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

Cong et al., 2020 - Google Patents

Formation control for multiquadrotor aircraft: Connectivity preserving and collision avoidance

Cong et al., 2020

Document ID
2167769973821713723
Author
Cong Y
Du H
Jin Q
Zhu W
Lin X
Publication year
Publication venue
International Journal of Robust and Nonlinear Control

External Links

Snippet

In this article, we investigate the formation control problem of multiquadrotor aircraft system subject to connectivity preservation and collision avoidance. First, based on the backstepping design method, a novel formation control algorithm is developed to enable …
Continue reading at onlinelibrary.wiley.com (other versions)

Classifications

    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
    • G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
    • G05B13/0265—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric the criterion being a learning criterion
    • G05B13/027—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric the criterion being a learning criterion using neural networks only
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B2219/00—Program-control systems
    • G05B2219/30—Nc systems
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
    • G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
    • G05B13/04—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computer systems based on biological models
    • G06N3/02—Computer systems based on biological models using neural network models
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00—Subject matter not provided for in other groups of this subclass
    • G06N99/005—Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00—Computer systems utilising knowledge based models
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B19/00—Programme-control systems
    • G05B19/02—Programme-control systems electric
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot

Similar Documents

Publication Publication Date Title
Lin et al. Event-based finite-time neural control for human-in-the-loop UAV attitude systems
Yu et al. Distributed adaptive fractional‐order fault‐tolerant cooperative control of networked unmanned aerial vehicles via fuzzy neural networks
Cong et al. Formation control for multiquadrotor aircraft: Connectivity preserving and collision avoidance
Du et al. Finite-time formation control for a group of quadrotor aircraft
Li et al. Robust tracking control strategy for a quadrotor using RPD-SMC and RISE
Wang et al. Distributed sliding mode control for leader‐follower formation flight of fixed‐wing unmanned aerial vehicles subject to velocity constraints
Ren et al. Distributed fault‐tolerant time‐varying formation control of heterogeneous multi‐agent systems
Shi et al. Fault‐tolerant formation control of non‐linear multi‐vehicle systems with application to quadrotors
Zou et al. Adaptive neural network sliding mode control of a nonlinear two‐degrees‐of‐freedom helicopter system
Liu et al. Adaptive fault‐tolerant formation control for quadrotors with actuator faults
Dou et al. Distributed finite‐time formation control for multiple quadrotors via local communications
Norton et al. Adaptive fuzzy multi‐surface sliding control of multiple‐input and multiple‐output autonomous flight systems
Rojo-Rodriguez et al. Robust consensus-based formation flight for multiple quadrotors
Litimein et al. Circular formation control with collision avoidance based on probabilistic position
Wang et al. Adaptive fractional‐order nonsingular fast terminal sliding mode formation control of multiple quadrotor UAVs‐based distributed estimator
El Houm et al. Optimal new sliding mode controller combined with modified supertwisting algorithm for a perturbed quadrotor UAV
Min et al. Decentralized UAV formation tracking flight control using gyroscopic force
Han et al. Distributed fault-tolerant formation control for multiple unmanned aerial vehicles under actuator fault and intermittent communication interrupt
Zhang et al. A distributed adaptive mixed self-/event-triggered formation control approach for multiple stratospheric airships with relative state constraints and input delay
Dong et al. Formation control for unmanned aerial vehicle swarm with disturbances: A mission‐driven control scheme
Zhou et al. Finite‐time spatial path following control for a robotic underactuated airship
Lan et al. Adaptive 3D Distance‐Based Formation Control of Multiagent Systems with Unknown Leader Velocity and Coplanar Initial Positions
Jin et al. Cluster formation for multi‐agent systems under disturbances and unmodelled uncertainties
Zhang et al. Formation Control for Multiple Quadrotor Aircraft via Fixed‐time Consensus Algorithm
Arab et al. Distributed adaptive containment control for a group of aerial robots with external disturbances