Flight Constraints Research Articles

Receding Horizon Control with Extended Solution for UAV Path Planning

The receding horizon control (RHC) greatly reduces the planning time and achieves great success in UAV online path planning because of rolling window optimization. However, due to its small range of path search in the time window, UAVs cannot cope with environments with uncertain obstacles and multiple flight constraints. Therefore, the receding horizon control with extended solution (RHC-eS) method is proposed for UAV path planning based on the traditional RHC. This method first designs the path expansion mechanism, which not only expands the search range of feasible solutions but also ensures the real-time performance by the two-way search strategy. Secondly, in order to increase the richness of solutions, the crossover and directional variation strategy of Genetic Algorithm (GA) are integrated. Finally, the Sequential Quadratic Programming (SQP) method is used to optimize the objective function. The simulation results of UAV path planning in simple and complex environments certify that the proposed method can obtain shorter, safer, and smoother paths compared with the existing methods.

Flight Trajectories Optimization of Fixed-Wing UAV by Bank-Turn Mechanism

This paper addresses an optimization of Unmanned Aerial Vehicle (UAV) flight trajectories by bank-turn mechanism for a fixed-wing UAV at a constant altitude. The flight trajectories should be optimal and stay in the UAV flight operational area. The maneuver planning is conducted in two steps, which are UAV path planning and UAV flight trajectory planning. For the first step, the Bezier curve is employed as a maneuvering path. The path planning optimization objective is to minimize the path length while satisfying maximum curvature and collision avoidance constraints. The flight trajectories optimization objective is to minimize maneuvering time and load factor considering, minimum/maximum speed, minimum/maximum acceleration, maximum roll angle, maximum turn rate, and aerodynamics constraints. The variable speed trajectory generation is developed within allowable speed zone considering these UAV flight constraints by employing meta-heuristic optimizations. Results show that the PSO have outperformed the GA and the GWO for both steps of path planning and trajectory planning. The variable speed has succeeded in reducing the load factor during the bank-turn mechanism using the Bezier curve. The variable speed is recommended to be conducted when the result of the maneuvering path involve the lower turning radius. A simultaneous on arrival target mission has also succeeded to be conducted using the combination of the variable speed and constant speed strategies.

FC-RRT*: An Improved Path Planning Algorithm for UAV in 3D Complex Environment

In complex environments, path planning is the key for unmanned aerial vehicles (UAVs) to perform military missions autonomously. This paper proposes a novel algorithm called flight cost-based Rapidly-exploring Random Tree star (FC-RRT*) extending the standard Rapidly-exploring Random Tree star (RRT*) to deal with the safety requirements and flight constraints of UAVs in a complex 3D environment. First, a flight cost function that includes threat strength and path length was designed to comprehensively evaluate the connection between two path nodes. Second, in order to solve the UAV path planning problem from the front-end, the flight cost function and flight constraints were used to inspire the expansion of new nodes. Third, the designed cost function was used to guide the update of the parent node to allow the algorithm to consider both the threat and the length of the path when generating the path. The simulation and comparison results show that FC-RRT* effectively overcomes the shortcomings of standard RRT*. FC-RRT* is able to plan an optimal path that significantly improves path safety as well as maintains has the shortest distance while satisfying flight constraints in the complex environment. This paper has application value in UAV 3D global path planning.

Topology-Based Routing Protocols and Mobility Models for Flying Ad Hoc Networks: A Contemporary Review and Future Research Directions

Telecommunications among unmanned aerial vehicles (UAVs) have emerged recently due to rapid improvements in wireless technology, low-cost equipment, advancement in networking communication techniques, and demand from various industries that seek to leverage aerial data to improve their business and operations. As such, UAVs have started to become extremely prevalent for a variety of civilian, commercial, and military uses over the past few years. UAVs form a flying ad hoc network (FANET) as they communicate and collaborate wirelessly. FANETs may be utilized to quickly complete complex operations. FANETs are frequently deployed in three dimensions, with a mobility model determined by the work they are to do, and hence differ between vehicular ad hoc networks (VANETs) and mobile ad hoc networks (MANETs) in terms of features and attributes. Furthermore, different flight constraints and the high dynamic topology of FANETs make the design of routing protocols difficult. This paper presents a comprehensive review covering the UAV network, the several communication links, the routing protocols, the mobility models, the important research issues, and simulation software dedicated to FANETs. A topology-based routing protocol specialized to FANETs is discussed in-depth, with detailed categorization, descriptions, and qualitatively compared analyses. In addition, the paper demonstrates open research topics and future challenge issues that need to be resolved by the researchers, before UAVs communications are expected to become a reality and practical in the industry.

Online midcourse guidance method for boost phase interception via adaptive convex programming

This paper proposes an online midcourse guidance method for boost phase interception. Dynamic models are established and flight constraints are analyzed firstly. Handover constraints between midcourse and terminal guidance are transformed as an optimization problem by introducing additional optimization variables in this paper. Then midcourse guidance problem can be transformed as an optimization problem with constraints. It can be solved by convex programming through constraints relaxation and linearization. In order to overcome flight uncertainty and changes of target trajectory, an online guidance framework based on convex programming is presented. But it takes some calculation time to solve the convex programming problem, which causes the delay of guidance commands. Based on sensitivity analysis of nonlinear programming, a command correction method is designed to reduce the delay effect. Besides, an adaptive update strategy of trust region in convex programming is proposed to guarantee calculation accuracy and speed. And the discrete points are continuously updated with the flight time to improve calculation efficiency. Finally, numerical simulations for different cases have demonstrated the effectiveness of the online midcourse guidance method proposed.

PREDICTING THE INFRARED UAV IMAGERY OVER THE COAST

Abstract. The infrared (IR) imagery provides additional information to the visible (red-green-blue, RGB) about vegetation, soil, water, mineral, or temperature, and has become essential for various disciplines, such as geology, hydrology, ecology, archeology, meteorology or geography. The integration of the IR sensors, ranging from near-IR (NIR) to thermal-IR through mid-IR, constitutes a baseline for Earth Observation satellites but not for unmanned airborne vehicles (UAV). Given the hyperspatial and hypertemporal characteristics associated with the UAV survey, it is relevant to benefit from the IR waveband in addition to the visible imagery for mapping purposes. This paper proposes to predict the NIR reflectance from RGB digital number predictors collected with a consumer-grade UAV over a structurally and compositionally complex coastal area. An array of 15 000 data, distributed into calibration, validation and test datasets across 15 representative coastal habitats, was used to build and compare the performance of the standard least squares, decision tree, boosted tree, bootstrap forest and fully connected neural network (NN) models. The NN family surpassed the four other ones, and the best NN model (R2 = 0.67) integrated two hidden layers provided, each, with five nodes of hyperbolic tangent and five nodes of Gaussian activation functions. This perceptron enabled to produce a NIR reflectance spatially-explicit model deprived of original artifacts due to the flight constraints. At the habitat scale, sedimentary and dry vegetation environments were satisfactorily predicted (R2 > 0.6), contrary to the healthy vegetation (R2 < 0.2). Those innovative findings will be useful for scientists and managers tasked with hyperspatial and hypertemporal mapping.

Monocular vision based obstacle avoidance trajectory planning for Unmanned Aerial Vehicle

In recent years, monocular vision has been considered as an effective Unmanned Aerial Vehicle (UAV) onboard obstacle perception solution with applications to Sense and Avoid (SAA). However, with the limitations of monocular optical measurement, monocular vision based obstacle localization ability is insufficient for collision avoidance. Therefore, an obstacle collision avoidance trajectory planning scheme is proposed in this paper with considerations of monocular optical measurement characteristic. Firstly, two obstacle localization modes are defined in this paper to assist with obstacle collision avoidance, namely relative range based Mode 1 and relative angle based Mode 2. Obstacle localization observability of Mode 2 is analyzed, and coordinate systems for obstacle localization are constructed based on the analysis results. Given coordinate systems, Orthogonal Iteration (OI) is further adopted for obstacle localization. Secondly, due to the lack of global knowledge caused by monocular vision based localization capability, a rolling horizon based safe trajectory planning method is presented. In each time segment, the trajectory is optimized with considerations of: 1) objective functions including minimum trajectory length, elapsed time and energy consumption; 2) constraints including Mode 1 and 2 based obstacle collision avoidance constrains and UAV flight constraints. Finally, simulation results indicate the proposed obstacle collision avoidance trajectory planning scheme enhances UAV safety level and can achieve favorable performance when compared with geometric based obstacle collision avoidance and collision avoidance with global knowledge.

Joint Trajectory and Scheduling Design for UAV Aided Secure Backscatter Communications

In a secure backscatter communication system, an unmanned-aerial-vehicle (UAV) operates both as a source of radio frequency (RF) signals and an information collector. Batteryless backscatter devices (BDs) exploit RF signals emitted by the UAV to upload their own information to the UAV with the existence of multiple eavesdroppers (EDs). Uplink fair-secrecy-rate of BDs is maximised by jointly designing the UAV's trajectory, the BDs' scheduling indicators and their backscattering coefficients, while achieving the energy harvesting requirements of batteryless BDs and various flight constraints of the UAV. A block coordinate descent (BCD) algorithm is developed for solving the non-convex optimisation problem. Simulation results demonstrate the substantial performance gain of our design for UAV aided secure backscatter communications.

Cooperatively pursuing a target unmanned aerial vehicle by multiple unmanned aerial vehicles based on multiagent reinforcement learning

AbstractThis article considers a pursuit‐evasion problem, in which multiple unmanned aerial vehicles (multi‐UAVs) are required to cooperatively pursue a moving target UAV. The dynamics of the three‐dimensional partially unknown environment makes it hard to deal with this problem. A multiagent reinforcement learning approach is proposed. This algorithm is extended from cooperative double Q‐learning by taking into account of the characteristics of the studied pursuit problem. To study the performance, a simulator is developed, which concerns the dynamic nature of the environment and flight constraints of UAV. Compared with several state‐of‐the‐art reinforcement learning algorithms, the proposed algorithm provides better policy such that the pursuing multi‐UAVs can effectively chase the moving target UAV.

Cooperative guidance strategy for multiple hypersonic gliding vehicles system

Cooperative guidance strategy for multiple hypersonic gliding vehicles system with flight constraints and cooperative constraints is investigated. This paper mainly cares about the coordination of the entry glide flight phase and driving-down phase. Different from the existing results, both the attack time and the attack angle constraints are considered simultaneously. Firstly, for the entry glide flight phase, a two-stage method is proposed to achieve the rapid cooperative trajectories planning, where the control signal corridors are designed based on the quasi-equilibrium gliding conditions. In the first stage, the bank angle curve is optimized to achieve the attack angle coordination. In the second stage, the angle of attack curve is optimized to achieve the attack time coordination. The optimized parameters can be obtained by the secant method. Secondly, for the driving-down phase, the cooperative terminal guidance law is designed where the terminal attack time and attack angle are considered. The guidance law is then transformed into the bank angle and angle of attack commands. The cooperative guidance strategy is summarized as an algorithm. Finally, a numerical simulation example with three hypersonic gliding vehicles is provided for revealing the effectiveness of the acquired strategy and algorithm.

Drone flight planning for safe urban operations

This paper describes the requirements of a flight planning tool for safe urban operations, which may be used to design operations considering flight constraints and limitations. This system is designed to work in coordination with an unmanned traffic management system in charge of distributing available very low level airspace resources among different operations and authorizing them, and of monitoring compliance of actual flights with flight authorizations. Representative examples of flight planning are described, as calculated by a prototype flight planning tool following this requirements.

Fixed-wing UAV guidance law for ground target over-flight tracking

This paper studies the problem of tracking a ground target for a fixed-wing unmanned aerial vehicle (UAV) based on the proposed guidance law. The algorithm ensures that a UAV continuously overflies the target whether it is fixed or moving. The requirements of the UAV flight constraints such as bounded airspeed and acceleration are considered. A Lyapunov function is constructed to prove the stability of the proposed guidance law, and parameter design criteria have been developed. Considering the fixed and moving ground targets, numerical simulations are performed to verify the feasibility and benefits of the proposed guidance algorithm.

UCAV Formation Online Collaborative Trajectory Planning Using hp Adaptive Pseudospectral Method

In this paper, a novel approach to solving the formation online collaborative trajectory planning for fixed-wing Unmanned Combat Aerial Vehicles (UCAVs) is proposed. In order to describe the problem, the formation attack process which consists of communication framework and synergy elements is analyzed. The collaborative trajectory planning model which is based on avoiding the threat zones, reducing the execution time, and accomplishing the mission combines kinematics/dynamics model of UCAV with formation relative motion model to establish the optimal control problem. The approach based on hp adaptive pseudospectral method is presented to generate formation trajectory that satisfies the collaborative constraints. When a trigger event is detected, based on the offline planning, the online collaborative trajectory replanning using rolling horizon strategy is carried out. Simulated experiments which are divided into offline scenarios and online scenarios demonstrate that the proposed approach can generate trajectories which can meet the actual flight constraints, and the results verify the feasibility and stability of the proposed approach.

Dynamic modeling and control method of a new concept wing-disk aircraft

The research aimed at a new layout wing-disk solar aircraft concept with several wings around the disc fuselage, select coordinates and variables adaptively for the new dynamic subject, and establish dynamic model, using blade element momentum theory and CFD value for correction. Design the flight control strategy and controller constraint relations, put forward the method of control allocation and manipulation, and use nonlinear dynamic inversion control method aimed at the transverse and longitudinal coupling, serious nonlinear characteristics, and adds integral element as a robust dynamic inverse control to deal with the poor performance of previous method, and simulate to validate the control design.

Rapid generation of entry trajectory with multiple no-fly zone constraints

An entry trajectory planning algorithm that generates flyable trajectories satisfying multiple no-fly zones and other path and terminal constraints is presented. The algorithm divides the entry trajectory into initial and glide phases. In the initial phase, the maximum value of heating rate is controlled accurately as the altitude of the quasi-equilibrium glide condition (QEGC) transition point is adjusted with a nominal angle of attack and a parameterized bank angle. In the glide phase, a geometry based planning algorithm that relies on the center positions and radius of the multiple no-fly zones, is proposed to calculate the waypoints of the virtual flight path. The magnitude and reversal point of the bank angle in each sub-phase are searched based on a reduced-order lateral system with the predictor-corrector method. The altitude is designed as an analytical function of energy, and the QEGC is employed to analytically solve the remaining state variables. Finally, a linear quadratic regulator is used to test the realization of the 3D trajectory. The algorithm is tested using the common aero vehicle-H model. The results demonstrate that the algorithm can rapidly generate the entry trajectory with multiple no-fly zone constraints and achieve complex flight missions satisfying all flight constraints.

Ground Target Tracking Guidance Law for Fixed-Wing Unmanned Aerial Vehicle: A Search and Capture Approach

One important problem for unmanned aerial vehicles (UAVs) in mission applications is to track ground targets automatically. A major concern is how to keep the tracking process stable and efficient while the motion of the ground targets changes rapidly. In this brief, a new guidance strategy for the ground target “Search and Capture” based on a virtual target is proposed. First, a virtual trajectory, which is composed of straight lines and arcs, is generated based on the motion of the target. The straight lines are used to capture, while the arcs are used to search, and switch between straight line and arc when some condition is met; second, we design a new guidance law based on line-of-sight (LOS) which makes a UAV to track the virtual target automatically. This new method solves the following three problems simultaneously: (1) The UAV always keeps a constant speed to track the target with changing velocity, (2) the generated trajectory meets the flight constraints of the UAV, and (3) the speed range of the ground target can be from the stationary to almost the maximum cruising speed of the UAV. Simulation results show that the proposed guidance strategy can achieve stable tracking for various motions of the ground target.

A robust predictor–corrector entry guidance

With the development of aerospace industry, the guidance system of an entry vehicle becomes more robust, reliable and autonomous. Based on fuzzy logic, a predictor–corrector guidance law is proposed in this paper, where the trajectory prediction is realized by numerical integration. The correction system consists of two fuzzy controllers, which correct longitudinal motion and lateral motion synergistically. A drag acceleration profile is designed through interpolating between upper drag boundary and lower drag boundary, which is corrected continually to eliminate the range error. Attack angle, a secondary control variable in the paper, is used to eliminate the altitude error. In addition, the lateral error is removed by regulating the reversal time of bank angle. Compared with the traditional guidance laws, the method in this paper not only can correct synergistically the longitudinal motion and lateral motion of the vehicle, but also can easily cope with the flight constraints using interpolated drag acceleration profile. Moreover, in a correction cycle, the method designed in this paper only needs a single trajectory prediction, which reduces the on-board computation. The guidance law demonstrates a high precision and robustness in the simulation scenario.

Qualification campaign of the 50 mK hybrid sorption-ADR cooler for SPICA/SAFARI

SAFARI (SpicA FAR-infrared Instrument) is an infrared instrument planned to be part of the SPICA (SPace Infrared telescope for Cosmology and Astrophysics) Satellite. It will offer high spectral resolution in the 30 - 210 μm frequency range. SAFARI will benefit from the cold telescope of SPICA and to obtain the required detectors sensitivity, a temperature of 50 mK is required. This temperature is reached thanks to the use of a hybrid sorption - ADR (Adiabatic Demagnetization Refrigerator) cooler presented here. This cooler provides respectively 14 μW and 0.4 μW of cooling power at 300 mK and 50 mK. The cooler is planned to advantageously use two thermal interfaces of the instrument at 1.8 and 4.9 K. One of the challenges discussed in this paper is the low power available at each intercept. A dedicated laboratory electronic is being designed based on previous development with a particular focus on the 50 mK readout. Temperature regulation at 50 mK is also discussed. This cooler has been designed following flight constraints and will reach a high TRL, including mechanical and environmental tests at the end of the on-going qualification campaign.

Nonlinear model predictive controller robustness extension for unmanned aircraft

Purpose – Nonlinear model predictive control (NMPC) is emerging as a way to control unmanned aircraft with flight control constraints and nonlinear and unsteady aerodynamics. However, these predictive controllers do not perform robustly in the presence of physics-based model mismatches and uncertainties. Unmodeled dynamics and external disturbances are unpredictable and unsteady, which can dramatically degrade predictive controllers’ performance. To address this limitation, the purpose of this paper is to propose a new systematic approach using frequency-dependent weighting matrices. Design/methodology/approach – In this framework, frequency-dependent weighting matrices jointly minimize closed-loop sensitivity functions. This work presents the first practical implementation where the frequency content information of uncertainty and disturbances is used to provide a significant degree of robustness for a time-domain nonlinear predictive controller. The merit of the proposed method is successfully verified through the design, coding, and numerical implementation of a robust nonlinear model predictive controller. Findings – The proposed controller commanded and controlled a large unmanned aerial system (UAS) with unsteady and nonlinear dynamics in the presence of environmental disturbances, measurement bias or noise, and model uncertainties; the proposed controller robustly performed disturbance rejection and accurate trajectory tracking. Stability, performance, and robustness are attained in the NMPC framework for a complex system. Research limitations/implications – The theoretical results are supported by the numerical simulations that illustrate the success of the presented technique. It is expected to offer a feasible robust nonlinear control design technique for any type of systems, as long as computational power is available, allowing a much larger operational range while keeping a helpful level of robustness. Robust control design can be more easily expanded from the usual linear framework, allowing meaningful new experimentation with better control systems. Originality/value – Such algorithms allows unstable and unsteady UASs to perform reliably in the presence of disturbances and modeling mismatches.

Maneuver characteristics analysis for hypersonic glide vehicles

The maneuver characteristics of hypersonic glide vehicles are analyzed from the perspectives of maneuver modes and maneuverability in this paper. Longitudinal skip maneuver mode, equilibrium glide mode, lateral weaving maneuver mode and lateral turning maneuver mode are adopted to describe the maneuver process of hypersonic glide vehicles from the view of shapes of maneuver trajectories, and the corresponding control variables in each mode are deduced. Flight constraints including heating rate, aerodynamic press, load factor are converted to be constraints putting on angle of attack to validate whether the vehicle can realize the assigned maneuver. In addition, some performance indices to evaluate the maneuverability are analyzed in. The study in the paper can help to deepen the understanding of the maneuver characteristics of hypersonic glide vehicles and provide guide to trajectory planning and optimization.