Design and Simulation of an Adaptive Flight Control System for Unmanned Rotorcraft

Flight stability and control system design is a problematic area for teaching\nand learning in most tertiary institutions because of limitations in\nimplementation and operation opportunities. Implementation and operation is a\ncritical element of student learning because of the need for students to\nunderstand the relationship between design procedures and decisions, and their\nconsequences in flight operation. Motion based flight simulation is a very\neffective mechanism for students to experience the transient responses and\nstability of a flight control system in flight, and to relate these back to the\ndesign process to reinforce learning. This paper describes how a motion based\nflight simulation facility has been integrated into a flight control system\ndesign course in a way that makes use of the CDIO principles. Students conceive\nand design a flight control solution for a given aeroplane, and then are able\nto embed that solution in the simulator and to operate the autopilot so as to\nexperience the dynamics of their solution through the subsequent vestibular and\nvisual stimuli.\n\nThe paper also addresses how this concept is being expanded into a more\nthorough\nimplementation in which courses in aircraft design, dynamics, and aerodynamics\nare\nbeing unified in a CDIO structure, with flight simulation providing capstone\nlearning opportunities.

Recently, there has been a growing interest among academics worldwide in studying flight control systems. The advancement of tracking technologies, such as the X-15 adaptive flight control system developed at NASA (National Aeronautics and Space Administration), has sparked significant exploration efforts by scientists. The vast availability of aerial resources further contributes to the importance of studying adaptive flight control systems (AFCS). The successful operation of AFCS relies on effectively managing the three fundamental motions: pitch, roll, and yaw. Therefore, scientists have been diligently working on developing optimization algorithms and models to assist AFCS in achieving optimal gains during motion. However, in real-world scenarios, each motion requires its own set of criteria, which presents several challenges. Firstly, there are multiple criteria available for selecting appropriate optimization values for each motion. Secondly, the relative importance of these criteria influences the selection process. Thirdly, there is a trade-off between the performance of the criteria within a single optimization case and across different cases. Lastly, determining the critical value of the criteria poses another obstacle. Consequently, evaluating and selecting optimum methods for AFCS trajectory controls becomes a complex operation. To address the need for optimizing AFCS for various maneuvers, this study proposes a new selection process. The suggested approach involves utilizing black hole optimization (BHO), Jaya optimization algorithm (JOA), and sunflower optimization (SFO) as methods for detecting and correcting trajectories in adaptive flight control systems. These methods aim to determine the best launch of missiles from the AFCS based on the coordinate location for both long and short distances. Additionally, the methods determine the optimal gains for the FOPID (fractional order proportional integral derivative) controller and enhance protection against enemy attacks. The research framework consists of two parts. The first part focuses on improving the FOPID motion gains by employing optimization algorithms (BHO, JOA, and SFO) that are evaluated based on the FOPID criteria. Lower significant weighting values of the optimization algorithms demonstrate the best missile launching in a cosine wave trajectory within AFCS, while higher significant values indicate the best missile launching in a sine wave trajectory within AFCS. The FOPID controller criteria, including Kp_pitch, Ki_roll, Kd_yaw, λ_pitch, and µ_yaw, are considered in all situations. Furthermore, the study reports the best weights obtained for the "Kp_pitch" criterion across the motions as follows: (0.8147, 66.7190, and 54.4716). For the "Ki_roll" criterion, the best weights are (0.0975, 64.4938, and 64.7311), and for "Kd_yaw" the weights are (0.1576, 35.2811, and 54.3886). The results of the selection process by the BHO, JOA, and SFO algorithms also include λ_pitch (0.1419, 40.0791, and 72.1047) and µ_yaw (0.6557, 13.5752, and 52.2495). To ensure the validity of the proposed research framework, a systematic evaluation and precise analysis were conducted.

Selection and evaluation of FOPID criteria for the X-15 adaptive flight control system (AFCS) via Lyapunov candidates: Optimizing trade-offs and critical values using optimization algorithms

Rotorcraft flight control systems present design challenges which often exceed those associated with fixed-wing aircraft. First, large variations in the response characteristics of rotorcraft result from the wide range of airspeeds of typical operation (hover to over 100 kts). Second, the assumption of vehicle rigidity often employed in the design of fixed-wing flight control systems is rarely justified in rotorcraft where rotor degrees of freedom can have a significant impact on the system performance and stability. Proposed herein is a methodology for the design of robust rotorcraft flight control systems utilizing Quantitative Feedback Theory (QFI'), a technique which accounts for variability in the dynamic response of the controlled element in the design of robust control systems. It was developed to address a Multiple-Input-Single-Output (MISO) design problem, but was extended to the address the Multiple-Input-Multiple-Output (MIMO) flight control system (FCS) design problem of a UH-60 Black Hawk Helicopter. Inherent conservatism in this design technique leads to limitations in its utility. A modified QFI' approach proved a viable method for designing robust MIMO flight control systems. An analysis of the two flight control system design methodologies is presented.

The energy configuration of the actuator of the flight control system directly affects whether the aircraft is stable and safe to fly. On the one hand, the safety of flight control system is closely related to the energy configuration of actuator, and it needs to be carefully configured to meet the requirements of safety index of flight control system; on the other hand, the development of electric drive actuator technology is increasingly mature and the reliability is continuously improved, which can effectively reduce the weight of aircraft; therefore, it is important to study the energy configuration design of flight control system actuator. Firstly, this paper studies the configuration design of aircraft control system in foreign countries, summarizes the design idea and development trend; secondly, designs the hydraulic configuration requirements of flight control system actuators and power supply system configuration requirements, and improves the flight control safety and reliability through the hybrid configuration of multiple energy sources; finally, a large aircraft flight control system actuator energy configuration scheme is provided to promote the design and development of flight control system.

In this paper, direct adaptive model reference control is applied to a modified MK-82 Joint Direct Attack Munition weapon flight control system. This adaptive flight control system was designed and flight tested without wind tunnel measurement of any aerodynamic changes to the modified weapon. The adaptive flight control augments the weapon’s baseline autopilot which was designed using a linear quadratic regulator incorporating integral control. While the latter was constructed to provide system stability and command tracking using nominal plant data, the adaptive augmentation was designed to maintain the desired closed-loop system characteristics in the presence of the aerodynamic uncertainties caused by the hardware modifications, environmental disturbances, and potential control failures. This paper summarizes the design, simulation testing, and flight test results using the adaptive flight control system.

The paper addresses initial steps involved in the development and flight implementation of new metrics driven L1 adaptive flight control system. The work concentrates on (i) definition of appropriate control driven metrics that account for the control surface failures; (ii) tailoring recently developed L1 adaptive controller to the design of adaptive flight control systems that explicitly address these metrics in the presence of control surface failures and dynamic changes under adverse flight conditions; (iii) development of a flight control system for implementation of the resulting algorithms onboard of small UAV; and (iv) conducting a comprehensive flight test program that demonstrates performance of the developed adaptive control algorithms in the presence of failures. As the initial milestone the paper concentrates on the adaptive flight system setup and initial efforts addressing the ability of a commercial off-the-shelf autopilot with and without adaptive augmentation to recover from control surface failures.

In this paper, we apply a so‐called robust and perfect tracking (RPT) control technique to the design and implementation of the flight control system of a miniature unmanned rotorcraft, named HeLion. To make the presented work self‐contained, we will first outline some background knowledge, including mainly the nonlinear flight dynamics model and the inner‐loop flight control system design. Next, the highlight of this paper, that is, the outer‐loop flight control system design procedure using RPT control technique, will be detailed. Generally speaking, RPT control technique aims to design a controller such that (i) the resulting closed‐loop system is asymptotically stable, and (ii) the controlled output almost perfectly tracks a given reference signal in the presence of any initial conditions and external disturbances. Since it makes use of all possible information including the system measurement output and the command reference signal together with all its derivatives (if available) for control, RPT control technique is particularly useful for the outer‐loop layer of an unmanned aircraft. Both simulation and flight‐test results will be presented and analyzed at the end of this paper, and the efficiency of the RPT control approach will be evaluated comprehensively.

The Orion Spacecraft will be required to perform entry and landing functions for both Low Earth Orbit (LEO) and Lunar return missions, utilizing only the Command Module (CM) with its unique systems and GN&C design. This paper presents the current CM Flight Control System (FCS) design to support entry and landing, with a focus on analyses that have supported its development to date. The CM FCS will have to provide for spacecraft stability and control while following guidance or manual commands during exo-atmospheric flight, after Service Module separation, translational powered flight required of the CM, atmospheric flight supporting both direct entry and skip trajectories down to drogue chute deploy, and during roll attitude reorientation just prior to touchdown. Various studies and analyses have been performed or are on-going supporting an overall FCS design with reasonably sized Reaction Control System (RCS) jets, that minimizes fuel usage, that provides appropriate command following but with reasonable stability and control margin. Results from these efforts to date are included, with particular attention on design issues that have emerged, such as the struggle to accommodate sub-sonic pitch and yaw control without using excessively large jets that could have a detrimental impact on vehicle weight. Apollo, with a similar shape, struggled with this issue as well. Outstanding CM FCS related design and analysis issues, planned for future effort, are also briefly be discussed.

This book provides information covering the fundamentals of control theory and optimization applied to real-world flight control systems. Covers the following topics: the challenges inherent in flight control system design; an overview of their core approach to flight control system design utilizing multiobjective parametric optimization; the specific software developed called Control Designer’s Unified Interface (CONDUIT); detailed explanations of the tools, plots, language, and four key components involved in defining the problem using CONDUIT; the XV-15 hover/forward flight case study is discussed in sufficient detail for even seasoned veterans to find the presentation informative and useful. Here the authors have done an excellent job of demonstrating many flight control concepts; proprietary specifications; methodologies for developing simulation models of model-based flight control system designs; design of flight control systems; the inner workings of the design optimization approach. The coverage includes specifics of various algorithms, along with their relative advantages and disadvantages. This chapter also provides insights into sequential loop closure strategies, with emphasis on their effectiveness and practical use; nested versus simultaneous multiloop strategies; and design considerations for real-world applications. This book serves as an excellent reference for senior undergraduate and/or graduate students, and it provides a wellbalanced perspective covering the theory, implementation, and practical applications of flight control design.

The work presented in this paper focuses on the design of a robust nonlinear flight control system for a small fixed-wing UAV against uncertainties and external disturbances. Toward this objective, an integrated UAV waypoints guidance scheme based on Carrot Chasing guidance law (CC) in comparison with the pure pursuit and line of sight-based path following (PLOS) guidance law is analyzed. For path following based on CC, a Virtual Track Point (VTP) is introduced on the path to let the UAV chase the path. For PLOS, the pure pursuit guidance law directs the UAV to the next waypoint, while the LOS guidance law steers the vehicle toward the line of sight (LOS). Nonlinear Dynamic Inversion (NLDI) awards the flight control system researchers a straight forward method of deriving control laws for nonlinear systems. The control inputs are used to eliminate unwanted terms in the equations of motion using negative feedback of these terms. The two-time scale assumption is adopted here to separate the fast dynamics—three angular rates of aircraft—from the slow dynamics—the angle of attack, sideslip, and bank angles. However, precise dynamic models may not be available, therefore a modification of NLDI is presented to compensate the model uncertainties. Simulation results show that the modified NLDI flight control system is robust against wind disturbances and model mismatch. PLOS path-following technique more accurately follows the desired path than CC and also requires the least control effort.

A novel flight control system architecture aimed at vertical takeoff and landing (VTOL) vehicles was designed, simulated, and flight tested. A simulation model was developed using an empirically-derived aerodynamic model and mass properties for a subscale fixed-wing aircraft. The simulation framework was used to design and simulate the proposed flight control architecture through a series of piloted simulations. A simulation model of a VTOL variant of the fixed-wing vehicle was also created to demonstrate the flight control system on a transitioning VTOL aircraft. Flight tests were performed at the NASA Langley Autonomy Lab for Intelligent Flight Technology (ALIFT) and City Environment Range Testing for Autonomous Integrated Navigation (CERTAIN) facilities to validate the proposed control system. Validation flights were performed on a small multirotor vehicle and a subscale fixed-wing vehicle to assess hover and forward flight performance. A Pixhawk® flight computer was used along with the MathWorks® UAV Toolbox to provide rapid control law integration and testing. The presented results aim to validate the feasibility of the proposed control system architecture and simulation-to-hardware process.

Flight control system for the Automatic Landing Flight Experiment

A direct methodology for the design of flight control systems is introduced. The design approach uses a control selector and an inner/outer loop structure to achieve robustness and performance across the flight envelope. A control selector normalizes control effectiveness with respect to generalized inputs. An inner loop uses dynamic inversion to equalize plant dynamics across the flight envelope. An outer loop is designed around this equalized plant using μ-synthesis to achieve performance and robustness goals. The methodology is applied in the design of a manual flight control system for the lateral axis of a fighter aircraft. Analysis shows that the inner/outer loop approach produces designs which exhibit excellent performance and robustness for a broad range of operating conditions. The direct incorporation of design goals such as flying qualities requirements and the elimination of gain scheduling make this direct methodology an effective and efficient alternative to traditional flight control design approaches.

A direct methodology for the design of flight control systems is introduced. The design approach uses a control selector and an inner/outer loop structure to achieve robustness and performance across the flight envelope. A control selector normalizes control effectiveness with respect to generalized inputs. An inner loop uses dynamic inversion to equalize plant dynamics across the flight envelope. An outer loop is designed around this equalized plant, using mu -synthesis to achieve performance and robustness goals. The methodology is applied to the design of a manual flight control system for the lateral axis of a fighter aircraft. Analysis shows that the inner/outer loop approach produces designs with excellent performance and robustness for a broad range of operating conditions. The direct incorporation of design goals such as flying qualities requirements and the elimination of gain scheduling make this direct methodology an effective and efficient alternative to traditional flight control design approaches. >