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Updated: Oct 22, 2025

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy
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Analysis of a Fast Control Allocation approach for nonlinear over-actuated systems.

M F Santos1, L M Honório2, A P G M Moreira3

  • 1Department of Electroelectronics, CEFET-MG, José Peres Street, 558, Leopoldina, Brazil.

ISA Transactions
|August 31, 2021
PubMed
Summary
This summary is machine-generated.

This study presents a novel control allocation method for autonomous robots, simplifying complex nonlinear systems into manageable linear problems. This approach offers fast convergence and high accuracy, ideal for resource-constrained embedded systems.

Keywords:
Linear-partially-dependent systemNonlinear control allocationOver-actuated systemsTilt-rotors UAV

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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.