18695083. Motion Control Method and Apparatus simplified abstract (Siemens Aktiengesellschaft)
Contents
Motion Control Method and Apparatus
Organization Name
Inventor(s)
Motion Control Method and Apparatus - A simplified explanation of the abstract
This abstract first appeared for US patent application 18695083 titled 'Motion Control Method and Apparatus
The abstract of this patent application describes a motion control method that involves creating a model, training an online reinforcement learning model, producing feedback, calculating rewards, generating control values, and controlling the motion of an object.
- Creating a motion control model
- Training an online reinforcement learning model using the model
- Producing feedback with a controlled object, a model control value, and an initial control value
- Calculating a reward using the control value and the feedback
- Generating a residual control value using the online reinforcement learning model based on the reward, the model control value, and the feedback
- Controlling motion of the object with the residual control value and the model control value
- Sending the motion control model, the model control value, the feedback, and the reward to the cloud
- Training an offline model with the motion control model, the model control value, the feedback value, and the reward
- Updating the existing online model using the offline model or deploying the offline model in a motion control system without an online model
Potential Applications: - Industrial automation - Robotics - Autonomous vehicles
Problems Solved: - Improving motion control accuracy - Enhancing efficiency in controlling objects
Benefits: - Increased precision in motion control - Reduced human intervention required - Enhanced overall performance of controlled objects
Commercial Applications: Motion control systems in manufacturing, logistics, and transportation industries can benefit from this technology by improving efficiency and accuracy in controlling various processes.
Questions about Motion Control Method: 1. How does this technology improve the accuracy of motion control systems? 2. What are the potential cost savings associated with implementing this motion control method?
Original Abstract Submitted
Some embodiments of the teachings herein include a motion control method. An example includes: creating a motion control model; training an online reinforcement learning model using the model; producing feedback with a controlled object, a model control value, and an initial control value; calculating a reward using the control value and the feedback; generating a residual control value using the online reinforcement learning model based on the reward, the model control value, and the feedback; controlling motion of the object with the residual control value and the model control value; sending the motion control model, the model control value, the feedback, and the reward to the cloud; training an offline model with the motion control model, the model control value, the feedback value, and the reward; and updating the existing online model using the offline model or deploying the offline model in a motion control system without an online model.
