Self-Tuning Tractor Guidance for Changing Soil and Hitch Loads
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Automated guidance systems for off-road vehicles face challenges in adapting to changing dynamics due to soil irregularities and varying hitch loads, requiring extensive resources and expertise for controller parameter tuning, limiting adaptability and accessibility for ordinary machine operators.
Innovation Solution
A self-tuning regulator using real-time identification of vehicle dynamics and online computation of control parameters, based on a linear second-order reference model, enables adaptive control of yaw rate and lateral position, reducing the need for look-up tables and PID parameters, and simplifying implementation in embedded systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If pre-defined look-up tables and predetermined controller strategies are used, then implementation is simpler, but adaptability to changing working conditions is limited
Solution Approach 1:
The controller transitions from static pre-defined look-up tables to dynamic self-tuning parameters that adapt in real-time to changing vehicle dynamics, soil conditions, and hitch loads. The controller continuously identifies system parameters and adjusts control gains accordingly, enabling the system to respond dynamically to varying operating conditions while maintaining automated guidance functionality.
2Measurement precision
If extensive parameter tuning is performed to achieve accurate control, then control precision improves, but implementation time and complexity increase
Solution Approach 1:
The controller performs self-tuning by automatically identifying system parameters and adjusting control gains without requiring external engineering intervention. The self-tuning process occurs autonomously during operation, eliminating the need for manual parameter tuning while achieving accurate control adaptation to changing conditions.
Solution Approach 2:
The controller pre-computes control parameters based on identified system parameters before actual guidance operations begin. This preliminary parameter computation ensures that the controller is ready to provide accurate control from the start of automated guidance operations.
3Adaptability or versatility
If advanced adaptive control techniques are implemented, then adaptability improves, but system complexity increases
Solution Approach 1:
The controller implements continuous feedback loops that monitor vehicle position, orientation, and operating conditions, using this information to dynamically adjust control parameters. The feedback mechanism enables the controller to adapt to changing conditions while maintaining a relatively simple control architecture based on proportional-integral-derivative control with self-tuning gains.
Data Source
Figure 1
Figure 2
Figure 3
AI summary
A control system for an off-road vehicle is configured to provide automatic guidance for the vehicle. The control system is configured to apply an estimator to determine a plurality of system process parameters, determine a reference model based at least in part on user input, determine a plurality of control parameters using the process parameters and the reference model, determine a guidance input according to the control parameters, a setpoint of a desired output, and a previously measured output, and use the guidance input to automatically guide the vehicle. The estimator is configured to determine the plurality of system process parameters such that the control system automatically guides the vehicle so that the vehicle responds substantially in the same manner across different ground surface conditions, hitch forces and vehicle velocities.