Aircraft Control System Research Articles

Advances in flight control systems for modern commercial aircraft

Abstract. In consequence of the accelerated evolution of aviation technology, the flight control systems of commercial aircraft have undergone substantial technological advancement and system optimization. This paper presents a comprehensive analysis of the recent advancements and future trends in flight control systems for commercial aircraft. The fundamental concepts and historical evolution of flight control systems are delineated, with a particular emphasis on the evolution of autopilot systems and the technological advancements of flight control systems (FCS). Furthermore, it examines innovations in flight control algorithms, including adaptive control and intelligent algorithms, and investigates the impact of fault-tolerant design on flight safety. In terms of system integration, the integration of flight control systems with navigation and communication systems, as well as performance enhancements resulting from system optimization, is explored. In addition, it examines the potential impact of intelligence and networking on future flight control systems, with a particular focus on the prospects for the application of artificial intelligence, quantum computing, and new material technologies. The synthesis of these areas provides a systematic understanding of the technological evolution and future development of flight control systems for commercial aircraft.

Research on Quadrotor Control Based on Genetic Algorithm and Particle Swarm Optimization for PID Tuning and Fuzzy Control-Based Linear Active Disturbance Rejection Control

The control system of a quadrotor aircraft is characterized by nonlinearity, strong coupling, and underactuation, making it susceptible to external disturbances that can affect flight performance. To address this issue, this paper proposes a novel control system based on inner–outer loop architecture. In this system, the outer loop position control adopts a PID controller optimized by Genetic Algorithm-based Particle Swarm Optimization (GA-PSO), while the inner loop attitude control employs a Linear Active Disturbance Rejection Controller (LADRC) with fuzzy algorithm-based adaptive tuning, forming a dual-loop control structure. Comparisons with traditional dual-loop cascaded PID controllers, conventional PID in the outer loop with LADRC in the inner loop, and conventional PID in the outer loop with fuzzy algorithm-based adaptive tuning in the inner loop demonstrate that the proposed control system can stably track the desired position and attitude angles under certain external disturbances, exhibiting excellent anti-disturbance capability and stability.

Research on Triplex Redundant Flight Control System Based on M1394B Bus

In the modern aviation field, flight control systems’ reliability and safety are paramount. This paper presents a triplex redundant flight control system based on the M1394B bus and designs several key algorithms to enhance system performance. Firstly, a triplex redundant flight control system with a redundant bus structure is constructed based on the characteristics of the M1394B bus. Secondly, a periodic synchronization algorithm with automatic adjustment capabilities is designed to achieve periodic synchronization among the Vehicle Management Computers. An improved voting algorithm based on a sliding window is proposed to enhance the decision-making accuracy and reliability of the control commands output by the flight control system. Additionally, a system reconstruction algorithm is designed to promptly identify and isolate faults, enabling the recovery and reallocation of system resources. Finally, experiments validate the effectiveness of the synchronization algorithm, voting algorithm, and system reconstruction algorithm. The results indicate that the system can effectively address practical engineering challenges and significantly improve reliability and stability. This research provides an essential theoretical foundation and practical reference for the design of future flight control systems for unmanned aerial vehicles and aircraft, holding significant relevance to application.

Review on Uncertainty Analysis and Information Fusion Diagnosis of Aircraft Control System

Review on Uncertainty Analysis and Information Fusion Diagnosis of Aircraft Control System

Flap and Wing Dynamics for a Light Sport Aircraft Analysis Using a Topological Model

This paper presents a more general method to study the dynamic behavior of a planar mechanism with joints. To do this, Graph Theory is used. A topological description is presented based on which a corresponding graph is attached to any mechanism. This method can be used for both kinematic and dynamic study in the same model, and many of the descriptors used in kinematic analysis can also be used for dynamic analysis. As a final result, the motion equations of the studied mechanical system can be obtained. An application is made to a flap and wing control system of a light sport aircraft. The graph associated with the mechanism first used to determine the field of velocities and accelerations of the mechanism elements is then used to obtain the motion equation for the control system. In this way, Graph Theory proves useful for the parallel study of both the kinematic and dynamic study of such problems.

Cumulative thermal coupling modeling and analysis of oil-immersed motor-pump assembly for electro–hydrostatic actuator

The Electro–Hydrostatic Actuator (EHA) is applied to drive the control surface in flight control system of more electric aircraft. In EHA, the Oil-Immersed Motor Pump (OMP) serves as the core as a power assembly. However, the compact integration of the OMP presents challenges in efficiently dissipating internal heat, leading to a performance degradation of the EHA due to elevated temperatures. Therefore, accurately modeling and predicting the internal thermal dynamics of the OMP hold considerable significance for monitoring the operational condition of the EHA. In view of this, a modeling method considering cumulative thermal coupling was hereby proposed. Based on the proposed method, the thermal models of the motor and the pump were established, taking into account heat accumulation and transfer. Taking the leakage oil as the heat coupling point between the motor and the pump, the dynamic thermal coupling model of the OMP was developed, with the thermal characteristics of the oil considered. Additionally, the comparative experiments were conducted to illustrate the efficiency of the proposed model. The experimental results demonstrate that the proposed dynamic thermal coupling model accurately captured the thermal behavior of OMP, outperforming the static thermal parameter model. Overall, this advancement is crucial for effectively monitoring the health of EHA and ensuring flight safety.

Study of vortex throttle characteristics with adjustable resistance by rotation of the vortex chamber inlet channel

Abstract The study is aimed at obtaining and analyzing the flow and cavitation characteristics of the proposed control devices, which are in demand in control systems for aircraft and rocket engines, chemical and other technological processes that require a wide range of flow control at high pressure drops. The characteristics of vortex throttling devices with cylindrical and spherical chambers were obtained, providing flow control in the range of 0.1–25 kg/s. A change in flow rate in the range of 3.5–3.8 can be achieved by changing the flow swirl intensity without throttling the flow sections. When vortex devices operate, the threshold for the occurrence of cavitation shifts to the region of small values of P out /P in, and, starting from the values of the geometric characteristic A > 4.5, cavitation is absent throughout the entire range of flow control. The pressure drop at the inlet channel of the vortex chamber does not exceed 10–30 % of the total resistance of the device. The torque on the control roller is small, 1.8–2.8 Nm, regardless of the flow rate.

Applying Machine Learning Techniques: Uncertainty Quantification in Nonlinear Dynamics Characters Predictions via Gated Recurrent Unit-Based Reduced-Order Models

The development of reduced-order models has been a pivotal advancement in the computational analysis of fluid dynamics, substantially simplifying the complexity and boosting the efficiency of simulations. The accuracy and practicality of these models largely depend on the reduction techniques applied and the inherent characteristics of the fluid dynamics systems they represent. In this paper, we introduce an innovative machine-learning framework for assessing model uncertainty in computationally intensive reduced-order models. By combining subspace construction methods with advanced Bayesian inference techniques, our approach effectively captures the posterior distribution of model parameters, thereby providing an accurate representation of uncertainty in aerodynamic performance predictions. We employ the NACA0012 airfoil as a case study to validate our method’s ability to enhance the efficiency of reduced-order models and precisely measure the uncertainty inherent in predictions made by recurrent neural networks. It is important to note that our approach is influenced by specific constraints and variables that significantly impact the mean and variability of the predicted final lift coefficient distribution. Our findings indicate that setting the goodness of fit (R2) threshold above 0.985 markedly improves the correlation between Computational Fluid Dynamics (CFD) outcomes and model predictions, increasing from 72.2% to 97.9% as the interval amplification factor adjusts from 1.5 to 3. However, this adjustment causes a considerable expansion of the confidence interval, from 0.0737 to 0.1282, an increase of over 70%. Despite these challenges, our machine learning-based methodology provides essential insights into the further development of reduced-order modeling and uncertainty quantification in fluid dynamics. This highlights the need for ongoing research into the model parameters, especially in applications concerning aircraft control systems, to meet design specifications and ensure system reliability.

Adaptive fault-tolerant control of distributed electric propulsion aircraft based on multivariable model predictive control

Distributed Electric Propulsion (DEP) aircraft presents a highly promising technology aligned with the demands of green aviation due to its superior flight efficiency, reduced energy loss, and diminished noise. This paper firstly designs and establishes a flight dynamics model for DEP aircraft, followed by an analysis of flying qualities, thus laying the foundation for control method design. Secondly, addressing the challenge of detecting subtle control surface faults, a deep learning fault diagnosis method based on Data Dimensionality Reduction (DDR) structure is devised, achieving an accuracy rate of 99.8 %. Finally, an adaptive fault-tolerant control method for the lateral motion mode of DEP aircraft is introduced, utilizing Constrained Multivariable-multiobjective Model Predictive Control (CMMPC). Notably, for the rudder complete fault, adaptive fault-tolerant control is achieved by switching controllers and utilizing differential thrust from distributed redundant propulsion units to mitigate yaw channel anomalies, thus showcasing the advantages of DEP aircraft. Simulation results validate the theoretical soundness of the proposed method, providing a theoretical basis for the future engineering application and advancement of control systems for DEP aircraft.

Adaptive PI Control Based Stability Margin Configuration of Aircraft Control Systems with Unknown System Parameters and Time Delay

Adaptive PI Control Based Stability Margin Configuration of Aircraft Control Systems with Unknown System Parameters and Time Delay

Strategy of Russian Military Cooperation with the Countries of the Arab Region

The article undertakes an analysis of the prospective domains of Russian military collaboration with Arab countries against the backdrop of geopolitical uncertainties. Despite maintaining its position as the second-largest arms exporter globally, Russia has experienced a proportional decline in its share of the global arms market. Nevertheless, a discernible uptick in the trade volume of conventional weaponry, coupled with cyclical enhancements in the tactical and technical attributes of military assets, reflects positive momentum in this sector. Amid prevailing external constraints and a noticeable scarcity of contemporary Russian weaponry in burgeoning segments of the arms market, Russia necessitates resolute and equitable measures to uphold and fortify collaborative ties with partner nations. Within this context, particular emphasis is placed on Russia's strategic military cooperation with Arab states, given the region's status as a focal point of geopolitical interests for major economies and a primary destination for arms imports.The article scrutinizes Russia's competitive standing in the arms and military equipment markets of the Arab world, acknowledging the region's significance as a pivotal importer of such goods. Employing a multifaceted evaluation encompassing absolute and relative statistical metrics and derived indices, the study assesses the region's role in global arms procurement. Moreover, it offers an appraisal of the existing state and potential avenues for enhancing the efficacy of the Russian-Arab military-technical collaboration framework. The discourse delves into the transformative prospects of this partnership within the framework of networkcentric warfare concepts. Furthermore, the article elucidates the principal risks inherent in military cooperation among nations at present, highlighting concerns regarding the possible manipulation of military-technical cooperation mechanisms to serve as leverage in furthering the geopolitical aspirations of specific stakeholders.In conclusion, the study posits forward-looking trajectories for bolstering bilateral relations, both sectorally and geographically. These include initiatives such as expanding licensing, leasing, offset transactions, and technology transfer initiatives; advocating for fifth-generation fighter aircraft and long-range radar detection and control systems, leveraging Industry 4.0 technologies; and prioritizing the training of foreign specialists.

Towards Trustworthy Deep Learning

Deep neural networks (DNNs) have achieved unprecedented success across many scientific and engineering fields in the last decades. Despite its empirical success, unfortunately, recent studies have shown that there are various failure modes and blindspots in DNN models which may result in unexpected serious failures and potential harms, e.g. the existence of adversarial examples and small perturbations. This is not acceptable especially for safety critical and high stakes applications in the real-world, including healthcare, self-driving cars, aircraft control systems, hiring and malware detection protocols. Moreover, it has been challenging to understand why and when DNNs will fail due to their complicated structures and black-box behaviors. Lacking interpretability is one critical issue that may seriously hinder the deployment of DNNs in high-stake applications, which need interpretability to trust the prediction, to understand potential failures, and to be able to mitigate harms and eliminate biases in the model. To make DNNs trustworthy and reliable for deployment, it is necessary and urgent to develop methods and tools that can (i) quantify and improve their robustness against adversarial and natural perturbations, and (ii) understand their underlying behaviors and further correct errors to prevent injuries and damages. These are the important first steps to enable Trustworthy AI and Trustworthy Machine Learning. In this talk, I will survey a series of research efforts in my lab contributed to tackling the grand challenges in (i) and (ii). In the first part of my talk, I will overview our research effort in Robust Machine Learning since 2017, where we have proposed the first attack-agnostic robustness evaluation metric, the first efficient robustness certification algorithms for various types of perturbations, and efficient robust learning algorithms across supervised learning to deep reinforcement learning. In the second part of my talk, I will survey a series of exciting results in my lab on accelerating interpretable machine learning and explainable AI. Specifically, I will show how we could bring interpretability into deep learning by leveraging recent advances in multi-modal models. I'll present recent works in our group on automatically dissecting neural networks with open vocabulary concepts, designing interpretable neural networks without concept labels, and briefly overview our recent efforts on demystifying black-box DNN training process, automated neuron explanations for Large Language Models and the first robustness evaluation of a family of neuron-level interpretation techniques.

LaterAnalysis of the energy efficiency of an environmental control system of a passenger aircraft by using the entropy-statistical method

BACKGROUND: Aviation designers are striving to increase fuel efficiency of aircraft, including by increasing the efficiency of aircraft environmental control systems by reducing losses in its components.
 AIM: This study performs an entropy-statistical analysis of the environmental control system of a passenger aircraft assesses efficiency losses in the units included in it.
 MATERIALS AND METHODS: A static mathematical model of an environmental control system with moisture content control was developed to calculate the system parameters in various operating modes, for which an entropy-statistical analysis was performed.
 RESULTS: Using entropy-statistical analysis, the main units of the system were examined, their influence on the overall efficiency of the environmental control system was assessed, and the advantages of the given method of entropy-statistical analysis for such systems were outlined. The mathematical model was developed using the Matlab Simulink software package.
 CONCLUSIONS: A static mathematical model of an environmental control system with a three-wheel air cycle machine unit and a “loop” high-pressure dehumidification system was developed. An entropy-statistical analysis of the system was performed. The influence of the units included in the system on the efficiency of the system as a whole was assessed.

Curvilinear Approach to Landing

ABSTRACT The article describes the problem of controlling an aircraft control when performing a landing on a curvilinear trajectory. The adoption of a curvilinear approach trajectory allows reducing the impact of air traffic on the areas adjacent to the airport. Performing the correct approach on the curvilinear path requires support. For the correct execution of the landing manoeuvre on the curvilinear track, it is necessary to establish reference points so that the repeatability of the manoeuvre is ensured, especially in the case of landing more than one aircraft at the same time. In the following parts, the landing control system is presented. Particularly carefully presented is the issue of performing tests of the designed control system, which in the case of the aircraft control system during the approach to landing must be extremely thoroughly verified. The test plan included both verification the correctness of the adopted control laws and their robustness to interference occurring as a result of atmospheric air streams.

Preface

This Proceedings arises from 2023 6th International Conference on Power Electronics and Control Engineering (ICPECE 2023), which was held via virtual form in Nanning, China from November 10th to 12th, 2023. Meetings in the ICPECE series were and will be held every year, and ICPECE 2023 marks the sixth time that this series of conference had been held successfully.The scientific and social program for the Conference ran over three days with more than 50 delegates from about 10 countries gathering on November 10th and departing on November 12th, including keynote speeches, oral presentations, poster presentations, free discussion, academic investigation, etc.In all there were four keynote speeches by renowned professors during the meeting. Professor Xingjian Wang from Beihang University, China addressed his research to us on Health Status Assessment and Fault-tolerance Control for Aircraft Control System. According to the control command of the pilot or the autopilot, the aircraft control system drives the aircraft rudder through the servo actuator to realize the aircraft attitude and flight trajectory control. In order to realize the highly reliable and healthy service of the aircraft control system, the health status assessment and remaining useful life prediction of the key components of the aircraft control system, the key technology of fault diagnosis for the airborne hydraulic system, and the high safety hierarchical active fault-tolerance control strategy were carried out to effectively improve the healthy service capability of the aircraft control system.Topics that were the focus of invited presentations and contributed papers at ICPECE 2023 included: Motor Drive and Frequency Converter, Drive Motor and Control Technology, Power and Fluid Machinery Equipment, Automatic Control Technology, Computer Integrated Manufacturing System, etc. All submissions were gone through a rigorous review process by performing double blind review to check their quality of content, level of innovation, significance, originality and legibility.The Conference could not have occurred without the generous support of the sponsors and the hard work of all Committee members. We are most grateful for the staff of Journal of Physics: Conference Series for their help and kindness in the preparation of this volume. Finally, we would like to thank all the attendees at ICPECE 2023 for their scientific contributions to the Conference, and for their warm spirit of engagement which characterized the scientific discussions and social occasions.The Committee of ICPECE 2023List of Committee Member is available in this pdf.

A study on flow distribution characteristics of heat exchanger module integration scheme for aircraft environmental control system based on CFD

With the rapid development of the civil aviation industry, the performance requirements of the environmental control system for domestic commercial large aircraft are gradually improved, and the ram air inlet heat exchanger system is its main component. Generally speaking, a ram air heat exchanger system mainly includes an air conditioning system heat exchanger, air preparation system heat exchanger, and auxiliary cooling system heat exchanger. The integration mode of the heat exchanger will directly affect the flow and flow distribution characteristics of the ram air heat exchanger system. This paper develops three integration schemes referring to the integration mode of heat exchangers in Boeing 787 and Airbus 350 aircraft. Based on Fluent software, the calculation and simulation of three integrated scheme models under the seven working conditions of taking off, climbing, cruising, descent, hovering, emergency, and landing during flight were carried out, and the flow distribution and flow resistance values of different schemes were obtained, which were compared to meet the heat transfer requirements.

An improved neural network for modeling airfoil's unsteady aerodynamics in transonic flow

Understanding the aerodynamic hysteresis loop phenomenon is essential when assessing aerodynamic performance and designing aircraft control systems. This phenomenon is a result of time delay effects in unsteady flow. Traditional methods of predicting unsteady aerodynamic forces using computational fluid dynamics have drawbacks, such as long cycles and low efficiency. In this paper, we focus on predicting the aerodynamic hysteresis loop of the NACA (National Advisory Committee for Aeronautics) 0012 airfoil in transonic flow using a new model called LIDNN (Latin hypercube sample input deep neural network). This model integrates input signals and optimization methods to improve upon traditional neural network models. Based on the example validation, the LIDNN model is authenticated as an accurate and efficient method in predicting the unsteady aerodynamic hysteresis loop of the NACA 0012 airfoil in transonic flow, and another significant advantage of the proposed model is its ability to solve multivariable problems effectively, even under varying Mach numbers.

Characteristics of operational control reliability of aircraft functional systems and avionics suites

The operational control system (OCS) of civil aircraft (A/C) airborne equipment is an important component of its technical operation system (TOS). Operational control is an integral part of the technical operation process. It makes it possible to assess the technical conditions (TC) of the objects to be monitored in various states of airborne equipment operation, aircraft preparation for flight, various types of maintenance and recovery. The main property of operational control is the reliability of control. The key task of operational control is not only to determine the type of technical condition, but also to quantify the correctness or erroneousness of decision-making. Control reliability characteristics (CRC) are quantitative indicators of the degree of objectivity in decision-making. Depending on the level of task details, it is necessary to distinguish the control reliability characteristics of units, functional systems (FS) and avionics suites for various means of operational control: built-in test equipment (BITE), on-board self-contained, ground-onboard and ground systems. The choice of the control reliability characteristics is based on the system analysis and the mathematical apparatus of logic, probability theory and mathematical statistics. Rational sets of technical states and decision-making about the technical conditions of functional systems and avionics suites are formed. Based on these sets, three groups of control reliability characteristics were identified. The first group consists of conditional probabilities of transitions in the operational control process under various types of control. The second group consists of unconditional probabilities of transitions in the operational control process under various types of control. The third group consists of a posteriori decision-making probability in the operational control process under various types of control. Analytical dependences for calculating the control reliability characteristics of three groups for functional systems and avionics suites and relationships between them are determined. The air-conditioning system was used to calculate the reliability of the control.

Preface

The International Conference on Mechatronics, Automation and Intelligent Control (MAIC) has confirmed once again this year the enthusiasm and determination of students and young researchers to play a major role in the scientific progress. Since 2021, we have regularly gathered to discuss the most recent developments and achievement on mechatronics, automation and intelligent control, and we firmly convince that sharing our expertise and experience is the foundation of research activity.The 2023 3rd International Conference on Mechatronics, Automation and Intelligent Control (MAIC 2023) took place from September 15th to 17th, 2023 in Guilin, China (virtual event), attracting about 80 leading delegates from around the world. The format we chose is a formal meeting primarily aimed at graduate students and leading researchers, who were encouraged to present their work through oral or poster presentations that provide genuine engagement of the audience and cross-pollination of ideas. One of the main purposes of the Conference was to create an international network of researchers, both experimentalists and theorists, and fruitful collaborations across different branches of mechatronics, automation and intelligent control.After previous two sessions that strengthened it, the International Conference on Mechatronics, Automation and Intelligent Control was held for the third time. It was a three-day Conference. The success of this year’s event was testified by an increased number of participants and institutions all around the world. This resulted in an extremely rich and interactive keynote speech, oral and poster session that covered several areas related to mechatronics, automation and intelligent control.With the intent of broadening the contents and stimuli adopting academic communication, the keynote speech part was held. This choice reflected the growing importance of the activity performed by scientists and researchers, especially at the earliest stages of their career, as a way of increasing their expertise and developing soft skills. During the meeting, Prof. Xingjian Wang from Beihang University, China shared with us his research on Fault Diagnosis and Fault-tolerance Control for Aircraft Control System. In order to realize the highly reliable and healthy service of the aircraft control system, the health status assessment and remaining useful life prediction of the key components of the aircraft control system, the key technology of fault diagnosis for the airborne hydraulic system, and the high safety hierarchical active fault-tolerance control strategy were carried out to effectively improve the healthy service capability of the aircraft control system.This paper volume cover topics on Industrial Robots and Automatic Production Line, Automatic Control Technology, Intelligent Fault Detection and Identification, Man-Machine Interactions, etc. Given the recent experimental achievements in mechatronics, automation and intelligent control, several contributions were focused on the latest results obtained in these fields, presenting the impact of experiments to the community of young researchers and forecasting the future goals in these areas of research.The organizers of MAIC 2023 would like to thank all the keynote speakers, authors, peer reviewers, and everyone who contributed to the Conference. We owe gratitude to all the Committee members for providing necessary help and support throughout the meeting. The publication of the Proceedings of this Conference is supported by Journal of Physics: Conference Series.The Committee of MAIC 2023List of Committee Member is available in this pdf.

AN Optimization control Techniques for Aircraft Yaw Control Lateral Dynamics

Presently, advanced control theory plays a major role in the aircraft system for the control of Yaw, Roll and Pitch angles, which was very much necessary for the stabilization of aircraft system. Following the works of the control system community for aircraft applications, this paper concentrates on the control of Yaw angle by designing various optimal Linear Quadratic Regulator (LQR) controllers using standard existing tools. The optimal controllers are designed for the aircraft, tested and validated using MATLAB/SIMULINK environment, and the results are compared with different system conditions to select the best optimal LQR feedback controllers in future aircraft control systems.