Wheeled Robot Balance Control Using Observer-Based State Matrix
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Solution Overview
Problem
Existing balance control methods for wheeled robots are inaccurate due to differences between actual and desired models, leading to instability and poor stability, as they do not account for mounting errors and physical differences.
Innovation Solution
A motion state control method that includes determining a state matrix embodying balance errors, using an observer to iteratively update this matrix, and applying torque to control the robot to a standstill state, thereby improving accuracy and stability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a conventional linear model is used for balance control, then the control system is simple to implement, but the control accuracy deteriorates due to physical differences between actual and desired models
Solution Approach 1:
The patent transforms the balance control problem from position-based control to state matrix-based control. By changing the control parameters to include balance errors, pitch angles, and angular velocities in a state matrix, the system achieves higher accuracy while maintaining manageable complexity through systematic parameter organization
Solution Approach 2:
The patent replaces the conventional linear mechanical control model with an observer-based iterative estimation system. This substitution allows the system to adapt to actual physical differences through continuous state matrix updates, improving accuracy without requiring precise mechanical modeling
2Device complexity
If mounting errors and physical differences are not accounted for, then the control model remains simple, but the stability deteriorates due to balance point deviations
Solution Approach 1:
The patent implements feedback through the observer that continuously estimates the state matrix using actual sensor data. This feedback mechanism compensates for mounting errors and physical differences by iteratively updating the balance error parameters, thereby improving stability without significantly increasing system complexity
Solution Approach 2:
The patent transitions from a static control model to a dynamic adaptive model. The state matrix and observer continuously adapt to changing conditions and actual physical characteristics, allowing the system to maintain stability despite mounting errors and physical variations
3Ease of operation
If the balance error is not considered in control calculations, then the control process is simpler, but the reliability deteriorates due to inaccurate torque determination
Solution Approach 1:
The patent performs preliminary action by pre-defining the state matrix structure and observer parameters before control execution. This preparation work organizes the complexity in advance, making the actual control process reliable without being overly complex during operation
Data Source
AI summary
This application relates to the field of robot control, and provides a motion state control method and apparatus, a device, and a readable storage medium. The method includes the following steps: Step 301: Acquire basic data and motion state data, the basic data being used for representing a structural feature of a wheeled robot, and the motion state data being used for representing a motion feature of the wheeled robot. Step 302: Determine a state matrix of the wheeled robot based on the basic data and the motion state data, the state matrix being related to an interference parameter of the wheeled robot, the interference parameter corresponding to a balance error of the wheeled robot. Step 303: Determine, based on the state matrix, a torque for controlling the wheeled robot. Step 304: Control, by using the torque, the wheeled robot to be in a standstill state.