Problem Of Unmanned Aerial Vehicles Research Articles

Моделювання прийняття рішень оператором дистанційно пілотованого літального апарату в аварійних ситуаціях

Мета: Відсутність алгоритму рекомендацій дій оператора БПЛА в надзвичайних ситуаціях, розкладання процесу прийняття рішень оператором БПЛА в надзвичайних ситуаціях, розробка структури системи підтримки прийняття рішень для оператора БПЛА, розробка моделей прийняття рішень оператором БПЛА. Методи: Створення алгоритму прийняття рішень за допомогою критеріїв Вальда, Гурвіца, Ла Пласа. Результати: програма "UAV_AS", що дає рекомендації оператору БПЛА про те, як діяти в разі виникнення надзвичайної ситуації. Авторами розроблено алгоритм дій рекомендації оператора БПЛА в надзвичайних ситуаціях. Представлений процес прийняття рішень оператором БПЛА в надзвичайних ситуаціях у вигляді детермінованої моделі із застосуванням методів мережевого моделювання. Побудовано мережевий граф, за яким визначено критичний час на парирування надзвичайної ситуації у разі польоту БПЛА. Розроблено структуру розподіленої СППР для колективного управління пілотованих та безпілотних літальних апаратів оператором. Авторами розроблено бази даних для локальних СППР операторів управління БПЛА, Розроблено моделі прийняття рішень оператором БПЛА в умовах ризику та в умовах невизначеності у разі аварійної посадки БПЛА. Обговорення: У статті розглядаються проблеми польотів безпілотних літальних апаратів для вирішення різних завдань в надзвичайній ситуації, засноване на статистичних даних від аналізу типів надзвичайних ситуацій для безпілотних літальних апаратів. Визначається послідовність дій оператора БПЛА в разі виникнення надзвичайних ситуацій.

Heuristic and Genetic Algorithm Approaches for UAV Path Planning under Critical Situation

The present paper applies a heuristic and genetic algorithms approaches to the path planning problem for Unmanned Aerial Vehicles (UAVs), during an emergency landing, without putting at risk people and properties. The path re-planning can be caused by critical situations such as equipment failures or extreme environmental events, which lead the current UAV mission to be aborted by executing an emergency landing. This path planning problem is introduced through a mathematical formulation, where all problem constraints are properly described. Planner algorithms must define a new path to land the UAV following problem constraints. Three path planning approaches are introduced: greedy heuristic, genetic algorithm and multi-population genetic algorithm. The greedy heuristic aims at quickly find feasible paths, while the genetic algorithms are able to return better quality solutions within a reasonable computational time. These methods are evaluated over a large set of scenarios with different levels of diffculty. Simulations are also conducted by using FlightGear simulator, where the UAV’s behaviour is evaluated for different wind velocities and wind directions. Statistical analysis reveal that combining the greedy heuristic with the genetic algorithms is a good strategy for this problem.

Dynamic path planning based on improved boundary value problem for unmanned aerial vehicle

When unmanned aerial vehicles (UAVs) track a moving target in complex environment, most path planning methods are difficult to combine real-time calculation and optimality. A real-time path planning method based on boundary value problem (BVP) is studied. First, a grid model of terrain is established based on UAV constraints. Then the structure of receding horizon planning ensures the real-time tracking to moving target, and the path is determined based on BVP in each horizon window. The sub-goal of horizon window is designed by line-of-sight, and the method of updating potential field dynamically and the calculation of flight direction are proposed. By comparison with other methods, the simulation results show that the method can ensure the path smooth and feasible. It can track the moving target in real-time and have some optimality, which is suitable for the mission of UAV to track moving target in complex environment.

UAV State Estimation Using Adaptive Complementary Filters

We address the complete state estimation problem of unmanned aerial vehicles, even under high-dynamic 3-D aerobatic maneuvers, while using low-cost sensors with bias variations and higher levels of noise. In such conditions, the control demand, for a robust real-time data fusion filter with minimal lag and noise, is addressed with the efficiency of a complementary filter scheme. First, the attitude is directly estimated in Special Orthogonal Group (SO(3)) by complementing the noisy accelerometer/magnetometer vector basis with a gyro propagated vector basis. Data fusion follows a least square minimization in SO(3) (Wahba’s problem) solved in an analytic nonrecursive manner. Stability of the proposed filter is shown and performance metrics are extracted, whereas the computational complexity has been minimized with an appropriate reference frame and a custom singular value decomposition algorithm. An adaptation scheme is proposed to allow unhindered operation of the filter to erroneous inputs introduced by the high dynamics of a 3-D flight. Finally, the velocity/position estimation is mainly constructed by complementary filters combining multiple sensors. In addition to the low complexity and the filtering of the noise, the proposed observer is aided through a developed vision algorithm, enabling the use of the filter in Global-Positioning-System-denied environments. Extensive experimental results and comparative studies with state-of-the-art filters, either in the laboratory or in the field using high-performance autonomous helicopters, demonstrate the efficacy of the proposed scheme in demanding conditions.

Deployment method of UAVs with energy constraint for multiple tasks

This reported work addresses the deployment problem of unmanned aerial vehicles (UAVs) for multiple scattered tasks. The objective is to minimise the duration of all UAVs in reaching their assigned task locations so that the overall time needed to accomplish a mission is minimised. Taking speed and energy constraints into account, it is advantageous to transport UAVs by a large-scale ground vehicle in the shortest time. However, computation of the deployment points requires too much time for an optimal operation to accomplish a task. Therefore, an approximate solution is pursued by an algorithm for efficient deployment. The feasibility of the proposed algorithm is demonstrated through simulations.

UAV feasible path planning based on disturbed fluid and trajectory propagation

In this paper, a novel algorithm based on disturbed fluid and trajectory propagation is developed to solve the three-dimensional (3-D) path planning problem of unmanned aerial vehicle (UAV) in static environment. Firstly, inspired by the phenomenon of streamlines avoiding obstacles, the algorithm based on disturbed fluid is developed and broadened. The effect of obstacles on original fluid field is quantified by the perturbation matrix, where the tangential matrix is first introduced. By modifying the original flow field, the modified one is then obtained, where the streamlines can be regarded as planned paths. And the path proves to avoid all obstacles smoothly and swiftly, follow the shape of obstacles effectively and reach the destination eventually. Then, by considering the kinematics and dynamics equations of UAV, the method called trajectory propagation is adopted to judge the feasibility of the path. If the planned path is unfeasible, repulsive and tangential parameters in the perturbation matrix will be adjusted adaptively based on the resolved state variables of UAV. In most cases, a flyable path can be obtained eventually. Simulation results demonstrate the effectiveness of this method.

СТАН ТА ПЕРСПЕКТИВИ РОЗВИТКУ БЕЗПІЛОТНИХ ЛІТАЛЬНИХ АПАРАТІВ В УКРАЇНІ

The article analyzes the activities of state of the problem of unmanned aerial vehicles in Ukraine. Opredeleny main trends of contemporary and long-term development that will stimulate research and production potential of Ukraine in the development and construction of the UAV, which is not fully utilized. The authors propose to use state support and perform the following steps: to conduct an economic evaluation of acquisition opportunities (abroad) UAV and manufacturing its own components BPAK; develop a strategy for the development of UAV (unmanned roadmap), to develop a national target program

Design of Path Following Method for Unmanned Aerial Vehicles using Normal Forms

The path following problem for unmanned aerial vehicles (UAVs) is considered. The target path is chosen as a planar curve which is located at a specified altitude. In the simplest case UAV should move along a predicted planar curve with a constant velocity. In more complicated casesthe UAVvelocityisconsideredassomefunctionoftimewhich is knownatcurrent moment but no prolongation can be done. Ideas that are used for solving of the planar path following problem for wheeled robots now apply for UAVs. To obtain the stabilizing control the theory of normal form of an afine system with single output is used in the case of constant velocity. Some changes of the independent variable are investigated in order to get nonstationary normal forms which allow to design stabilizing control. Results of numerical simulations are demonstrated.

LQG Control of Unmanned Aerial Vehicles Under Communication Constraints

This paper addresses the LQG control problem for unmanned aerial vehicles (UAV) with time delays. In particular, the case with data-rate limitations is considered. It is shown in our results that the data rate of the communication channel has important effects on the control performances. It is derived that there exists a tradeoff between the data rate and the LQG cost. A quantization, coding, and control scheme is proposed to stabilize the unstable plant. Simulation results show the validity of the proposed scheme. DOI: http://dx.doi.org/10.11591/telkomnika.v11i9.2426

Fuzzy Model Based Control of Unmanned Aerial Vehicle

The design of fuzzy model based controller with a new analytical inversion method is presented and applied for attitude control problem of Unmanned Aerial Vehicle (UAV). The purpose of adaptive controller is to follow a certain pitch angle command under level flight condition which requires the roll stabilization controller. The Aerosonde simulation model has been chosen to apply the proposed analytical fuzzy model based controller. The simulation results show that both the roll rate and the pitch angles are tracked by the adaptive controller without significant transients. Flight test results for angle of attack control of a fixed wing platform which has been developed at UNSW@ADFA show that the controller is robust to operate in a real time environment.

Distributed MPC-Based Path Planning for UAVs under Radio Communication Path Loss Constraints

In this paper we address the Model Predictive Control (MPC)-based path planning problem for Unmanned Aerial Vehicles (UAVs). Our goal is to find trajectories that are safe with respect to grounding and collision, fuel efficient and satisfy criteria for communication such that the UAVs form a chain with a given radio communication capacity. A centralized MPC and a distributed MPC approaches to solve the path planning problem are proposed. Both approaches explicitly incorporate constraints on radio communication path losses, computed by using SPLAT!. In order to enhance the MPC problem computation, the terrain below each UAV and the communication path losses are approximated with linear functions. The control performance and the computational efficiency of the distributed MPC and the centralized MPC approaches are compared based on a simulation case study with two UAVs.

Constrained Optimal Controller Design of Aerial Robotics Based on Invariant Sets

Constrained optimal control problem of unmanned aerial vehicle (UAV) which is also called aerial robotics is studied in this paper. The nonlinear system of small unmanned helicopter with bounded disturbance is abstracted and modeled by PWA hybrid systems model. As the complexity on-line computation for a class of large hybrid systems, an explicit optimal controller for hybrid systems based on multi-parametric quadratic programming (mp-QP) is proposed. The feasible domain which is the maximal controlled invariant sets for hybrid systems is partitioned in backward dynamic programming by mp-QP method. At each step, one step reachable sets are computed, optimal control laws are constructed to the corresponding regions, and the explicit optimal controller is obtained. Finally simulation results verify the effectiveness of the proposed control method.