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Controller configurations are crucial in a car's cruise control system because they manage speed over time to maintain a consistent pace regardless of road conditions, thereby meeting design goals. In traditional control systems, fixed-configuration design involves predetermined controller placement. System performance modifications are known as compensation.
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Related Experiment Video

Updated: Dec 26, 2025

Robotized Testing of Camera Positions to Determine Ideal Configuration for Stereo 3D Visualization of Open-Heart Surgery
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Distance + Angle-Based Control of 2-D Rigid Formations.

Tairan Liu, Marcio de Queiroz

    IEEE Transactions on Cybernetics
    |March 17, 2020
    PubMed
    Summary

    This study addresses challenges in multi-agent formation control by introducing a generalized distance and angle-based scheme. The new controller ensures agents achieve the correct formation from most starting positions.

    Area of Science:

    • Robotics
    • Control Theory
    • Distributed Systems

    Background:

    • Distance-based formation control methods often suffer from multiple, undesired equilibrium points.
    • Existing schemes may not guarantee convergence to the intended formation configuration.

    Purpose of the Study:

    • To generalize a distance + angle-based control scheme for 2-D formations of single-integrator agents.
    • To mitigate the issue of extraneous equilibrium points in formation control.

    Main Methods:

    • Utilized directed graphs and triangulation techniques to model n-agent formations.
    • Developed a generalized control law incorporating distance and angle information.

    Main Results:

    • Demonstrated that the proposed controller ensures asymptotic stability of the desired formation.

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  • Showed the controller's effectiveness for almost all initial agent positions under specific conditions.

    • Conclusions:

    • The generalized distance + angle-based scheme effectively resolves multiple equilibrium point problems in formation control.
    • The controller provides robust convergence to the target formation for single-integrator agents.