Uninhabited Combat Air Vehicle Research Articles

A Comparative Study of Swarm Intelligence Algorithms for UCAV Path-Planning Problems

Path-planning for uninhabited combat air vehicles (UCAV) is a typically complicated global optimization problem. It seeks a superior flight path in a complex battlefield environment, taking into various constraints. Many swarm intelligence (SI) algorithms have recently gained remarkable attention due to their capability to address complex optimization problems. However, different SI algorithms present various performances for UCAV path-planning since each algorithm has its own strengths and weaknesses. Therefore, this study provides an overview of different SI algorithms for UCAV path-planning research. In the experiment, twelve algorithms that published in major journals and conference proceedings are surveyed and then applied to UCAV path-planning. Moreover, to demonstrate the performance of different algorithms in further, we design different scales of problem cases for those comparative algorithms. The experimental results show that UCAV can find the safe path to avoid the threats efficiently based on most SI algorithms. In particular, the Spider Monkey Optimization is more effective and robust than other algorithms in handling the UCAV path-planning problem. The analysis from different perspectives contributes to highlight trends and open issues in the field of UCAVs.

Quantum inspired monarch butterfly optimisation for UCAV path planning navigation problem

As a complicated high-dimensional optimisation problem, path planning navigation problem for uninhabited combat air vehicles (UCAV) is to obtain a shortest safe flight route with different types of constrains under complicated combating environments. Monarch butterfly optimisation (MBO) is a highly promising swarm intelligence algorithm. Since then, though it has successfully solved several challenging problems, MBO may be trapped into local optima sometimes. In order to improve the performance of MBO, quantum computation is firstly incorporated into the basic MBO algorithm and a new quantum inspired MBO algorithm is then proposed called QMBO. In QMBO, a certain number of the worst butterflies are updated by quantum operators. In this paper, the UCAV path planning navigation problem is modelled into an optimisation problem and then, its optimal path can be obtained by the proposed QMBO algorithm. In addition, B-spline curves are utilised to further smoothen the obtained path and make it more feasible for UCAV. The UCAV path obtained by QMBO is compared with the basic MBO and the experimental results show that QMBO can find much shorter path than MBO.

The effect of angle of attack on the aeroacoustic environment within the weapons bay of a generic UCAV

Cavity flow studies are generally concerned with observing the effect of geometry changes whilst maintaining a fixed zero angle of attack. Cavities employed as weapons bays will, however, experience a range of angles of attack. This paper presents the first known results showing the effect of flight angle of attack on the aeroacoustic characteristics of an internal weapons bay installed in an uninhabited combat air vehicle (UCAV). The UCAV geometry consisted of a Boeing M219-type cavity in a Boeing UCAV1303 airframe. Numerical simulation was conducted using a full-scale detached eddy simulation model and representative transonic flight conditions. As well as the reference case of zero degrees, data for angles of attack of 3.0, 4.5 and 6.0 degrees were analysed. Experimental data was used to validate the reference computational model, which agreed with the overall fluctuating sound pressure level (OAFPL) to within the experimental uncertainty of 4 dB. Data from the computational model was post-processed with frequency-domain and time-frequency-domain techniques showing that the flow structure within the weapons bay was altered significantly by the angle of attack changes, affecting the mean pressure distribution, frequency spectra and resonant modes. Overall, increasing the angle of attack from 0.0 to 3.0 degrees produced an increment in the acoustic load whilst a further increase tended to affect the resonance mechanism and thereby reduce the coherence and the temporal footprints of the resonant modes.

Numerical Simulation and Reduced-Order Aerodynamic Modeling of a Lambda Wing Configuration

This work is a contribution to the North Atlantic Treaty Organization Science and Technology Organization Task Group AVT-201 on stability and control estimation methods. Specifically, this study uses the Cobalt and Kestrel computational fluid dynamics flow solvers to predict and create reduced-order models for the aerodynamic force and moment coefficients of a generic uninhabited combat air vehicle under static and dynamic conditions and compare them with wind tunnel data. The particular reduced-order method investigated in this work is based on response functions. The geometry under investigation is known as DLR-F19, which is a lambda-wing configuration with a 53 deg angle of sweep at the leading edge. Each wing has two control surfaces on the trailing edge, hinged along the 75% chord line. Two different gridding strategies are employed: one uses an overset grid method for simulation of control-surface deflections without the need for regridding, and the other is to create a new grid for each control-surface deflection. The simulation results of these grids are compared in order to identify the effect of gaps present in the overset method. A grid is also created to study the presence of the sting geometry as tested in the experiments. Validation results are shown for different turbulence models at selected flight conditions. Overall, a good agreement between computational results and the wind tunnel experimental data for total force coefficients is achieved. However, delayed detached eddy simulations are required for angles of attack greater than 20 deg. The reduced-order modeling results show that predictions from a nonlinear model match quite well with full-order data of small amplitude motions. Small discrepancies can be seen in the plots of large-amplitude motions as well. The model predictions get worse when the belly sting geometry is included in simulations because of the nonlinear hysteresis behavior of a wake formed behind the sting.

Objectives, approach, and scope for the AVT-183 diamond-wing investigations

A roughly six-year investigation of blunt-leading-edge vortical separation has recently been completed. Principles from a hierarchical complexity approach were used to develop a simple diamond wing configuration with vortex flow properties that were relevant to those of a complex Uninhabited Combat Air Vehicle concept, known as SACCON. The focus of this paper is to present an overview of the project including the basic flow of interest, the approach used to develop the specific research investigation, and the scope of the results. Subsequent papers address specific experimental and numerical findings. This work was conducted under the NATO Science and Technology Organization, Applied Vehicle Technology panel.

Three-dimensional path planning for UCAV using an improved bat algorithm

As a challenging high dimension optimization problem, three-dimensional path planning for Uninhabited Combat Air Vehicles (UCAV) mainly centralizes on optimizing the flight route with different types of constrains under complicated combating environments. An improved version of Bat Algorithm (BA) in combination with a Differential Evolution (DE), namely IBA, is proposed to optimize the UCAV three-dimensional path planning problem for the first time. In IBA, DE is required to select the most suitable individual in the bat population. By connecting the selected nodes using the proposed IBA, a safe path is successfully obtained. In addition, B-Spline curves are employed to smoothen the path obtained further and make it practically more feasible for UCAV. The performance of IBA is compared to that of the basic BA on a 3-D UCAV path planning problem. The experimental results demonstrate that IBA is a better technique for UCAV three-dimensional path planning problems compared to the basic BA model.

A Glowworm Swarm Optimization Algorithm for Uninhabited Combat Air Vehicle Path Planning

AbstractUninhabited combat air vehicle (UCAV) path planning is a complicated, high-dimension optimization problem. To solve this problem, we present in this article an improved glowworm swarm optimization (GSO) algorithm based on the particle swarm optimization (PSO) algorithm, which we call the PGSO algorithm. In PGSO, the mechanism of a glowworm individual was modified via the individual generation mechanism of PSO. Meanwhile, to improve the presented algorithm’s convergence rate and computational accuracy, we reference the idea of parallel hybrid mutation and local search near the global optimal location. To prove the performance of the proposed algorithm, PGSO was compared with 10 other population-based optimization methods. The experiment results show that the proposed approach is more effective in UCAV path planning than most of the other meta-heuristic algorithms.

A Wolf Colony Search Algorithm Based on the Complex Method for Uninhabited Combat Air Vehicle Path Planning

Path planning for uninhabited combat air vehicle (UCAV) is a class of complicated high dimensional optimization problem, which mainly centralizes on path planning considering the different kinds of constrains in the complex environment of war. In order to solve this problem, it is converted to a kind of constrained function optimization problem, and a wolf colony search algorithm based on the complex method is proposed, which combines the complex method with a wolf colony search algorithm, and it solves the problem of UCAV path planning successfully. The experiment results show that our proposed algorithm is feasible and effective to solve the problem of UCAV path planning.

Chaotic predator–prey biogeography-based optimization approach for UCAV path planning

This paper proposes a novel Chaotic Predator–Prey Biogeography-Based Optimization (CPPBBO) approach for solving the path planning problems of Uninhabited Combat Air Vehicle (UCAV). To generate optimal or near-optimal flight path, path planning is a key part of UCAV assignment planning system. The planned path can ensure UCAV avoid hostile threats and safely reach an intended target with minimum fuel cost. An improved biogeography-based optimization algorithm is presented for solving the optimization problem in the path planning process. Biogeography-Based Optimization (BBO) is a new bio-inspired optimization algorithm. This algorithm searches for global optimum mainly through two steps: migration and mutation. To enhance the global convergence of the BBO algorithm, the chaos theory and the concept of predator–prey are adopted to get new search mechanism. The comparative simulation results are given to show that our proposed CPPBBO algorithm is more efficient than basic BBO, CBBO and PPBBO in solving the UCAV path planning problems.

An Improved Bat Algorithm and its Application in Multiple UCAVs

Uninhabited Combat Air Vehicles is a complicated global optimum problem. In this paper, according to the characteristics of Uninhabited Combat Air Vehicles, an improved bat algorithm was used to solve Uninhabited Combat Air Vehicles. The algorithm was experimented and the experimental results show that the improved algorithm to be successful in locating multiple solutions and better accuracy. Simulations and results indicate that the improved bat algorithm has better feasibility and validity for solving the multiple UCAV.

Optimal Formation Reconfiguration Control of Multiple UCAVs Using Improved Firefly Algorithm

Optimal formation reconfiguration control of multiple is a complicated global optimum problem. In this paper, according to the characteristics of Uninhabited Combat Air Vehicles. A Novel Firefly Algorithm was used to solve Uninhabited Combat Air Vehicles, the redesign of the individual location update in the algorithm, and introduced a Levy flight to increase the population search domain. In addition, a local search algorithm is introduced to enhance the local search ability in this paper. the algorithm was experimented and the experimental results show that the new algorithm to be successful in locating multiple solutions and better accuracy. Series experimental results demonstrate the feasibility and effectiveness of the proposed method in solving the optimal formation reconfiguration control problem for multiple UCAV.

Three Unstructured Computational Fluid Dynamics Studies on Generic Unmanned Combat Aerial Vehicle

Three independent studies from the United States (NASA), Sweden (Swedish Defense Research Agency), and Australia (Defense Science and Technology Organization) are analyzed to assess the state of current unstructured grid computational fluid dynamic tools and practices for predicting the complex static and dynamic aerodynamic and stability characteristics of a generic 53-deg swept, round-leading-edge uninhabited combat air vehicle configuration, calledSACCON (which stands for “stability and control configuration”). NASAexercised theUSM3D tetrahedral cell-centered flow solver, while the Swedish Defense Research Agency and the Defense Science and Technology Organization applied the Swedish Defense Research Agency/EDGE general-cell vertex-based solver. The authors primarily employ the Reynolds-averaged Navier–Stokes assumption, with a limited assessment of the EDGEdetached eddy simulation extension, to explore sensitivities to grids and turbulencemodels. Correlations with experimental data are provided for force and moments, surface pressure, and off-body flow measurements. The vortical flowfield over SACCON proved extremely difficult to model adequately. As a general rule, the prospect of obtaining reasonable correlations of SACCON pitching moment characteristics with the Reynolds-averaged Navier–Stokes formulation is not promising, even for static cases. However, dynamic pitch oscillation results seem to produce a promising characterization of shapes for the lift and pitching moment hysteresis curves. Future studies of this configuration should include more investigation with higher-fidelity turbulence models such as detached eddy simulation.

A Hybrid Metaheuristic DE/CS Algorithm for UCAV Three-Dimension Path Planning

Three-dimension path planning for uninhabited combat air vehicle (UCAV) is a complicated high-dimension optimization problem, which primarily centralizes on optimizing the flight route considering the different kinds of constrains under complicated battle field environments. A new hybrid metaheuristic differential evolution (DE) and cuckoo search (CS) algorithm is proposed to solve the UCAV three-dimension path planning problem. DE is applied to optimize the process of selecting cuckoos of the improved CS model during the process of cuckoo updating in nest. The cuckoos can act as an agent in searching the optimal UCAV path. And then, the UCAV can find the safe path by connecting the chosen nodes of the coordinates while avoiding the threat areas and costing minimum fuel. This new approach can accelerate the global convergence speed while preserving the strong robustness of the basic CS. The realization procedure for this hybrid metaheuristic approach DE/CS is also presented. In order to make the optimized UCAV path more feasible, the B-Spline curve is adopted for smoothing the path. To prove the performance of this proposed hybrid metaheuristic method, it is compared with basic CS algorithm. The experiment shows that the proposed approach is more effective and feasible in UCAV three-dimension path planning than the basic CS model.

A Bat Algorithm with Mutation for UCAV Path Planning

Path planning for uninhabited combat air vehicle (UCAV) is a complicated high dimension optimization problem, which mainly centralizes on optimizing the flight route considering the different kinds of constrains under complicated battle field environments. Original bat algorithm (BA) is used to solve the UCAV path planning problem. Furthermore, a new bat algorithm with mutation (BAM) is proposed to solve the UCAV path planning problem, and a modification is applied to mutate between bats during the process of the new solutions updating. Then, the UCAV can find the safe path by connecting the chosen nodes of the coordinates while avoiding the threat areas and costing minimum fuel. This new approach can accelerate the global convergence speed while preserving the strong robustness of the basic BA. The realization procedure for original BA and this improved metaheuristic approach BAM is also presented. To prove the performance of this proposed metaheuristic method, BAM is compared with BA and other population-based optimization methods, such as ACO, BBO, DE, ES, GA, PBIL, PSO, and SGA. The experiment shows that the proposed approach is more effective and feasible in UCAV path planning than the other models.

Computational Fluid Dynamics Analyses of Flow over Weapons-Bay Geometries

Detached-eddy simulations for the M219 experimental cavity geometry and the 1303 uninhabited combat air vehicle cavity geometry are presented. First, results from three computations are presented with the aim of studying the effect of imposing synthetic velocity fluctuations at the inflow boundary. Both methods employed (synthetic-eddy method and fluctuations from a precursor large-eddy simulation) increased the high-frequency content in the boundary layer upstream of the cavity. Averaged profiles showed little change in the streamwise velocity; however, the profiles of normal velocity were noticeably different. The influence of the upstream boundary layer on the cavity flowfield means that the full aircraft geometry needed to be modeled. Consequently, advanced multiblock topologies had to be used to properly represent the planform of the uninhabited combat air vehicle and all the details of the cavity, including doors and hinges, while sliding meshes were needed to insert the store into the uninhabited combat air vehicle configuration. Results with an empty cavity were encouraging for such complex configurations. Visualizations using the Q criteria revealed the added turbulent content due to the door leading edges and the door hinges. The addition of a store in between the doors had little effect close to the front wall. However, averaged flowfields showed that the proximity of the shear layer to the apex of the store deflected it downward into the cavity and restricted its growth. Outside the cavity, shedding was observed from the sting and force balance.

Chaotic artificial bee colony approach to Uninhabited Combat Air Vehicle (UCAV) path planning

Path planning of Uninhabited Combat Air Vehicle (UCAV) is a rather complicated global optimum problem which is about seeking a superior flight route considering the different kinds of constrains under complex combat field environment. Artificial Bee Colony (ABC) algorithm is a new optimization method motivated by the intelligent behavior of honey bees. In this paper, we propose an improved ABC optimization algorithm based on chaos theory for solving the UCAV path planning in various combat field environments, and the implementation procedure of our proposed chaotic ABC approach is also described in detail. Series of experimental comparison results are presented to show the feasibility, effectiveness and robustness of our proposed method.

Evaluation of DES for weapons bays in UCAVs

This paper demonstrates the Detached Eddy Simulation (DES) approach for the computation of flows around uninhabited combat air vehicles. One of the key features of this new family of aircraft is that weapon bays are used to enhance stealth characteristics and improve aerodynamic performance. The highly energetic flow-field within the weapon bays can change dramatically the aerodynamics of these aircraft and for this reason detailed CFD analyses are needed to provide insight in the change of loads encountered when weapon bays are exposed. In contrast to previous studies where idealised, isolated cavities are used as model problems, a realistic aircraft geometry is used in this work. Computations using DES are presented for the clean aircraft, the idealised cavity and the complete configuration. Advanced multi-block topologies are used which allow for most of the geometric details of the aircraft to be preserved and resolved by the employed CFD solver. For all cases where weapon bays are present, DES is used for the simulation while statistical turbulence models prove to be adequate for the clean aircraft cases. Comparisons against experimental data demonstrate the accuracy of the employed methods and strengthen confidence in the employed DES models. The overall loading of the aircraft is well-predicted even at high angles of attack and DES appears to offer encouraging results at low and high Mach number cases. Experiments conducted by QinetiQ and DSTL are used for validation of the DES method and results indicate that less than 3dB discrepancies in the overall sound pressure level can be obtained in comparison to the tunnel data.

Three-dimension path planning for UCAV using hybrid meta-heuristic ACO-DE algorithm

Three-dimension path planning of uninhabited combat air vehicle (UCAV) is a complicated optimal problem, which mainly focuses on optimizing the flight route considering the different types of constrains under complicated combating environments. A new hybrid meta-heuristic ant colony optimization (ACO) and differential evolution (DE) algorithm is proposed to solve the UCAV three-dimension path planning problem. DE is applied to optimize the pheromone trail of the improved ACO model during the process of ant pheromone updating. Then, the UCAV can find the safe path by connecting the chosen nodes of the three-dimensional mesh while avoiding the threats area and costing minimum fuel. This new approach can accelerate the global convergence speed while preserving the strong robustness of the basic ACO. The realization procedure for this hybrid meta-heuristic approach is also presented in detail. In order to make the optimized UCAV path more feasible, the к-trajectory is adopted for smoothing the path. Finally, series experimental comparison results demonstrate that this proposed hybrid meta-heuristic method is more effective and feasible in UCAV three-dimension path planning than the basic ACO model.

Optimal Formation Reconfiguration Control of Multiple UCAVs Using Improved Particle Swarm Optimization

Optimal formation reconfiguration control of multiple Uninhabited Combat Air Vehicles (UCAVs) is a complicated global optimum problem. Particle Swarm Optimization (PSO) is a population based stochastic optimization technique inspired by social behaviour of bird flocking or fish schooling. PSO can achieve better results in a faster, cheaper way compared with other bio-inspired computational methods, and there are few parameters to adjust in PSO. In this paper, we propose an improved PSO model for solving the optimal formation reconfiguration control problem for multiple UCAVs. Firstly, the Control Parameterization and Time Discretization (CPTD) method is designed in detail. Then, the mutation strategy and a special mutation-escape operator are adopted in the improved PSO model to make particles explore the search space more efficiently. The proposed strategy can produce a large speed value dynamically according to the variation of the speed, which makes the algorithm explore the local and global minima thoroughly at the same time. Series experimental results demonstrate the feasibility and effectiveness of the proposed method in solving the optimal formation reconfiguration control problem for multiple UCAVs.

스텔스 무인전투기 형상의 와류 거동에 대한 흐름가시화 연구

스텔스 무인전투기 형상 주위 유동장의 수동에서의 흐름가시화 시험을 통한 기본 공력 특성 파악 연구가 수행되었다. 시험은 자유류 속도 12.7 cm/sec와 평균시위 기준 레이놀즈수 <TEX>$1.4{\times}10^4$</TEX>에서 수행되었다. 물감을 사용하여 가시화된 와류의 생성 및 붕괴 현상은 앞서 수행된 힘과 모멘트 측정 결과와 비교되었다. 시험 결과 낮은 받음각에서는 동체와 날개 junction 와류가 큰 영향을 주지만, 높은 받음각 영역에서는 전방동체 와류 거동이 공력에 지배적인 영향을 줌을 확인하였다. Flow visualization study to qualitatively define the flow field over a stealth UCAV(Uninhabited Combat Air Vehicle) configuration in a water tunnel has been conducted to clarify the basic aerodynamic performance. The test was performed at freestream velocity of 12.7 cm/sec which was corresponding to a Reynolds number of <TEX>$1.4{\times}10^4$</TEX> based on mean aerodynamic chord. The development and breakdown of vortices illuminated by using dye were compared to the previous force and moment data. It was shown that the effect of the vortices generated by the main-body and junction are dominant in the low angle-of-attack region. However, in the high angle-of-attack region, the vortex generated by the fore-body mainly influenced the aerodynamic performance of the model.