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Flight Control System Simulation
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Flight Control System Simulation

A special issue of Drones (ISSN 2504-446X).

Deadline for manuscript submissions: closed (31 March 2023) | Viewed by 10748

Special Issue Editors

Dr. Zeashan H. Khan

E-Mail Website
Guest Editor
Department of Avionics Engineering, College of Aeronautical Engineering (CAE), National University of Sciences and Technology (NUST), Islamabad, Pakistan
Interests: flight dynamics and control; fault diagnosis; reconfigurable flight control
Dr. Imran Mir

E-Mail Website
Guest Editor
Department of Avionics Engineering, College of Aeronautical Engineering (CAE), National University of Sciences and Technology (NUST), Islamabad, Pakistan
Interests: autopilot design; flight dynamics and control; Unmanned Air Vehicle (UAV) systems; nonlinear dynamics; wind energy
Dr. Syed Tauqeer Ul Islam Rizvi

E-Mail Website
Guest Editor
Department of Avionics Engineering, College of Aeronautical Engineering (CAE), National University of Sciences and Technology (NUST), Islamabad, Pakistan
Interests: flight vehicle design (SLV & UAV); trajectory optimization; flight dynamics & simulation; computational fluid dynamics; experimental aerodynamics

Special Issue Information

Dear Colleagues, 

Flight dynamics modeling and Simulation have always been an area of interest to model the nonlinear dynamics of flight vehicles and testing the flight control software for necessary verification and validation of guidance, navigation and control (GNC) algorithms. This applies to both fixed-wing and helicopters, spacecraft and similar systems. In the initial design, Model-in-Loop (MIL) simulation is used to evaluate the algorithms in the simulation environment. Moreover, software in loop (SIL) simulation verifies the generated software code used in the controller for quick debugging. Processor-in-Loop (PIL) provides a framework for the validation of the actual controller code on a microcontroller/DSP/FPGA-based flight computer that interacts with a simulation in the software environment. By comparing normal and PIL simulation results, the designer can test the numerical equivalence of the generated model and the generated code, whereas the processor in the loop simulation (PIL) and the hardware in the loop simulation (HILS) in real-time is used for the verification of flight control algorithms against realistic virtual stimuli. Recent technological advancements, such as the availability of advanced 6DOF motion simulators and hardware-software co-design tools have simplified the deployment of verification and validation of flight control algorithms. Thus, the “time to fly” your design with the necessary avionics suite is too less as compared to a classical methodology which required extensive testing and validation loops for reliable design of flight computer software.

The scope of this Special Issue is to present state-of-the-art research related to flight control simulation platforms, verification and validation, software in loop, processor in loop and hardware in loop simulation. Comparison of results between linear and nonlinear controllers and actual validation in flight test, system identification for correction of aerodynamics model and the related areas.

Papers for the Special Issue must provide a substantial novel contribution and authors must carefully position their work with regard to the relevant scientific literature. They must clearly address research issues related to flight simulation, hardware in loop test setup design, inflight system identification and the role of modelling and simulation in the design of aerospace vehicles.

Dr. Zeashan H. Khan
Dr. Imran Mir
Dr. Syed Tauqeer Ul Islam Rizvi
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Drones is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • modelling, development, verification and validation of flight vehicles
  • pilot in the loop simulation of autopilot
  • integrating system identification for autopilot verification
  • big data and ai for flight testing of full envelope
  • diagnosis and fault identification using simulation models
  • augmented reality for flight simulation
  • trajectory optimization
  • motion simulator and their applications in flight control software validation
  • nonlinear and adaptive flight controllers under actuator and sensor faults

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Published Papers (4 papers)

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Research

27 pages, 3085 KiB  
Article
Attitude-Tracking Control for Over-Actuated Tailless UAVs at Cruise Using Adaptive Dynamic Programming
by Zihou He, Jianbo Hu, Yingyang Wang, Jiping Cong, Yuan Bian and Linxiao Han
Drones 2023, 7(5), 294; https://doi.org/10.3390/drones7050294 - 27 Apr 2023
Cited by 5 | Viewed by 1678
Abstract
Using adaptive dynamic programming (ADP), this paper presents a novel attitude-tracking scheme for over-actuated tailless unmanned aerial vehicles (UAVs) that integrates control and control allocation while accounting for nonlinearity and nonaffine control inputs. The proposed method uses the idea of nonlinear dynamic inversion [...] Read more.
Using adaptive dynamic programming (ADP), this paper presents a novel attitude-tracking scheme for over-actuated tailless unmanned aerial vehicles (UAVs) that integrates control and control allocation while accounting for nonlinearity and nonaffine control inputs. The proposed method uses the idea of nonlinear dynamic inversion to create an augmented system and converts the optimal tracking problem into an optimal regulation problem using a discounted performance function. Drawing inspiration from incremental control, this method achieves optimal tracking control for the nonaffine system by simply using a critic-only structure. Moreover, the unique design of the performance function ensures robustness against model uncertainties and external disturbances. The ADP method was found to outperform traditional control architectures that separate control and control allocation, achieving the same level of attitude-tracking performance through a more optimized approach. Furthermore, unlike many recent optimal controllers for nonaffine systems, our method does not require any model identifiers and demonstrates robustness. The superiority of the ADP-based approach is verified through two simulated scenarios, and its internal mechanism is further discussed. The theoretical analysis of robustness and stability is also provided. Full article
(This article belongs to the Special Issue Flight Control System Simulation)
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21 pages, 5131 KiB  
Article
A Nonlinear Adaptive Autopilot for Unmanned Aerial Vehicles Based on the Extension of Regression Matrix
by Quanwen Hu, Yue Feng, Liaoni Wu and Bin Xi
Drones 2023, 7(4), 275; https://doi.org/10.3390/drones7040275 - 18 Apr 2023
Viewed by 1968
Abstract
In applications of the L1 adaptive flight control system, we found two limitations to be extended: (1) the system cannot meet the demands of engineering in terms of nonlinearity and adaptation in most flight scenarios; (2) the adaptive control law generates a [...] Read more.
In applications of the L1 adaptive flight control system, we found two limitations to be extended: (1) the system cannot meet the demands of engineering in terms of nonlinearity and adaptation in most flight scenarios; (2) the adaptive control law generates a transient response in the tracking error, hindering the system from reaching the steady-state error, and ultimately decreasing control accuracy. In response to these problems, an extended flight control system for L1 adaptive theory is proposed and rigorously proved. This system involves considering the nonlinear function matrix of state variables, which serves as an extension of the regression matrix in the original L1 adaptive control system, thus enhancing its nonlinear characteristics. The problem of calculating the adaptive laws, caused by the extended regression matrix, is solved by using the pseudo-inverse matrix. To eliminate the transient response, the state vector and its estimate are recorded and employed just like an integrator. Finally, the proposed system is verified on a high-subsonic flight subject to nonlinear uncertainties, with simulation results showing improved control accuracy and enhanced robustness. The proposed system resolves the limitations of the L1 adaptive control system in nonlinearity, providing the possibility for further theoretical development to improve the performance of adaptive control systems. Full article
(This article belongs to the Special Issue Flight Control System Simulation)
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22 pages, 4139 KiB  
Article
Neural Network and Dynamic Inversion Based Adaptive Control for a HALE-UAV against Icing Effects
by Yiyang Li, Lingquan Cheng, Jiayi Yuan, Jianliang Ai and Yiqun Dong
Drones 2023, 7(4), 273; https://doi.org/10.3390/drones7040273 - 17 Apr 2023
Cited by 3 | Viewed by 2033
Abstract
In the past few decades, in-flight icing has become a common problem for many missions, potentially leading to a reduction in control effectiveness and flight stability, which would threaten flight safety. One of the most popular methods to address this problem is adaptive [...] Read more.
In the past few decades, in-flight icing has become a common problem for many missions, potentially leading to a reduction in control effectiveness and flight stability, which would threaten flight safety. One of the most popular methods to address this problem is adaptive control. This paper establishes a dynamic model of an iced high-altitude long-endurance unmanned aerial vehicle (HALE-UAV) with disturbance and measurement noise. Then, by combining multilayer perceptrons (MLP) with a nonlinear dynamic inversion (NDI) controller, we propose an MLP-NDI controller to compensate for online inversion errors and provide a brief proof of control stability. Two experiments were conducted: on one hand, we compared the MLP-NDI controller with other typical controllers; on the other hand, we evaluated its robustness and adaptiveness under different icing conditions. Results indicate that the MLP-NDI controller outperforms other typical controllers with higher tracking accuracy and exhibits strong robustness in the presence of icing errors and measurement noise, which has huge potential to ensure flight safety. Full article
(This article belongs to the Special Issue Flight Control System Simulation)
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28 pages, 3268 KiB  
Article
Transition Nonlinear Blended Aerodynamic Modeling and Anti-Harmonic Disturbance Robust Control of Fixed-Wing Tiltrotor UAV
by Jingxian Liao and Hyochoong Bang
Drones 2023, 7(4), 255; https://doi.org/10.3390/drones7040255 - 10 Apr 2023
Cited by 5 | Viewed by 4121
Abstract
This study proposed a novel nonlinear blended aerodynamic model for the tiltrotor unmanned aerial vehicle (UAV) during the transition phase to handle the high angle-of-attack (AoA) flight, which aggregated the flat-plate mode and the linear mode of the aerodynamic coefficients. Additionally, a harmonic [...] Read more.
This study proposed a novel nonlinear blended aerodynamic model for the tiltrotor unmanned aerial vehicle (UAV) during the transition phase to handle the high angle-of-attack (AoA) flight, which aggregated the flat-plate mode and the linear mode of the aerodynamic coefficients. Additionally, a harmonic disturbance observer (HDO) and super-twisting sliding mode controller (STSMC) addressed the fast-changing external disturbances and attenuated the chattering problem in the original SMC. The comparative trajectory tracking results indicated that the blended aerodynamic model accurately tracks the reference signals with no tracking errors, which demonstrated a superior performance as compared to the traditional aerodynamic model, with a reduction of 2.2%, 50%, 73.6%, and 11.2% in the time required for tracking the pitch angle, pitch rate, and velocities u and w, respectively. Conversely, the traditional one exhibited significant tracking errors, ranging from 0.016° in the pitch angle channel to 1.25°/s in the pitch rate channel, and 0.6 m/s for velocity u and 0.01 m/s for velocity w. Moreover, the comparative control input results illustrated that the least control effort was required for the proposed HDO-STSMC control scheme with a blending function, while the original ESO-SMC experienced more oscillations and sharp amplitude changes, taking twice the time to converge, with considerable tracking errors such as 1.067° in the pitch angle channel, 0.788°/s in the pitch rate channel, 1.554 m/s for velocity u, and 0.746 m/s for velocity w, which verified the feasibility and superiority of the proposed HDO-STSMC with the blending function. Two performance indices revealed the robust stability and rapid convergence of the proposed transition blended aerodynamic model with the HDO-STSMC control scheme. Full article
(This article belongs to the Special Issue Flight Control System Simulation)
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