Livestock House Temperature Prediction for Adaptive Climate Control
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Solution Overview
Problem
Existing livestock house environmental control systems face challenges in achieving real-time accurate regulation, timely response, adaptability, accuracy, and energy efficiency due to their reliance on feedback mechanisms that are limited by sensor accuracy and time lags, leading to temperature fluctuations and increased energy consumption.
Innovation Solution
A predictive control system utilizing a grey model (GM (1,1) integrated with accumulated generating operation (AGO) and residual model correction for temperature prediction, combined with a predictive fuzzy control module, to dynamically adjust ventilation and heating systems based on livestock requirements and environmental data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If feedback control based on sensor detection is used, then the system can monitor and regulate temperature, but the response is delayed due to time lags and cannot achieve real-time accurate regulation
Solution Approach 1:
The patent applies preliminary action by using a grey prediction model to forecast future temperature trends before they actually occur. The system predicts temperature changes at time t+Δt based on historical data, allowing the control system to prepare and respond in advance rather than reacting to past temperature deviations, thereby eliminating time lags and achieving real-time accurate regulation.
2Reliability
If fixed sensor feedback control is used, then the system can maintain basic temperature regulation, but the adaptability to different growth stages and environmental conditions is poor
Solution Approach 1:
The patent applies dynamics by transforming the static, fixed-threshold control system into a dynamic adaptive system. The grey prediction model continuously learns from historical temperature data and adjusts its predictions based on changing conditions, while the fuzzy logic controller dynamically adjusts control parameters according to predicted temperature trends and livestock growth stage requirements, enabling the system to adapt to different growth stages and environmental conditions while maintaining reliable temperature control.
3Manufacturing precision
If conventional feedback control is used, then the system can regulate temperature, but energy consumption increases due to frequent adjustments and overshoot
Solution Approach 1:
The patent reduces energy consumption by applying preliminary action through temperature trend prediction. The system forecasts future temperature changes and pre-adjusts control parameters before temperature deviations occur, avoiding the need for frequent emergency adjustments and reducing overshoot phenomena. This proactive control approach maintains precise temperature control while significantly reducing the frequency and intensity of control actions, thereby lowering energy consumption of the control system.
Data Source
AI summary
A predictive control system and regulatory method for a temperature of a livestock house are provided. The predictive control system includes a temperature and humidity sensor, a breeding environment temperature dynamic requirement module, an environmental controller and an environmental regulation implementation mechanism, where the environmental controller is connected to the breeding environment temperature dynamic requirement module and the temperature and humidity sensor; the environmental regulation implementation mechanism is connected to the environmental controller and is configured to perform corresponding environmental regulation according to a command from the environmental controller. The regulatory method controls a temperature of a breeding environment based on a livestock breeding environment temperature dynamic setting model, a livestock breeding environment temperature prediction system based on a GM (1,1) model, and a grey predictive fuzzy system based on the GM (1,1) model.