SELF-TUNING CONTROLLER AND TRACKING METHOD FOR AUTONOMOUS AERIAL DRONE Abstract: The technology that uses the inputs from various disciplines like mechanical, software, electronic, aeronautical, and electro-mechanical is the unmanned aerial vehicles (UAV) technology. Thus, this makes the system more complicated and highly technical. This has become a dominant research topic. It has its applications mainly in the field of the civil and military fields like the collection of data, aerial surveillance, reconnaissance, remote sensing, detection of fire, search and rescue operations, assessment of the damage, transfer of the communication, dragging of mine, logistics, and hazardous substances detection. There are other few advantages in the usage of the UAVs that include low cost due to loss, it provides less loss in terms of life and it overcomes the limitations of the manned vehicles like fatigue related to humans, operating time. The control and tracking of an aerial drone autonomously are the most challenging task in mobile robotics. Proportional Integral-Derivative (PID) controller is widely used in industries to control the action of aerial drones due to their simplicity and trade-off efficiency. The autonomous aerial drone is provided with the quadcopter type of multi-rotor. In the proposed system, Multilayer Perceptron (MLP) is trained with the Extended Kalman Filter (EKF) and Artificial Neural Network (ANN) architectural framework is attracted due to the concept similar to the biological neurons. The unmanned aerial vehicles (UAVs) are designed to control their trajectory automatically using the Proportional Integral-Derivative (PID) controllers trained with Extended Kalman Filter (EKF). The automatic tracking of the trajectory of the UAVs is performed by using the deep convolutional neural network (CNN). SELF-TUNING CONTROLLER AND TRACKING METHOD FOR AUTONOMOUS AERIAL DRONE Diagram PROPORTIONAL r~t)e~t)UWt y(t} e41) INTEGRAL GAIN - QUADROTOR DIFFERENTIAL Figure 1: Block Diagram of the Quadrotor using the PID (Proportional-Integral Derivative)Controller. QUADROTOR MODEL SU1 TRANSLATIIONAL DESIRED CONTROLLER OUTPUT INPUT ROTORINPUTS U 2 ROTATIONAL Figure 2: Block diagram of the Quadrotor UAVs (Unmanned Aerial Vehicles).


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    Titel :

    SELF-TUNING CONTROLLER AND TRACKING METHOD FOR AUTONOMOUS AERIAL DRONE


    Beteiligte:

    Erscheinungsdatum :

    03.06.2021


    Medientyp :

    Patent


    Format :

    Elektronische Ressource


    Sprache :

    Englisch


    Klassifikation :

    IPC:    G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen / G05D SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES , Systeme zum Steuern oder Regeln nichtelektrischer veränderlicher Größen / B64C AEROPLANES , Flugzeuge / G05B Steuer- oder Regelsysteme allgemein , CONTROL OR REGULATING SYSTEMS IN GENERAL



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