Robot ZMP Stability Control With Lead Compensation for Phase Lag
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Solution Overview
Problem
Legged robots experience phase lag between actual and desired motion trajectories due to joint tracking lag and mechanical flexibility, affecting controller performance and robot stability.
Innovation Solution
A spring-mass-damping-acceleration model is introduced to address phase lag by incorporating acceleration, allowing for lead input of desired trajectories and improving tracking and response performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional control methods are used, then the control system is simple, but phase lag occurs between actual and desired motion trajectories
Solution Approach 1:
The patent transforms the second-order spring-mass-damping model into a first-order model by changing the mathematical parameters and structure. This parameter transformation resolves the contradiction by simplifying the control model while maintaining its ability to compensate for phase lag, thus improving tracking accuracy without increasing complexity
Solution Approach 2:
The patent replaces the traditional mechanical control approach with a mathematical transformation approach. By substituting the complex second-order dynamic model with a simplified first-order model through parameter transformation, the system achieves the same phase compensation effect with reduced computational complexity
2Measurement precision
If joint tracking lag is compensated, then motion precision improves, but control response time increases
Solution Approach 1:
The patent applies preliminary action by using the spring-mass-damping model to predict and compensate for phase lag before it affects tracking precision. The model proactively adjusts the control input based on expected deviations, improving motion precision without requiring reactive corrections that would increase response time
Solution Approach 2:
The patent introduces the spring-mass-damping model as an intermediary between the desired trajectory and the actual control output. This intermediary model processes the trajectory information and generates compensated control signals, achieving precise tracking while maintaining fast response through efficient mathematical computation
Data Source
AI summary
A robot stability control method includes: obtaining a desired zero moment point (ZMP) and a fed-back actual ZMP of a robot at a current moment; based on a ZMP tracking control model, the desired ZMP and the actual ZMP, calculating a desired value of a motion state of a center of mass of the robot at the current moment, wherein the desired value of the motion state of the center of mass comprises a correction amount of the position of the center of mass; based on a spring-mass-damping-acceleration model and the desired value of the motion state of the center of mass, calculating a lead control input amount for the correction amount of the position of the center of mass; and controlling motion of the robot according to the lead control input amount and a planned value of the position of the center of mass at the current moment.


