Using neural networks and fuzzy logic for control

    Project Details

    Description

    This PCFC Project investigated the control using neural networks as feed forward estimators and as feedback controllers and using in series neural networks.

    That was compared to the control of robots using bounded, smoothed, incremental and stepping variable structure control.

    Then neural networks were added to the inner feedback path to improve on the use of pre-trained feed forward estimators.

    Finally, fuzzy logic was used to approximate the performance test data of a DC-motor connected to a dynamometer to see if the se of fuzzy logic could improve on low level actuator control.

    Layman's description

    Control of a robot using neural networks and fuzzy logic.

    Key findings

    Investigated control of a robot using:

    - Neural networks as feed forward estimators.
    - Neural networks as feedback controllers.
    - An in series neural network.
    - Bounded, smoothed, incremental and stepping variable structure control.
    - Neural networks added to the inner feedback path.
    - Fuzzy logic.
    Short titlePCFC Project concerning Robot control using AI and fuzzy logic
    StatusFinished
    Effective start/end date24/03/9016/03/93

    Keywords

    • Robotics
    • Control Engineering
    • Neural networks
    • Fuzzy logic

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