[go: up one dir, main page]
More Web Proxy on the site http://driver.im/

Bingöl et al., 2021 - Google Patents

Neuro sliding mode control of quadrotor UAVs carrying suspended payload

Bingöl et al., 2021

View PDF
Document ID
11469498803553894864
Author
Bingöl
Güzey H
Publication year
Publication venue
Advanced Robotics

External Links

Snippet

In this paper, a neuro-sliding mode controller (SMC) has been designed for a quadrotor transporting a suspended payload. SMCs are very efficient under uncertain conditions. However, if the uncertain dynamics change over time, SMC gains need to be updated to …
Continue reading at www.researchgate.net (PDF) (other versions)

Classifications

    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05DSYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
    • G05D1/0011Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot associated with a remote control arrangement
    • G05D1/0044Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot associated with a remote control arrangement by providing the operator with a computer generated representation of the environment of the vehicle, e.g. virtual reality, maps
    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05DSYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
    • G05D1/08Control of attitude, i.e. control of roll, pitch, or yaw
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00Subject matter not provided for in other groups of this subclass
    • G06N99/005Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05BCONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B13/00Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
    • G05B13/02Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00Administration; Management

Similar Documents

Publication Publication Date Title
Zuo et al. Unmanned aerial vehicles: Control methods and future challenges
Bingöl et al. Neuro sliding mode control of quadrotor UAVs carrying suspended payload
Özbek et al. Feedback control strategies for quadrotor-type aerial robots: a survey
Demir et al. Real-time trajectory tracking of an unmanned aerial vehicle using a self-tuning fuzzy proportional integral derivative controller
Zhang et al. A survey of modelling and identification of quadrotor robot
He et al. Distributed output-feedback formation tracking control for unmanned aerial vehicles
Sierra et al. Wind and payload disturbance rejection control based on adaptive neural estimators: application on quadrotors
Kayacan et al. Learning control of fixed‐wing unmanned aerial vehicles using fuzzy neural networks
Li et al. Robust trajectory tracking control for a quadrotor subject to disturbances and model uncertainties
Kim et al. Optimum design of three-dimensional behavioural decentralized controller for UAV formation flight
Zhang et al. An adaptive neural network approach to the tracking control of micro aerial vehicles in constrained space
Mohiuddin et al. UAV payload transportation via RTDP based optimized velocity profiles
Wang et al. Attitude and Altitude Controller Design for Quad‐Rotor Type MAVs
Eliker et al. An optimization problem for quadcopter reference flight trajectory generation
Yanez-Badillo et al. Adaptive robust motion control of quadrotor systems using artificial neural networks and particle swarm optimization
Yu et al. Dynamic modeling and control for aerial arm-operating of a multi-propeller multifunction aerial robot
Taherinezhad et al. Robust trajectory-tracking for a bi-copter drone using indi: A gain tuning multi-objective approach
Dalwadi et al. Disturbance observer-based backstepping control of tail-sitter UAVs
Giannaris et al. Switching wireless control for longitudinal quadrotor maneuvers
Orozco Soto et al. Active disturbance rejection control for the robust flight of a passively tilted hexarotor
Xue et al. A Moving Target Tracking Control of Quadrotor UAV Based on Passive Control and Super‐Twisting Sliding Mode Control
Meradi et al. A predictive sliding mode control for quadrotor’s tracking trajectory subject to wind gusts and uncertainties
Zhang et al. Extreme learning machine assisted adaptive control of a quadrotor helicopter
Qi et al. A segmented energy‐based nonlinear tracking control method for quadrotor transport system
Wan et al. Adaptive sliding mode tracking control for unmanned autonomous helicopters based on neural networks