Robotic Manipulator Friction Torque Control via Temperature
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Solution Overview
Problem
Existing robot control systems inaccurately account for gear mechanism friction torques, leading to inefficient motor usage and jerky motion due to imprecise temperature-dependent friction modeling, resulting in wasted cycle time and disrupted adjustment processes.
Innovation Solution
A method to determine gear mechanism friction torque as a function of gear mechanism temperature, using direct measurement, approximate determination from available parameters, or thermal models, allowing for precise control and adjustment without additional sensors, thereby optimizing motor torque utilization and movement behavior.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If worst-case estimates for maximum friction torque are used to ensure reliable operation across all temperature conditions, then the robot can operate reliably under any temperature, but motor torque remains unused and valuable cycle time is unnecessarily lost
Solution Approach 1:
The friction torque model transitions from static worst-case estimates to dynamic temperature-dependent calculations. The control system continuously adapts the friction torque values based on real-time or estimated gear mechanism temperatures, allowing optimal torque utilization across varying operating conditions without sacrificing reliability.
Solution Approach 2:
The friction torque parameters are changed from fixed worst-case values to variable values that depend on gear mechanism temperature. By incorporating temperature as a variable parameter in the friction model, the system achieves both reliability across temperature ranges and optimal productivity at each specific temperature condition.
2Reliability
If conservative maximum friction assumptions are made to account for unknown gear mechanism temperatures, then the system operates safely under all conditions, but the friction torque model becomes imprecise and motor torque is not optimally utilized
Solution Approach 1:
The system implements feedback mechanisms to continuously update friction torque calculations based on actual or estimated gear mechanism temperatures. This feedback loop allows the control system to maintain safe operation while significantly improving the precision of friction torque modeling compared to static worst-case assumptions.
Solution Approach 2:
The patent replaces direct mechanical temperature measurement (which would require additional sensors) with thermal models that calculate gear mechanism temperature based on available operational parameters. This substitution maintains measurement precision while avoiding the complexity and cost of additional sensing hardware.
3Measurement precision
If additional temperature sensors are installed in gear mechanisms to directly measure temperature for precise friction modeling, then friction torque can be determined accurately, but device complexity and cost increase
Solution Approach 1:
The patent introduces thermal models as intermediaries that translate readily available operational parameters (motor currents, positions, speeds) into gear mechanism temperature estimates. This intermediary approach achieves accurate temperature-dependent friction modeling without requiring direct temperature sensing in the gear mechanisms.
Solution Approach 2:
Instead of directly measuring gear mechanism temperature with physical sensors, the system creates a virtual copy or model of the thermal behavior based on operational data. This thermal model copying approach provides accurate temperature information while avoiding the complexity of physical sensor installation in difficult-to-reach gear mechanism locations.
4Productivity
If temperature-dependent friction modeling is implemented to optimize motor torque usage, then cycle time can be reduced and performance improved, but the control system complexity increases
Solution Approach 1:
The control system leverages existing multi-functional capabilities to implement temperature-dependent friction modeling. By using the same computational infrastructure and sensor data already present for other control functions, the system achieves improved productivity without proportionally increasing control system complexity.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach reduces the difference between target and actual motor torques by up to 40%, enabling flexible cycle time management and improved robot performance in time-optimal planning, collision recognition, and load data detection.
Implementation Method 1
friction torques that appear in gear mechanisms provided for moving axes of the manipulator
Implementation Method 2
the temperature conditions prevailing in or on motors and gear mechanisms have a great influence on the frictional effects (friction torques) contained in the dynamic models
Data Source
AI summary
Methods and apparatus for adjusting and controlling a robotic manipulator based on a dynamic manipulator model. A model for gear mechanism friction torque is determined for at least one axis, based on driven axis speeds and accelerations, and on a motor temperature on the drive side of one of the motors that is associated with the axis. The model is used to determine target values, such as motor position or current. The gear mechanism friction torque that complies with the model is determined in accordance with a gear mechanism temperature.