Analysis of a Fast Control Allocation approach for nonlinear over-actuated systems

Area of Science:

• Robotics
• Control Systems Engineering
• Embedded Systems

Background:

• Autonomous robots with multiple directional thrusters are often over-actuated, necessitating complex nonlinear control allocation.
• Existing methods require significant computational resources, posing challenges for smaller robotic platforms.

Purpose of the Study:

• Introduce a new, computationally efficient control allocation approach for autonomous robots.
• Address the limitations of current methods in embedded systems requiring fast convergence and high accuracy.

Main Methods:

• Developed a control allocation approach that decomposes nonlinear systems into coupled linear sub-problems.
• Divided Real Actions (RAs) and Virtual Control Variables (VCVs) into subsets to linearize input and output subspaces.
• Sequentially solved smaller linear systems to address complex nonlinear allocation challenges.

Main Results:

• The proposed method demonstrates fast convergence and high accuracy in solving nonlinear control allocation problems.
• Successfully applied the methodology to mathematical test cases and simulations of over-actuated unmanned aerial vehicles (UAVs).

Conclusions:

• The new approach effectively simplifies complex nonlinear control allocation for autonomous robots.
• This method is particularly suitable for embedded systems with limited computational power, enhancing performance and efficiency.