6 research outputs found
Neural network control design for an unmanned aerial vehicle with a suspended payload
Unmanned aerial vehicles (UAVs) demonstrate excellent manoeuvrability in cluttered environments, which makes them a suitable platform as a data collection and parcel delivering system. In this work, the attitude and position control challenges for a drone with a package connected by a wire is analysed. During the delivering task, it is very difficult to eliminate the external unpredictable disturbances. A robust neural network-based backstepping sliding mode control method is designed, which is capable of monitoring the drone's flight path and desired attitude with a suspended cable attached. The convergence of the position and attitude errors together with the Lyapunov function are employed to attest to the robustness of the nonlinear transportation platform. The proposed control system is tested with a simulation and in an outdoor environment. The simulation and open field test results for the UAV transportation platform verify the controllers' reliability
Neural Network-Based Adaptive Control for Spacecraft Under Actuator Failures and Input Saturations
In this article, we develop attitude tracking control methods for spacecraft as rigid bodies against model uncertainties, external disturbances, subsystem faults/failures, and limited resources. A new intelligent control algorithm is proposed using approximations based on radial basis function neural networks (RBFNNs) and adopting the tunable parameter-based variable structure (TPVS) control techniques. By choosing different adaptation parameters elaborately, a series of control strategies are constructed to handle the challenging effects due to actuator faults/failures and input saturations. With the help of the Lyapunov theory, we show that our proposed methods guarantee both finite-time convergence and fault-tolerance capability of the closed-loop systems. Finally, benefits of the proposed control methods are illustrated through five numerical examples
Dynamics estimator based robust fault-tolerant control for VTOL UAVs trajectory tracking
This paper investigates the control issue of the trajectory tracking of vertical take-off and landing (VTOL) unmanned aerial vehicles (UAVs) in the presence of partial propeller fault and external disturbance. In particular, a robust passive fault-tolerant control strategy is proposed by introducing a first-order filter based dynamics estimator. First, a bounded force command is exploited by employing a new smooth saturation function in the output of the estimator. A sufficient condition in terms of a specified parameter selection criteria is provided to ensure the nonsingularity extraction of the command attitude. Then, a torque command is applied to the attitude loop tracking. Since there is merely one filter parameter involved in the dynamics estimator, the practical implementation and parameter tuning can be significantly simplified. Stability analysis indicates that the proposed control strategy guarantees the semi-globally ultimately bounded tracking of VTOL UAVs subject to partial propeller fault and external disturbance. Simulation and experiment results with comparison examples are performed to validate the effectiveness of the proposed strategy. Experimental results show that the proposed strategy achieves the trajectory tracking with a good performance (mean deviation 0.0074 m and standard deviation 0.1202 m) in the presence of 35% propeller fault and 4 m/s persistent wind disturbance
On finite-time anti-saturated proximity control with a tumbling non-cooperative space target
For the challenging problem that a spacecraft approaching a tumbling target with non-cooperative maneuver, an anti-saturated proximity control method is proposed in this paper. First, a brand-new appointed-time convergent performance function is developed via exploring Bezier curve to quantitatively characterize the transient and steady-state behaviors of the pose tracking error system. The major advantage of the proposed function is that the actuator saturation phenomenon at the beginning can be effectively reduced. Then, an anti-saturated pose tracking controller is devised along with an adaptive saturation compensator. Wherein, the finite-time stability of both the pose and its velocity error signals are guaranteed simultaneously in the presence of actuator saturation. Finally, two groups of illustrative examples are organized and verify that the close-range proximity is effectively realized even with unknown target maneuver
Shortest Route at Dynamic Location with Node Combination-Dijkstra Algorithm
Abstractâ Online transportation has become a basic
requirement of the general public in support of all activities to go
to work, school or vacation to the sights. Public transportation
services compete to provide the best service so that consumers
feel comfortable using the services offered, so that all activities
are noticed, one of them is the search for the shortest route in
picking the buyer or delivering to the destination. Node
Combination method can minimize memory usage and this
methode is more optimal when compared to A* and Ant Colony
in the shortest route search like Dijkstra algorithm, but canât
store the history node that has been passed. Therefore, using
node combination algorithm is very good in searching the
shortest distance is not the shortest route. This paper is
structured to modify the node combination algorithm to solve the
problem of finding the shortest route at the dynamic location
obtained from the transport fleet by displaying the nodes that
have the shortest distance and will be implemented in the
geographic information system in the form of map to facilitate
the use of the system.
Keywordsâ Shortest Path, Algorithm Dijkstra, Node
Combination, Dynamic Location (key words