Flight Dynamics Research Articles

Automatic autopilot tuning framework using genetic algorithms and system identification

This paper presents a comprehensive framework for offline optimization of tuning parameters in unmanned aerial vehicle (UAV) flight controllers. The framework uses system identification to create a simplified flight dynamics model, followed by control law matching to ensure the simulated controller's output closely replicates real-world autopilot commands. The optimization phase employs genetic algorithms to tune parameters based on a defined cost function that incorporates performance requirements. Each stage, from flight dynamics model development to optimization, is validated to ensure enhanced controller performance. Finally, real-world flight tests confirm the effectiveness of the optimized controller, demonstrating the validity of the proposed framework for autopilot tuning optimization.

Unsteady aerodynamic modeling and flight trajectory simulation of dual-spin projectile based on DNN and transfer-learning

To evaluate flight performance and aerodynamic characteristics of a dual-spin projectile, the coupled computational fluid dynamics and rigid body dynamics (CFD/RBD) method is commonly used, which can simultaneously solve the flight mechanics and flow field. However, the efficiency is compromised by the large number of CFD calculations required. This paper develops an unsteady aerodynamic modeling method that combines deep neural networks and transfer learning, which can accurately predict unsteady aerodynamics of dual-spin projectiles under varying initial conditions. Considering the influence of flight state and aerodynamic data from short-term historical moments, we integrate them as input features of the aerodynamic model to reduce the impact of long-term historical data. To enhance the model generalization under varying initial conditions, we fine-tune the built aerodynamic model using small amounts of data under new conditions by transfer learning. The proposed method is validated through interpolated and extrapolated prediction cases, respectively. The results indicate that the proposed method can achieve better accuracy and generalizability than long short-term memory neural networks and autoregressive moving average method in unsteady aerodynamic modeling of the dual-spin projectile. By coupling the flight dynamics equations with the aerodynamic model in the time domain, the flight simulation only takes a few seconds, which can reduce computing time by three orders of magnitude compared to the coupled CFD/RBD method.

Implementation of Control Valves System on Microturbine Drone’s Rotational Motion

The drone technology has received a wide range of research focusing on improving flight dynamics, battery life, payload capacity and sensor technology. However, for the applications of using drone for high rise buildings are limited by battery life for longer flight with longer duration tasks. This work presents the implementation of a control valve systems for the rotational motion of a microturbine drone. The first objective of this project was to design and develop a control valve system for a microturbine with propeller. The second objective was to measure micro turbine’s performance output which consisted of revolution per minute (rpm) and voltage (V) produced with the control valves system. The final objective was to verify the effectiveness of the control valve system by measuring the differences of the turbine speed of each turbine on the quadcopter to conceptually control the rotational motion of the drones. In conclusion, this work demonstrated the concept of the developed control valve system that can control the rotational motion of the drone.

An Innovative Applied Control System of Helicopter Turboshaft Engines Based on Neuro-Fuzzy Networks

This study focuses on helicopter turboshaft engine innovative fault-tolerant fuzzy automatic control system development to enhance safety and efficiency in various flight modes. Unlike traditional systems, the proposed automatic control system incorporates a fuzzy regulator with an adaptive control mechanism, allowing for dynamic fuel flow and blade pitch angle adjustment based on changing conditions. The scientific novelty lies in the helicopter turboshaft engines distinguishing separate models and the fuel metering unit, significantly improving control accuracy and adaptability to current flight conditions. During experimental research on the TV3-117 engine installed on the Mi-8MTV helicopter, a parametric modeling system was developed to simulate engine operation in real time and interact with higher-level systems. Innovation is evident in the creation of the failure model that accounts for dynamic changes and probabilistic characteristics, enabling the prediction of failures and minimizing their impact on the system. The results demonstrate high effectiveness for the proposed model, achieving an accuracy of 99.455%, while minimizing the loss function, confirming its reliability for practical application in dynamic flight conditions.

Evidence of Directional Structural Superlubricity and Lévy Flights in a van der Waals Heterostructure.

Structural superlubricity is a special frictionless contact in which two crystals are in incommensurate arrangement such that relative in-plane translation is associated with vanishing energy barrier crossing. So far, it has been realized in multilayer graphene and other van der Waals (2D crystals with hexagonal or triangular crystalline symmetries, leading to isotropic frictionless contacts. Directional structural superlubricity, to date unrealized in 2D systems, is possible when the reciprocal lattices of the two crystals coincide in one direction only. Here, directional structural superlubricity a α-bismuthene/graphite van der Waals system is evidenced, manifested by spontaneous hopping of the islands over hundreds of nanometers at room temperature, resolved by low-energy electron microscopy and supported by registry simulations. Statistical analysis of individual and collective α-bismuthene islands populations reveal a heavy-tailed distribution of the hopping lengths and sticking times indicative of Lévy flight dynamics, largely unobserved in condensed-mattersystems.

Application of PID Control Technology in Unmanned Aerial Vehicles

Abstract. The rapid advancement of unmanned aerial vehicle (UAV) technology underscores the essential role of PID (proportional-integral-derivative) control in ensuring flight stability, particularly through precise motor speed adjustments. Thus, this paper systematically analyzes the fundamental principles and limitations of traditional PID control, further highlighting its insufficient adaptability to dynamic external conditions, which includes load fluctuations and wind disturbances. In response to these challenges, it explores adaptive control strategies such as self-tuning PID and fuzzy logic PID, points out how these advanced methods can effectively improve flight stability by dynamically adjusting control parameters, and demonstrates their superiority over traditional PID through comparative analysis. In addition, the paper anticipates future developments in UAV control systems, thereby emphasizing the integration of artificial intelligence and machine learning technologies into PID control. And this integration seeks to optimize control strategies and markedly enhance the autonomous decision-making capabilities and adaptability of UAVs. Meanwhile, the paper also predicts the development trend of hybrid control systems, that is, combining PID with other advanced control methods (such as linear quadratic control) to enhance the overall control capabilities of UAVs. In short, it underscores the necessity for continuous innovation and in-depth research in response to the dynamic flight environment and the diverse mission requirements.

Mathematical modeling of an articulated flying vehicle for precise control analysis in grasping highly oscillatory objects

In this research work, a detailed mathematical modeling approach has been taken in order to develop a complete package for the investigation of phenomena associated with the flight dynamics and control of an articulated aerial robot in grasping high weight oscillatory objects such as living creatures. To this end, the origin of forces and moments generated by a moving target is analyzed and the nonlinear differential equations of the system are derived. Then, the model is verified and the effect of target oscillations on the whole system dynamics is investigated. In the next step, due to the nonlinear nature of this under-actuated system and the presence of the force-generating target with unknown dynamics and model parametric and non-parametric uncertainties, two versions of adaptive sliding mode control (A-SMC) are designed to enable the system follows the nominal trajectories in a desirable way without needing to know the upper bounds of the time-varying forces and uncertainties. In this regard, the stability of closed-loop systems is proved based on Lyapunov theory. The performance and robustness of the designed controllers are evaluated and compared through numerical and Monte Carlo simulations with some standard criteria. At the end, the conclusion of this work is presented.

Numerical Modeling, Trim, and Linearization of a Side-by-Side Helicopter in Hovering Conditions

In the present paper, a flight dynamics model is adopted to represent the trim and stability characteristics of a side-by-side helicopter in hovering conditions. This paper develops a numerical representation of the rotorcraft behavior and proposes a set of guidelines for trimming and linearizing the highly coupled rotor dynamics derived by the modeling approach. The trim algorithm presents two nested loops to compute a solution of the steady-state conditions averaged around one blade’s revolution. On the other hand, a 38-state-space linear representation of the helicopter and rotor dynamics is obtained to study the effects of flap, lead–lag, and inflow on the overall stability. The results are compared with an analytical framework developed to validate the rotorcraft stability and compare different modeling approaches. The analysis showed that non-uniform inflow modeling led to a coupled longitudinal inflow–phugoid mode which made the vehicle prone to dangerous instabilities. The flap and lead–lag dynamics introduced damping in the system and can be considered beneficial for rotor dynamics.

Modeling and Transition Flight Control of Distributed Propulsion–Wing VTOL UAV with Induced Wing Configuration

The integration of propulsion and wing in distributed propulsion–wing UAVs (DPW UAVs) introduces significant propulsion-aerodynamic coupling, complicating dynamic modeling and flight control. This complexity is heightened by using induced wing surfaces for vertical takeoff and landing, requiring controllers to adapt to configuration changes and disturbances during transition flight. This paper develops a propulsion-aerodynamic coupling model for a medium-sized DPW UAV with induced wings (DPW-IW), enabling real-time aerodynamic performance calculations. Furthermore, a unified flight-control framework is proposed to avoid controller scheduling and switching during flight mode transitions. The proposed control framework employs the time-scale separation principle, divided into an outer loop and an inner loop. The outer loop uses a fuzzy controller to adjust allocation parameters, while the inner loop applies incremental nonlinear dynamic inversion (INDI) and control allocation (INCA) methods, providing robustness to nonlinear changes during flight transitions. Finally, simulations under various conditions demonstrate the controller’s effectiveness in ensuring smooth and robust transitions.

Space flight mechanics theoretist and practitioner. On the 100th anniversary of the birth of academician T.M. Eneev

The article presents materials about Academician Timur Magometovich Eneev, an outstanding scientist in the field of space flight mechanics, one of the founders of modern space flight dynamics. His works have made a significant contribution to the achievements of world science. Namely, his contribution to the launch of the first artificial satellite of the Earth, the flight of Yuri Gagarin, to the implementation of flights to the Moon, planets of the Solar system, to the study of small bodies of the Solar system, to the theory of cosmogony, solving problems of genetics is great. The new mathematical methods proposed by T.M. Eneev to solve the problems of space exploration constitute the golden fund of Russian astrodynamics and are successfully used for the implementation of Russian space exploration projects. T.M. Eneev is not only an outstanding scientist, but also a citizen of our Fatherland, who responded to the problems of the formation of science, cosmonautics, cosmogony, biology and other issues of concern to modern society.

Development of a Novel Tailless X-Type Flapping-Wing Micro Air Vehicle with Independent Electric Drive.

A novel tailless X-type flapping-wing micro air vehicle with two pairs of independent drive wings is designed and fabricated in this paper. Due to the complexity and unsteady of the flapping wing mechanism, the geometric and kinematic parameters of flapping wings significantly influence the aerodynamic characteristics of the bio-inspired flying robot. The wings of the vehicle are vector-controlled independently on both sides, enhancing the maneuverability and robustness of the system. Unique flight control strategy enables the aircraft to have multiple flight modes such as fast forward flight, sharp turn and hovering. The aerodynamics of the prototype is analyzed via the lattice Boltzmann method of computational fluid dynamics. The chordwise flexible deformation of the wing is implemented via designing a segmented rigid model. The clap-and-peel mechanism to improve the aerodynamic lift is revealed, and two air jets in one cycle are shown. Moreover, the dynamics experiment for the novel vehicle is implemented to investigate the kinematic parameters that affect the generation of thrust and maneuver moment via a 6-axis load cell. Optimized parameters of the flapping wing motion and structure are obtained to improve flight dynamics. Finally, the prototype realizes controllable take-off and flight from the ground.

Uncertainty analysis of hypersonic flight dynamics under elastic effects

Abstract In addressing the aerodynamic-elastic coupling issues of hypersonic vehicles, this study delves into the analysis of the elastic deformation of the aircraft based on mechanistic understanding. It employs the Interval Analysis Method based on Polynomial Approximations to conduct uncertainty analysis of the aerodynamic model under elasticity, delineating the range of uncertainty in the aerodynamic model influenced by elastic deformation. The aerodynamic force of the aircraft under elasticity is connected with the rigid body, and then the aerodynamic layout of the aircraft fuselage and control surface after elastic deformation is calculated to study the influence of the elastic effect on the aerodynamic force. The results show that the change caused by uncertainty has a relatively small effect on lift but a relatively large effect on drag and pitching moment.

Nonlinear Aero-Propulsive Modeling for Fixed-Wing eVTOL UAV from Flight Test Data

This paper presents a methodology for constructing an aero-propulsive system identification model for a fixed-wing propeller-driven aircraft with limited flight data. Developing a flight dynamics model is an iterative process involving costly and time-consuming flight testing to collect relevant data. To maximize the utilization of available data, this study employs a time-domain system identification procedure on flight data from various maneuvers and flights. The methodology incorporates multivariate orthogonal functions to capture the nonlinear terms representing the coupled effects of the propeller and airframe dynamics. A stepwise regression is then employed to identify the most pertinent model parameters. Estimation of variables associated with the propulsive contribution is accomplished through an electrical propulsive model, identified using command and battery data from static thrust and flight tests. Aero-propulsive derivatives are determined using the output-error method, where the accuracy is assessed based on a colored noise correction. To validate the predictability of the flight dynamics model, out-of-sample data are employed. The construction of the electrical propulsive model and identification of aerodynamic derivatives from flight data were specifically carried out for a particular eVTOL flight test vehicle; however, the techniques employed are generalizable and applicable to other aircraft models.

Study on the aerodynamic characteristics of reentry capsule with obtuse head inverted cone under hypersonic chemical nonequilibrium flow

Abstract During spacecraft reentry, the aerodynamic characteristics of the reentry capsule with a sizeable obtuse head inverted cone (OBHIC) in a hypersonic state are the key factors in the design of controlled reentry trajectory, the design of trim angle of attack (AoA), and the accuracy of fall point of capsules. This paper establishes a numerical simulation algorithm of a hypersonic chemical nonequilibrium flow field by considering high-temperature real gas effects. The reentry capsule’s aerodynamic and flow field characteristics are predicted and analyzed. The component transport equations for chemical reactions are added to the Navier-Stokes equations, enabling precise modeling of gas molecule vibrational excitation and ionization processes. A half-model multi-block structured mesh is employed to construct the aerodynamic profile of the reentry capsule with OBHIC. The aerodynamic characteristics and pressure distribution of the reentry capsule were calculated and analyzed under the typical conditions of flight altitude of 40~80 km, flight velocity of 6~27 Ma, and AoA of 15°~24°. The results of the aerodynamic characteristics prediction show that the aerodynamic characteristics of the reentry capsule are little affected by the incoming flow velocity in a hypersonic state but significantly affected by the AoA. As the AoA increases, the lift coefficient CL increases linearly, the drag coefficient CD decreases linearly, the lift-to-drag ratio K rises linearly, and K increases from 0.19 to 0.29. In its hypersonic state, the reentry capsule exhibits a low lift-to-drag ratio, characterized by high drag and low lift coefficients. The results of this paper play an essential role in the reentry flight dynamics and reentry trajectory design of the reentry capsule. Moreover, it can further ensure the safety and reliability of the reentry flight of spacecraft.

Research on Bionic Robot Motion Control Based on Reinforcement Learning

This research explores the application of reinforcement learning (RL) to enhance the motion control of bio-inspired robots across various environments. Focusing on underwater, terrestrial, and aerial robotic models, the study integrates model-free Q-learning, Deep Q Network (DQN), State-Action-Reward-State-Action (SARSA), and Double Deep Q Network (DDQN) algorithms. These methods are employed to achieve adaptive and efficient movement strategies without relying on pre-defined environmental models. The methodologies range from real-time data capture using live camera feeds for terrestrial robots to simulating aquatic and flight dynamics in controlled environments. Experimental results confirm the efficacy of these RL methods, demonstrating significant improvements in the robots' ability to adapt to dynamic and unknown environments, optimize movement efficiency, and navigate complex scenarios. The findings suggest a promising direction for future robotic applications, emphasizing the need for further research on optimizing these algorithms and expanding their real-world applicability. This study highlights the potential of RL to revolutionize robotic motion control, making robots more versatile and capable in varied and unpredictable settings.

Conceptual Designing of Control System for an Unmanned Martian Airship for Exploration

This research focuses on the flight dynamics of a Martian airship designed for planetary exploration, with special attention to the unique atmospheric challenges presented by the Red Planet. The study delves into the intricacies of flight stability, buoyancy control, aerodynamic drag, and propulsion. By employing MATLAB Simulink simulations, we model the airship's ascent, hovering, and descent cycles to evaluate thrust requirements and optimal fuel management. Through a detailed examination of aerodynamic forces, we present a holistic view of the airship’s flight mechanics and control systems, including an innovative Pneumatic Propulsion System.

Quantifying Well Clear Thresholds for UAV in Conjunction with Trajectory Conformity

The rapid advancement of unmanned aerial vehicles (UAVs) has introduced new challenges in overseeing and managing their flight operations due to their diverse flight dynamics and performance metrics. To address these complexities, this study introduces a concept of trajectory conformity aimed at enhancing the supervision and control of UAV flights. Trajectory conformity, from a regulatory perspective, is defined as the distribution of deviations between a UAV’s actual flight path and its intended trajectory, offering a measure of system-wide operational error. The concept of conformity is hoped to simplify and strengthen the monitoring process to ensure conflict-free drone flying. The present work is also concerned with the development of a comprehensive UAV collision risk model grounded in trajectory conformity analysis. The normality and homogeneity of UAV trajectory deviations are validated by evaluating the trajectory data obtained from real-world UAV flights. Well clear thresholds between two UAVs operating in three orthogonal directions within the same airspace have been established by the developed model. The results obtained demonstrate the effectiveness in omni-encounter scenarios, underscoring the potential to strengthen safety measures. The present work is expected to enhance UAV safety systems, such as detect and avoid (DAA) and unmanned aircraft system traffic management (UTM), by enabling real-time collision warnings within predefined safety thresholds, supporting proactive risk mitigation. Furthermore, the model’s versatility allows it to be applied to various UAV operational aspects in future works, including route planning, flight procedure design, airspace capacity assessments, and establishment of separation minima.

Swarming Insects May Have Finely Tuned Characteristic Reynolds Numbers.

Over the last few years, there has been much effort put into the development and validation of stochastic models of the trajectories of swarming insects. These models typically assume that the positions and velocities of swarming insects can be represented by continuous jointly Markovian processes. These models are first-order autoregressive processes. In more sophisticated models, second-order autoregressive processes, the positions, velocities, and accelerations of swarming insects are collectively Markovian. Although it is mathematically conceivable that this hierarchy of stochastic models could be extended to higher orders, here I show that such a procedure would not be well-based biologically because some terms in these models represent processes that have the potential to destabilize insect flight dynamics. This prediction is supported by an analysis of pre-existing data for laboratory swarms of the non-biting midge Chironomus riparius. I suggest that the Reynolds number is a finely tuned property of swarming, as swarms may disintegrate at both sufficiently low and sufficiently high Reynolds numbers.

A Deep Learning Approach for Predicting Aerial Suppressant Drops in Wildland Firefighting Using Automatic Dependent Surveillance–Broadcast Data

This study utilizes Automatic Dependent Surveillance–Broadcast (ADS-B) data sourced by the OpenSky Network to curate a dataset aimed at enhancing the precision of aerial suppressant drop predictions in wildland firefighting. By amalgamating ADS-B data with Automated Telemetry Unit (ATU) drop information, this research constructs a reliable base for analyzing the spatial aspects of aerial firefighting operations. Using sequential machine learning models, specifically Long Short-Term Memory (LSTM) networks and 1D Convolutional Neural Networks (1DCNN), the study interprets complex flight dynamics to predict drop locations. The dataset, covering 2017 to 2023, is labeled and segmented to reflect accurate suppressant release events, facilitating the distinction between drop and non-drop activities in fixed-wing aircraft. The LSTM model demonstrated strong predictive performance with an F1 score of 0.922, effectively identifying suppressant drop events with high accuracy. This model’s reliable predictions can significantly improve situational awareness in real-time aerial firefighting operations, enabling more informed decision-making and better coordination of resources during wildfire events.

Modelling and dynamic analysis of a synchropter

This paper addresses the flight dynamics modelling, trim, and dynamic analysis of an intermeshing-rotor helicopter, indicated as synchropter. This configuration has gained a great interest for its suitability within heavy load lifting and transportation in extreme high temperature and altitude, and other harsh environments. The paper presents some relevant features related to synchropter's flight dynamics modelling of the interference between its two tilted main rotors. Trim results show the advantage of the synchropter in forward flight where the yawing moment is naturally balanced at almost all speeds and no lateral-directional compensation is needed. The synchropter's dynamic stability shows similarity to a conventional helicopter in the longitudinal phugoid. However, in the lateral phugoid, the synchropter is unstable at all flying speeds and therefore its vertical fin needs to be carefully designed.