The range of small, electrically powered UAVs is still limited by the mass specific energy of batteries. This paper investigates the idea that, in cases where multiple aircraft must transit to the same location, savings in mass or an extension of achievable range are possible when they join wingtip-to-wingtip. The viability of joined flight is investigated by quantifying the relative magnitude of savings resulting from increased aerodynamic efficiency and that of penalties due to the increased structural and component weights. Through a parametric analysis the level of savings achievable is found to be greatly dependent on the proportion of the flight spent in a joined configuration and aircraft design parameters such as wing loading, aspect ratio and the added weight of the joining mechanism. A custom, multidisciplinary UAV sizing algorithm is presented and utilised to design several sample aircraft, featuring two different joining mechanism architectures. The results verify the findings of the parametric study and indicate that mass savings are possible only for moderate to low aspect ratios, with semi-permanent magnetic joining mechanism performing better than rigid structural ones, even when the joined fight segment accounts for only 30% of the total airborne time.

A smooth adaptive sliding-mode-based controller is developed for BTT missiles considering nonlinear couplings and aerodynamic uncertainties, wherein fixed-time stability theory is synthesised into sliding-mode control algorithm, such that control variables follow the desired command within fixed-bounded convergence time. Unlike other terminal sliding-mode-related works, the bound of settling time is independent of initial states, indicating that performance metrics, for instance the convergence rate, can be evaluated in advance. The control input is designed to be intrinsically smooth, based on adaptive estimations, and therefore the problem of singularity and chattering is effectively eliminated. Simulation results demonstrate the satisfactory performance and validate the effectiveness of the designed approach.

This article presents a potential analytic redundancy approach to detect faults in the air data sensor of an aircraft. In modern aircraft, fault detection of air data sensors is performed using a complex voting mechanism, which requires the availability of redundant air data sensor in all situations. However, to continuously monitor operation and performance of these sensors, the analytic redundancy-based air data estimation and fault detection is highly preferred than estimation with air data probe measurements. The proposed algorithm uses the kinematics of aircraft to estimate air data and detect air data sensor fault. In this paper, a simple mathematical model is developed, which does not consider the forces and moments acting on aircraft and uses measurements only from the Inertial Measurement Unit (IMU) and Navigation System Data (NSD). In order to implement this approach, the Iterated Optimal Extended Kalman Filter (IOEKF) is developed to estimate air data, which provides an accurate and stable estimation. With the estimated states, the physical air data sensor measurements are compared and the residual is calculated to track each sensor performance and to detect the occurrence of a fault. The key advantage of this approach is that it does not require complex dynamic equations and is free from system uncertainties. The proposed algorithm is simulated in MATLAB software using flight simulator flight data and validated using the real-time flight data of Cessna Citation II transport aircraft.

Aiming at the issue of missiles attacking on-ground maneuvering targets in three-dimensional space, a three-dimensional finite-time guidance law with impact-angle constraints is proposed. In order to improve convergence speed and restrain chattering phenomenon, the nonsingular fast terminal three-dimensional second-order sliding mode guidance law with coupling terms is designed based on the theory of nonhomogeneous fast terminal sliding surface and second-order sliding mode control. The system model need not be linearized during the design process, and the singular problem is avoided. A nonhomogeneous disturbance observer is designed to estimate and compensate the total disturbance, which is caused by target maneuvering information and coupling terms of line of sight. And the stability and finite-time convergence of the guidance law are proved strictly and mathematically. Finally, simulation results have verified the effectiveness and superiority of the proposed guidance law.

This paper considers actuator redundancy management for a redundant multirotor Unmanned Aerial Vehicle (UAV) under actuators failures. Different approaches are proposed: using robust control (passive fault tolerance), and reconfigurable control (active fault tolerance). The robust controller is designed using high-order super-twisting sliding mode techniques, and handles the failures without requiring information from a Fault Detection scheme. The Active Fault-Tolerant Control (AFTC) is achieved through redistributing the control signals among the healthy actuators using reconfigurable multiplexing and pseudo-inverse control allocation. The Fault Detection and Isolation problem is also considered by proposing model-based and model-free modules. The proposed techniques are all implemented on a coaxial octorotor UAV. Different experiments with different scenarios were conducted for the validation of the proposed strategies. Finally, advantages, disadvantages, application considerations and limitations of each method are examined through quantitative and qualitative studies.

The prime focus of this work is to estimate stability and control derivatives of an airship in a completely nonlinear environment. A complete six degrees of freedom airship model has its aerodynamic model as nonlinear functions of angle of attack. Estimating the parameters of aerodynamic model in a nonlinear environment is challenging as it demands an exhaustive dataset that could cover the entire regime of operation of airship. In this work, data generation is achieved by simulating the mathematical model of airship for different trim conditions obtained from continuation analysis. The mathematical model is simulated using predicted parameter values obtained using DATCOM methodology. A modular neural network is then trained using back-propagation and Adam optimisation algorithm for each of the aerodynamic coefficients separately. The estimated nonlinear airship parameters are found to be consistent with the DATCOM parameter values which were used for open-loop simulation. This validates the proposed methodology and could be extended to estimate airship parameters from real flight data.

This paper has proposed a new robust hybrid nonlinear guidance law, which accounts for a missile’s terminal line-of-sight (LOS) angle constraint, in order to intercept a non-cooperative maneuvering target. The proposed hybrid nonlinear guidance strategy consists of two phases; in the first phase, a guidance law named PIGL is derived from prescribed performance control and the inertial delay control method. In PIGL, a revised prescribed performance function is put forward, and a prescribed performance controller with unknown uncertainties is then derived. The controller smoothly drives both the LOS angle and its rate to a predesigned small region under unknown uncertainties that are induced by target’s maneuvers within a fixed time. Then, a guidance law named SIGL is activated, which is derived from sliding mode control and inertial delay control. By driving the desired sliding mode variable to zero within a finite time, the SIGL guidance law is able to achieve high terminal interception accuracy. The robustness of both of the proposed sub-guidance laws has been proved explicitly in this paper. The hybrid guidance law has the advantage of a tunable convergence rate of the LOS angle and the rate of the LOS angle at the beginning period, by which an excessive large initial maneuver can be avoided. Meanwhile, the hybrid guidance law also has the advantage of lower sensitivity to errors in the estimation of the time-to-go.