External Force Estimator Parameter Updating Without Special Drive Commands
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Solution Overview
Problem
Existing methods for estimating external force parameters in controlled objects require special drive commands, which can cause defects and malfunctions, and lack efficient ways to update parameters without external force detection.
Innovation Solution
A method and system that determine if a controlled object is in a known state without external force, calculate a learning value to reduce error between known and estimated external force, and update the estimator's parameters using this value, eliminating the need for special drive commands and enhancing estimation accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a sine wave command is inputted to estimate the parameter of the inverse model, then the estimation accuracy of the parameter is improved, but the controlled object may experience defects or malfunctions
Solution Approach 1:
The system performs parameter estimation during idle periods before normal operation begins, preparing the estimator in advance without requiring special drive commands during actual operation. This preliminary action allows accurate parameter identification while avoiding the risks of sine wave commands during controlled object operation.
Solution Approach 2:
The system uses its own idle periods and existing operational data to perform self-learning and parameter estimation, eliminating the need for external special drive commands. The controlled object serves its own parameter identification needs during normally idle times when no control commands are being executed.
2Measurement precision
If special drive commands are used for parameter estimation, then the parameter accuracy is improved, but the operation complexity and risk increase
Solution Approach 1:
The system automatically performs parameter estimation during idle periods using its own resources and data, eliminating the need for external special drive commands and reducing operational complexity. The controlled object independently identifies its own parameters without requiring complex external testing procedures.
3Measurement precision
If traditional parameter estimation methods are used, then the external force can be estimated, but high-accuracy force sensors are required which increases cost
Solution Approach 1:
The system introduces an estimator as an intermediary that calculates external force based on control inputs and outputs rather than directly measuring it with expensive force sensors. This mathematical intermediary provides the same functional capability as physical force sensors without the high cost and complexity.
Solution Approach 2:
The system replaces the mechanical force sensor measurement approach with a computational estimation approach using mathematical models. Instead of using physical sensors to measure external force, the system uses an estimator that calculates external force from control inputs and outputs, substituting mechanical measurement with computational analysis.
Data Source
AI summary
An aspect of this specification discloses a method of, based on a control input to a controlled object and on a control output from the controlled object, updating a value of a parameter in an estimator configured to estimate external force that acts on the controlled object. The method includes: determining whether the controlled object is in a particular state in which external force that acts on the controlled object is known; during a period in which it is determined that the controlled object is in the particular state, calculating, as a learning value, the value of the parameter that reduces an error between the known external force and estimated external force, the estimated external force being estimated by the estimator based on the control input and the control output;and updating the value of the parameter in the estimator with the calculated learning value.