MIMO State Machine for Harvester Control Optimization
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Solution Overview
Problem
Agricultural harvester operators face challenges in optimizing machine settings to minimize crop loss while maintaining grain quality and yield, as existing automated control systems often iterate between sub-optimal settings due to single input-single output control loops.
Innovation Solution
A multiple input-multiple output state machine architecture that uses a combination of sensors and finite state machine logic to identify operational states and generate control signals to adjust various machine settings, such as fan speed and ground speed, to address problem states like high crop loss, aiming for a global optimum.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If a single input-single output control loop is used to automatically adjust machine settings, then one operating parameter can be controlled, but the system iterates among sub-optimal settings and cannot simultaneously optimize multiple parameters
Solution Approach 1:
The patent combines multiple single input-single output control loops into a unified multiple input-multiple output control system. The controller simultaneously receives multiple operating parameters (crop loss, grain quality, yield) and coordinates multiple machine settings (sieve settings, chaffer settings, fan speed, rotor settings) to optimize all parameters together, eliminating the iterative sub-optimal adjustments of separate control loops
Solution Approach 2:
The controller is designed with multi-functionality to handle multiple control objectives simultaneously. It monitors multiple operating parameters and adjusts multiple machine settings through a single integrated system, making the control system universal rather than specialized for single-parameter control
2Loss of substance
If manual machine setting changes are made to address crop loss, then crop loss may be reduced, but other operating parameters such as grain quality and yield may deteriorate
Solution Approach 1:
The system implements comprehensive feedback by continuously monitoring multiple operating parameters including crop loss, grain quality, and yield. The controller uses this feedback information to make coordinated adjustments to multiple machine settings, ensuring that reducing crop loss does not compromise grain quality or yield
Solution Approach 2:
The system dynamically changes multiple machine parameters simultaneously based on real-time operating conditions. Instead of manually adjusting single parameters that may adversely affect other parameters, the controller coordinates changes across multiple parameters (sieve settings, chaffer settings, fan speed, rotor settings) to achieve overall optimization
Data Source
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AI summary
An overall machine operational state (such as a problem state, field state, machine state, other non-problem state, etc.) is identified, and exit and entry conditions are monitored to determine whether the machine transitions into another operational state. When the machine transitions into a problem state, a multiple input, multiple output control system uses a state machine to identify the problem state and a solution is identified. The solution is indicative of machine settings that will return the machine to an acceptable, operational state. Control signals are generated to modify the machine settings based on the identified solution.