This paper addresses cooperative search for multiple stationary ground targets by a group of unmanned aerial vehicles with limited sensing and communication capabilities. The whole surveillance ...region is partitioned into cells where each cell is associated with a probability of target existence within the cell, which constitutes a probability map for the whole region. Each agent keeps an individual probability map and updates the map individually with measurements according to Bayesian rule. A nonlinear transformation of the probability map is introduced to simplify the computation by linearizing the Bayesian update. A consensus-like distributed fusion scheme is proposed for multiagent map fusion. We prove that all the individual probability maps converge to the same one that reflects the true existence or nonexistence of targets within each cell. Coverage and topology control algorithms are designed for the path planning of mobile agents. Moreover, the performance of the fusion scheme for asynchronous implementations of sampling and communication is analyzed. Finally, the effectiveness of the proposed algorithms is illustrated via simulations.
Using the optical camera in remote sensing is limited in various environmental conditions. This paper presents a system of combining deep learning and image transform algorithms to detect landslide ...location in satellite images. In the deep learning part, a convolution neural network is used to classify satellite images contain landslides. From landslide images classified, in order to accurately identify landslides under different lighting conditions, this paper proposes a transformation algorithm Hue - Bi-dimensional empirical mode decomposition (H-BEMD) to determine the landslide region and size. After the location of landslide is detected, we discover the size change of the landslide based on different time points. In this study, we record an accuracy of up to 96% in the classification process, and the accuracy of landslide location almost absolute.
In this paper, we consider the problem of graceful performance degradation , for affine nonlinear systems. The method is an optimization based scheme, that gives a constructive way to reshape online ...the output reference for the post-fault system, and explicitly take into account the actuators and states saturations. The online output reference reshaping is associated with an online, model predictive control (MPC)-based, controller reconfiguration, that forces the post-fault system to track the new output reference. The effect of fault detection and diagnosis (FDD) uncertainties on the online controller reconfiguration stability are studied, to ensure at least boundedness of the closed-loop system's states. The reshaping and reconfiguration schemes are applied to the Caltech ducted fan numerical example, which is described by a non-minimum phase nonlinear model.
In this paper, we present the systematic design and implementation of a robust real-time embedded vision system for an unmanned rotorcraft for ground target following. The hardware construction of ...the vision system is presented, and an onboard software system is developed based on a multithread technique capable of coordinating multiple tasks. To realize the autonomous ground target following, a sophisticated feature-based vision algorithm is proposed by using an onboard color camera and navigation sensors. The vision feedback is integrated with the flight control system to guide the unmanned rotorcraft to follow a ground target in flight. The overall vision system has been tested in actual flight missions, and the results obtained show that the overall system is very robust and efficient.
In this brief, we propose a control allocation method for a particular class of uncertain over-actuated affine nonlinear systems, with unstable internal dynamics. Dynamic inversion technique is used ...for the commanded output to track a smooth output reference trajectory. The corresponding control allocation law has to guarantee the boundedness of the states, including the internal dynamics, and satisfy control constraints. The proposed method is based on a Lyapunov design approach with finite-time convergence to a given invariant set. The derived control allocation is in the form of a dynamic update law which, together with a sliding mode control law, guarantees boundedness of the output tracking error as well as of the internal dynamics. The effectiveness of the control law is tested on a numerical model of the non-minimum phase planar vertical take-off and landing (PVTOL) system.
In this paper, we present the design and implementation of an autonomous flight control law for a small-scale unmanned aerial vehicle (UAV) helicopter. The approach is decentralized in nature by ...incorporating a newly developed nonlinear control technique, namely the composite nonlinear feedback control, together with dynamic inversion. The overall control law consists of three hierarchical layers, namely, the kernel control, command generator and flight scheduling, and is implemented and verified in flight tests on the actual UAV helicopter. The flight test results demonstrate that the UAV helicopter is capable of carrying out complicated flight missions autonomously.
This paper presents an approach for data-driven modeling of aeroelasticity and its application to flutter control design of a wind-tunnel wing model. Modeling is centered on system identification of ...unsteady aerodynamic loads using computational fluid dynamics data, and adopts a nonlinear multivariable extension of the Hammerstein-Wiener system. The formulation is in modal coordinates of the elastic structure, and yields a reduced-order model of the aeroelastic feedback loop that is parametrized by airspeed. Flutter suppression is thus cast as a robust stabilization problem over uncertain airspeed, for which a low-order H∞ controller is computed. The paper discusses in detail parameter sensitivity and observability of the model, the former to justify the chosen model structure, and the latter to provide a criterion for physical sensor placement. Wind tunnel experiments confirm the validity of the modeling approach and the effectiveness of the control design.
This brief discusses the convergence analysis of proportional navigation (PN) guidance law in the presence of delayed line-of-sight (LOS) rate information. The delay in the LOS rate is introduced by ...the missile guidance system that uses a low cost sensor to obtain LOS rate information by image processing techniques. A Lyapunov-like function is used to analyze the convergence of the delay differential equation (DDE) governing the evolution of the LOS rate. The time-to-go until which decreasing behaviour of the Lyapunov-like function can be guaranteed is obtained. Conditions on the delay for finite time convergence of the LOS rate are presented for the linearized engagement equation. It is observed that in the presence of line-of-sight rate delay, increasing the effective navigation constant of the PN guidance law deteriorates its performance. Numerical simulations are presented to validate the results.
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