Tillage Control with Feedback Optimization for Variable Field Conditions
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Solution Overview
Problem
Existing agricultural tillage methods lack the ability to optimize processing efficiency and quality in response to unpredictable situational influences such as weather and local conditions, leading to inefficiencies in fuel consumption, machine lifespan, labor costs, and overall processing quality.
Innovation Solution
A method utilizing a cascaded control loop with feedback data to iteratively optimize tillage processes, incorporating site-specific target values and weighting factors, and adjusting process control parameters based on real-time sensor data from imaging and other sensors to minimize costs and adhere to agronomic quality criteria.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If site-specific working speed and depth are set based on application maps, then tillage efficiency is improved, but adaptability to unpredictable situational influences deteriorates
Solution Approach 1:
The system continuously measures actual field conditions (soil moisture, residue distribution, weather) and feeds this information back to the control unit, which automatically adjusts working parameters in real-time, resolving the contradiction between pre-planned efficiency and real-time adaptability
Solution Approach 2:
The control system transitions from static pre-defined working parameters to dynamic real-time adjustment of speed and depth based on current field conditions, enabling the system to adapt to changing situations while maintaining optimal efficiency
2Loss of energy
If fixed working parameters are used, then process costs are reduced, but processing quality deteriorates
Solution Approach 1:
The system dynamically changes working parameters (speed, depth) based on real-time conditions to optimize both fuel efficiency and processing quality, avoiding the trade-off between fixed parameters and variable performance
3Manufacturing precision
If manual monitoring and adjustment is performed, then processing quality is improved, but labor costs increase
Solution Approach 1:
The control unit autonomously monitors field conditions and adjusts working parameters without human intervention, making the system self-regulating and eliminating the need for manual monitoring while maintaining high processing quality
4Adaptability or versatility
If real-time sensor data and optimization modules are added, then adaptability is improved, but device complexity increases
Solution Approach 1:
The control unit serves multiple functions: it stores application maps, processes sensor data from various sources, runs optimization algorithms, and controls multiple implement parameters, reducing overall system complexity through functional integration
Data Source
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AI summary
Method for automating an agricultural work task performed by a soil cultivation implement (14) on an agricultural tractor (10), wherein one or more site-specific target values and/or weighting factors with regard to process-related and/or agronomic quality criteria are specified by a control unit via an interface module (74), according to which the work task is to be carried out by means of the soil cultivation implement (14);In an optimization module (76), the target values and/or weighting factors are converted into process control variables representing working and/or operating parameters of the tillage implement (14); and in a stabilization module (78), the process control variables are adjusted by controlling positioning and/or operating devices of the tillage implement (14) and/or the agricultural tractor (10), wherein the optimization module (76) additionally receives feedback data regarding the state of a field surface (18) before and/or after tillage using the tillage implement (14) as well as regarding the operating state of the tillage implement (14) and/or the agricultural tractor (10) in order to modify the process control variables.