per fan mode to consider profile reliable
 REFERENCE_SLOPE_ERROR = 1.0  # °C – reference comfort error at which the representative
 # "working" effective slope is reported. The learned slope model is slope(error) = a + b·error;