Aircraft Guidance Research Articles

Finite-Time Guidance and Control for Uncrewed Receiver Aircraft in Aerial Refueling Rendezvous

Finite-Time Guidance and Control for Uncrewed Receiver Aircraft in Aerial Refueling Rendezvous

Guidance algorithm for reusable launch vehicle considering change in target

To address the design challenges of reentry guidance for high-speed aircraft in complex environments, and in response to the need for target adjustments during reentry, a method for designing reentry guidance laws with extended range has been introduced. The longitudinal guidance law has significantly improved real-time performance by converting infinite-dimensional optimization into a single-parameter search using the reentry flight corridor approach. The lateral guidance law employs line-of-sight angular deviation corridors to achieve target tracking, while the extended-range guidance law rapidly increases the flight distance of the reusable launch vehicle during the flight by optimizing attack angle profiles. Numerical simulations have been conducted to validate the effectiveness of the longitudinal, lateral, and extended-range guidance laws, indicating that they can meet the mission requirements for target adjustments during reentry.

Study of the wear process in an experimental simulation of a fuselage/runway rubbing contact

In this work, the authors tackle the problem of laboratory simulation of frictional contact in wheels-up emergency landing conditions. To design a novel tribometer simulating the contact between an aircraft structure and a runway, one must carry two complementary main tasks: the understanding of the underlying physical mechanisms and the scaling up of the in-lab results to the scale of interest. The authors propose to progress on the first task by conducting exploratory work using existing resources. Their contribution consists of a multi-scale methodology to reconstruct the wear process in a tribological system within wheels-up emergency landing conditions. This could provide guidance for safer aircraft and runway design. The study falls within the framework of three-body tribology. The proposed multi-scale characterisation methodology is made up of four steps. After describing the whole tribological system, its mechanical response is measured and analysed. This measurement is complemented by surface observations and physicochemical analyses. Finally, all the measurements and observations are discussed to come across a phenomenological wear scenario that revealed friction and wear as system responses with the key role of the third body.

Hamiltonian Neural Network 6-DoF Rigid-Body Dynamic Modeling Based on Energy Variation Estimation

This study introduces a novel deep modeling approach that utilizes Hamiltonian neural networks to address the challenges of modeling the six degrees of freedom rigid-body dynamics induced by control inputs in various domains such as aerospace, robotics, and automotive engineering. The proposed method is based on the principles of Hamiltonian dynamics and employs an inductive bias in the form of a constructed bias for both conservative and varying energies, effectively tackling the modeling issues arising from time-varying energy in controlled rigid-body dynamics. This constructed bias captures the information regarding the changes in the rigid body’s energy. The presented method not only achieves highly accurate modeling but also preserves the inherent bidirectional time-sliding inference in Hamiltonian-based modeling approaches. Experimental results demonstrate that our method outperforms existing techniques in the time-varying six degrees of freedom dynamic modeling of aircraft and missile guidance, enabling high-precision modeling and feedback correction. The findings of our research hold significant potential for the kinematic modeling of time-varying energy systems, parallel system state prediction and control, inverse motion inference, and autonomous decision-making in military applications.

Application of Severe Weather Nowcasting to Case Studies in Air Traffic Management

Effective and time-efficient aircraft assistance and guidance in severe weather environments remains a challenge for air traffic control. Air navigation service providers around the globe could greatly benefit from specific and adapted meteorological information for the controller position, helping to reduce the increased workload induced by adverse weather. The present work proposes a radar-based nowcasting algorithm providing compact meteorological information on convective weather near airports for introduction into the algorithms intended to assist in air-traffic management. The use of vertically integrated liquid density enables extremely rapid identification and short-term prediction of convective regions that should not be traversed by aircraft, which is an essential requirement for use in tactical controller support systems. The proposed tracking and nowcasting method facilitates the anticipation of the meteorological situation around an airport. Nowcasts of centroid locations of various approaching thunderstorms were compared with corresponding radar data, and centroid distances between nowcasted and observed storms were computed. The results were analyzed with Method for the Object-Based Evaluation from the Model Evaluation tools software (MET-10.0.1, Developmental Testbed Center, Boulder, CO, US) and later integrated into an assistance arrival manager software, showing the potential of this approach for automatic air traffic assistance in adverse weather scenarios.

Study on the practical method implementation of the navigation equations in a simulated FMS

This paper presents the main objective of Air Traffic Management Systems – ATMS that is to achieve optimized performance in terms of aviation safety and the enhancement of the current air transport system, through the in-depth study of the complex integration of all advanced technologies regarding air traffic monitoring, aeronautical communications on-board computers, display and control systems within the extended framework of Air Traffic Services - ATS. The Flight Management System - FMS is indispensable for flight planning, air navigation, flight performance management, aircraft guidance on the flight path and continuous monitoring of the progress during flight. The FMS is the device used by the flight crew to select various modes of flight control via the flight control computer - FCM and to display flight plans and other flight data via the Multi-Functional Control Display Unit - MCDU. The flight path is monitored by the MCDU and the Electronic Instrument System – EIS. The in-depth study of Air Transport Efficiency when applying air traffic service operational analysis and trajectory determination methods to identify key areas of Air Traffic Management inefficiencies and to prioritize and implement appropriate optimization methods are presented and analyzed in detail in this paper.

Interacting Multiple Model Filtering for Aircraft Guidance Modes Identification from Surveillance Data

Accurate and reliable trajectory prediction (TP) is required in several air traffic management systems. Estimating the aircraft trajectory in a vertical plane typically requires the knowledge of a pair of operational instructions. A sequence of operational instructions specifies the aircraft intent, information that is seldom available, besides for the ownship trajectory planning system. In the execution of the trajectory, the aircraft is directed by the (auto)pilot through a series of sequential guidance modes that might override some of the planning instructions of the aircraft intent. Therefore, having reliable guidance mode information is fundamental for the next generation of air- or ground-based TP. The main goal of this contribution is to develop a methodology able to identify in real-time the active guidance modes for both vertical climb and descent profiles, using only Automatic Dependent Surveillance-Broadcast and Enhanced Mode-S Surveillance data. The proposed solution is based on an interacting multiple model (IMM) filtering approach, which uses a bank of filters, each one matched to a possible guidance mode. The guidance mode identification performance of the IMM-based solution is validated with i) a set of simulated representative trajectories and ii) real flight data obtained from flight data recorders.

High-Precision Aircraft Guidance System with Axial Acceleration Self-Tuning

Creation of aircraft control systems that provide high quality guidance is an urgent task associated with increasing efficiency of the modern missile systems. Classical autonomous guidance systems without integration with any other external correction systems are making it impossible to ensure high-precision target engagement. An approach based on the use of adaptive guidance system is proposed. Besides, an approach to synthesis and analysis of the self-tuning aircraft control system that implements terminal homing is illustrated. A technique for forming the control system structure is presented ensuring the control quality constant level in all operating modes due to self-tuning of the constituent elements variable coefficients. Structural schemes and control equations were determined to correct the aircraft flight. Implementation of the developed technique on board the aircraft is proposed determining relationship between the aircraft control system parameters and the apparent acceleration. Adaptive system operation is demonstrated on a typical model of the aircraft flying in the atmosphere with guidance at the stationary target. Results of numerical simulation are presented, and high efficiency of the developed technique is revealed

A Policy-Reuse Algorithm Based on Destination Position Prediction for Aircraft Guidance Using Deep Reinforcement Learning

Artificial intelligence for aircraft guidance is a hot research topic, and deep reinforcement learning is one of the promising methods. However, due to the different movement patterns of destinations in different guidance tasks, it is inefficient to train agents from scratch. In this article, a policy-reuse algorithm based on destination position prediction is proposed to solve this problem. First, the reward function is optimized to improve flight trajectory quality and training efficiency. Then, by predicting the possible termination position of the destinations in different moving patterns, the problem is transformed into a fixed-position destination aircraft guidance problem. Last, taking the agent in the fixed-position destination scenario as the baseline agent, a new guidance agent can be trained efficiently. Simulation results show that this method can significantly improve the training efficiency of agents in new tasks, and its performance is stable in tasks with different similarities. This research broadens the application scope of the policy-reuse approach and also enlightens the research in other fields.

Anti-Interception Guidance for Hypersonic Glide Vehicle: A Deep Reinforcement Learning Approach

Anti-interception guidance can enhance a hypersonic glide vehicle (HGV) compard to multiple interceptors. In general, anti-interception guidance for aircraft can be divided into procedural guidance, fly-around guidance and active evading guidance. However, these guidance methods cannot be applied to an HGV’s unknown real-time process due to limited intelligence information or on-board computing abilities. In this paper, an anti-interception guidance approach based on deep reinforcement learning (DRL) is proposed. First, the penetration process is conceptualized as a generalized three-body adversarial optimal (GTAO) problem. The problem is then modelled as a Markov decision process (MDP), and a DRL scheme consisting of an actor-critic architecture is designed to solve this. Reusing the same sample batch during training results in fewer serious estimation errors in the critic network (CN), which provides better gradients to the immature actor network (AN). We propose a new mechanismcalled repetitive batch training (RBT). In addition, the training data and test results confirm that the RBT can improve the traditional DDPG-based-methodes.

Rocket landing guidance using convex optimization and proportional navigation considering performance-limited engine

In recent years, convex optimization has been widely applied in aircraft trajectory optimization and guidance. For rocket vertical landing, the dynamics are highly nonlinear, which easily causes convergence issues in convex optimization. Moreover, for the existing convex optimization methods, it is difficult to implement landing guidance with a performance-limited engine in which the thrust cannot be continuously and instantly regulated. To address these two issues, a novel rocket vertical landing guidance method is developed, in which the guidance in the normal and tangential planes with respect to the rocket velocity is separated to enhance the convergence property of convex optimization. Normal guidance adopts biased proportional navigation to easily satisfy the pinpoint landing with the required attitude angles. For tangential guidance, convex optimization and model predictive control are employed to optimize the thrust command that satisfies the landing velocity limit. Based on this, an impulse equivalent transformation method is designed to derive thrust commands that satisfy the engine limits. Simulation results indicate that the proposed guidance method can achieve precise landing and satisfy various constraints while being highly robust to uncertainties. Moreover, the efficiency, convergence property, and control smoothness are significantly improved.

Experimental strapdown inertial navigation system for the autonomous guidance system of a short-range uav

The task of experimental verification of the possibility of using a miniature strapdown inertial navigation system (SINS) on micromechanical sensors for autonomous guidance of a short-range manned aircraft moving along a programmed hypothetical trajectory is considered.
 A mathematical model of the first approximation of the instrumental errors of the two-coordinate autonomous SINS of the aircraft with a short flight time was obtained. The mathematical model allows both to calculate the values of these errors for specific types of inertial sensors used in SINS (direct analysis problem), and to choose the types of accelerometers and gyroscopes based on ensuring the given accuracy of SINS (inverse synthesis problem). The requirements for permissible errors of accelerometers and gyroscopes of the SINS sensor unit have been determined.
 The design and manufacturing technology of an experimental SINS based on a triaxial micromechanical accelerometer and three uniaxial micromechanical gyroscopes are described.
 The technology of flight tests of the experimental SINS is considered. The test results of the experimental SINS of the aircraft, created in accordance with the requirements specified in the article, confirmed the correctness of the chosen approach to ensuring the accuracy of the SINS for the autonomous inertial guidance system of short-range aircraft.

Method of Obtaining a Control Low Using a Synergetic Approach for the Problem of Aircraft Guidance Along a Hyperbola

The purpose of the article is to describe the methodology for obtaining the structure of the optimal controller, which guidances the aircraft to the target point along a hyperbola, using the Time Difference of Arrivals (TDoA) from two navigation positions on the plane. A feature of this system is that one TDoA measurement does not allow to fully describe the position of the aircraft on the plane, but only describes the position hyperbola. The guidance problem is solved by choosing a proper hyperbola passing through the target point and letting the aircraft move along this hyperbola to the target. This paper considers the application of the method of synthesis of an aggregated controller to obtain a nonlinear guidance law. This made it possible to take into account the properties of the control object to a larger extent. Computer simulation has shown the effectiveness of the expressions obtained.

Procedure of the Synthesis of Control Device by the Method of Analytical Design of the Optimal Regulator for the Problem of Aircraft Guidance Along a Hyperbola

The purpose of the article is to describe the methodology for obtaining the structure of the optimal controller, which provides the guidance of the aircraft to the target point on the plane, using the method of time difference of arrivals (TDoA) for two navigation positions. The main feature of the system is that one measurement of time difference of arrivals between the aircraft and two navigation positions does not allow to describe the position of the aircraft on the plane fully. It describes only the line of position (LOP) in the form of a hyperbola. The aiming problem is solved by choosing a hyperbola passing through the target point, bringing the aircraft to a given hyperbola, followed by its movement along this hyperbola. In this case, the choice of the target hyperbola is a trivial task, in contrast to the task of determining the structure of the control system implementing the right and effective guidance law. The regulator obtained on the basis of the method of analytical design of the optimal regulator, according to the results of the computer simulation, showed its operability.

High-Precision Aircraft Guidance System Based on Dual-Optical Frequency Combs: Accurate Autonomous Landing of Drones

High-Precision Aircraft Guidance System Based on Dual-Optical Frequency Combs: Accurate Autonomous Landing of Drones

Robust Adaptive Neural Cooperative Control for the USV-UAV Based on the LVS-LVA Guidance Principle

Around the cooperative path-following control for the underactuated surface vessel (USV) and the unmanned aerial vehicle (UAV), a logic virtual ship-logic virtual aircraft (LVS-LVA) guidance principle is developed to generate the reference heading signals for the USV-UAV system by using the “virtual ship” and the “virtual aircraft”, which is critical to establish an effective correlation between the USV and the UAV. Taking the steerable variables (the main engine speed and the rudder angle of the USV, and the rotor angular velocities of the UAV) as the control input, a robust adaptive neural cooperative control algorithm was designed by employing the dynamic surface control (DSC), radial basic function neural networks (RBF-NNs) and the event-triggered technique. In the proposed algorithm, the reference roll angle and pitch angle for the UAV can be calculated from the position control loop by virtue of the nonlinear decouple technique. In addition, the system uncertainties were approximated through the RBF-NNs and the transmission burden from the controller to the actuators was reduced for merits of the event-triggered technique. Thus, the derived control law is superior in terms of the concise form, low transmission burden and robustness. Furthermore, the tracking errors of the USV-UAV cooperative control system can converge to a small compact set through adjusting the designed control parameters appropriately, and it can be also guaranteed that all the signals are the semi-global uniformly ultimately bounded (SGUUB). Finally, the effectiveness of the proposed algorithm has been verified via numerical simulations in the presence of the time-varying disturbances.

Robust Time-Delayed PID Flight Control for Automatic Landing Guidance under Actuator Loss-Of-Control

A robust fault-tolerant flight control scheme using a Time-Delayed PID (TD-PID) control law for automatic landing guidance of a fixed-wing aircraft under successive actuator faults is presented in this paper. The desired landing trajectory is translated into attitude reference commands, and a PID control law in discrete-time form within a Time-Delay Control (TDC) framework is synthesized into a TD-PID control for aircraft attitude command tracking control system. The robustness property of TDC towards parametric uncertainties in the system is exploited in this work in developing a fault-tolerant flight control framework to passively to mitigate the effects of partial loss-of-control during the landing phase of the aircraft.

Energy-optimal trajectory planning for solar-powered aircraft using soft actor-critic

High-Altitude Long-Endurance (HALE) solar-powered Unmanned Aircraft Vehicles (UAVs) can utilize solar energy as power source and maintain extremely long cruise endurance, which has attracted extensive attentions from researchers. Trajectory optimization is a promising way to achieve superior flight time because of the finite solar energy absorbed in a day. In this work, a method of trajectory optimization and guidance for HALE solar-powered aircraft based on a Reinforcement Learning (RL) framework is introduced. According to flight and environment information, a neural network controller outputs commands of thrust, attack angle, and bank angle to realize an autonomous flight based on energy maximization. The validity of the proposed method was evaluated in a 5-km radius area in simulation, and results have shown that after one day-night cycle, the battery energy of the RL-controller was improved by 31% and 17% compared with those of a Steady-State (SS) strategy with a constant speed and a constant altitude and a kind of state-machine strategy, respectively. In addition, results of an uninterrupted flight test have shown that the endurance of the RL controller was longer than those of the control cases.

Methods for Aircraft Guidance with Changes in Control Priorities

Methods for Aircraft Guidance with Changes in Control Priorities

A Multi-Dimensional Goal Aircraft Guidance Approach Based on Reinforcement Learning with a Reward Shaping Algorithm.

Guiding an aircraft to 4D waypoints at a certain heading is a multi-dimensional goal aircraft guidance problem. In order to improve the performance and solve this problem, this paper proposes a multi-layer RL approach. The approach enables the autopilot in an ATC simulator to guide an aircraft to 4D waypoints at certain latitude, longitude, altitude, heading, and arrival time, respectively. To be specific, a multi-layer RL approach is proposed to simplify the neural network structure and reduce the state dimensions. A shaped reward function that involves the potential function and Dubins path method is applied. Experimental and simulation results show that the proposed approach can significantly improve the convergence efficiency and trajectory performance. Furthermore, the results indicate possible application prospects in team aircraft guidance tasks, since the aircraft can directly approach a goal without waiting in a specific pattern, thereby overcoming the problem of current ATC simulators.