Computed-Torque Robot Control for Nonlinear Disturbance Rejection
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Solution Overview
Problem
Robot manipulator control systems face challenges in maintaining stability and accurately tracking trajectories due to nonlinearity and exogenous disturbances, such as friction and noise, which are difficult to model precisely, necessitating improved control algorithms and parameter determination methods.
Innovation Solution
A computed torque based controller is developed, combining proportional-derivative (PD) control with feedback linearization techniques to address nonlinearity and exogenous disturbances, and a parameter determination method that adjusts control parameters to minimize trajectory tracking errors using the L∞/L2 induced norm as a performance analysis criterion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If feedback linearization technique is used to remove nonlinearity, then control accuracy is improved, but device complexity increases
Solution Approach 1:
The controller is divided into two distinct loops: an inner loop that performs feedback linearization to remove nonlinearity, and an outer loop that applies PD control for trajectory tracking. This segmentation allows each loop to handle specific control tasks, improving overall control accuracy while making the complexity manageable through modular design.
2Stability of the object's composition
If exogenous disturbance removal is implemented, then stability is improved, but loss of information increases due to unmodeled dynamics
Solution Approach 1:
The controller incorporates feedback mechanisms in both the inner and outer loops to continuously monitor and correct for exogenous disturbances. The inner loop feedback linearization compensates for unmodeled dynamics and friction, while the outer loop PD control adjusts trajectories based on tracking errors, thereby maintaining stability without requiring complete knowledge of all disturbance sources.
3Manufacturing precision
If proportional-derivative control is combined with feedback linearization, then trajectory tracking precision is improved, but device complexity increases
Solution Approach 1:
The control algorithm is segmented into two functional layers: feedback linearization in the inner loop that handles nonlinear dynamics, and PD control in the outer loop that manages trajectory tracking. This segmentation enables the system to achieve high trajectory tracking precision by combining the strengths of both control methods while keeping the implementation structured and manageable.
4Manufacturing precision
If control parameters are adjusted to minimize trajectory tracking errors, then manufacturing precision is improved, but loss of time increases due to parameter optimization
Solution Approach 1:
The controller parameters are designed and configured in advance based on the system dynamics and performance requirements. The feedback linearization and PD control parameters are predetermined to achieve optimal trajectory tracking, eliminating the need for real-time parameter optimization during operation and thus avoiding time loss while maintaining high precision.
Data Source
AI summary
Provided is a controller of a robot manipulator, a performance analysis method thereof and a parameter determination method thereof. The controller computes an error value of an output value of a control target for a target value through a computational equation and provides a control input value of the control target, and includes an outer loop controller which constitutes closed loop control of the control target, and an inner loop controller which performs feedback linearization to remove nonlinearity of the control target, wherein the computational equation is a linear differential equation designed considering exogenous disturbance acting in the controller and a computational error.