Flight Control

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Evolution of Aircraft Flight Control System and Fly-By-Light Flight Control System

Evolution of Aircraft Flight Control System and Fly-By-Light Flight Control System

on conventional methods of mechanical and hydro-mechanical system. The present generation aircraft are using fly-by-wire (FBW) and in future likely to migrate to fly-by-light (FBL) method for aircraft control system. Mechanical & Hydro- mechanical flight control systems have been replaced by Fly- By-Wire due to increasing speed of modern aircraft. Due to inherent characteristics of FBL like light weight, compact size, large bandwidth, immunity to EMI & HIRF FBL, it is expected to be ideal futuristic flight control system. Fly-by- Light control systems offer inherent resistance to the new generation more hostile military environments. The inherent features are the motivator to achieve the technological advances to make Fly-by-Light systems a successful replacement aircraft control system technology for future. The application of optical fiber in aviation promises to be very exciting study, covering highly complex aircraft stability and controls.
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Study of UAV Flight Control Software Test Method

Study of UAV Flight Control Software Test Method

(1) Wide coverage. Test may be divided into configuration item test and system test. Different test strategies and methods are adopted to test documents, source codes and software programs so as to eliminate software defects. Software requirements, correct design documents, standard codes and correct design or logic are guaranteed by document review, dynamic analysis and code review. Requirements for software functions, performance, interfaces and safety are checked in configuration item test. Software’s reliability in flight control system and the ability to collaborate with other UAV-carried integrated software are checked in system test.
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Aircraft Flight Control Simulation Using Parallel Cascade Control

Aircraft Flight Control Simulation Using Parallel Cascade Control

Abstract Aircraft flight simulation is a billion dollar industry worldwide that requires vast engineering resources. A method for modeling flight control systems using parallel cascade system identification is proposed as an addition to the flight simulator engineer’s toolbox. This method is highly efficient in terms of the data collection required for the modeling process since it is a black box method. This means that only the input and the output to the flight control system are required and details of the inner workings of the system can be largely ignored resulting in significantly fewer real data signals that need to be recorded. The paper views on two objectives. One the specific parallel cascade models can be identified that reproduce the behavior of a particular part of an aircraft flight control system. i.e. the pilot input control meet the objective test requirements of a commercial aircraft flight simulator. The second is to produce such a model which also meets the basic requirements for implementation in a working flight simulator.
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Information support of reconfigurable flight control system of the aircraft

Information support of reconfigurable flight control system of the aircraft

A. An analysis of the literature on information support in special situations reconfigurable flight control system Analysis of publications has shown that the science direction of diagnostics the state of the aircraft’s exterior aerodynamic contour in order to prevent the development of special situations in flight is not well-developed. There is no complete agreement which of the suggested methods of recording the moment of time, place and the degree of damage of the aircraft’s exterior contour in flight is the most effective to date. A group of researchers from the National Aviation University, Kyiv, Ukraine led by the supervisor of this science direction, is working in four areas of diagnosis of the aircraft exterior contour: electro-mechanic, thermodynamic, infra-red and marker-ion methods. In [1] the theoretical basics of diagnostics the state of the aircraft’s exterior aerodynamic contour in flight is laid. In [2,3] all materials on the diagnosis of the aerodynamic contour, the new methods of diagnosis, the mathematical models of intact aircraft and damaged one and model the impact of injuries on the aerodynamic characteristics of the aircraft were systematized. The expediency and necessity the synthesis of control system adaptive to the aircraft’s exterior contour damage and to the power plant is done. In [5] proposed a method for diagnostics the state of the aerodynamic contour of the aircraft based on the temperature field area of its airframe, and developed a system for implementing this method. Many articles [10, 11, 12] devoted to the fiber-optic diagnostics. In [6] proposed a method of diagnostics of aircraft’s exterior contour in flight using film of capacitors.
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Summation of visual and mechanosensory feedback in Drosophila
flight control

Summation of visual and mechanosensory feedback in Drosophila flight control

The results presented here suggest a flight control model in which each sensory channel when concurrently active is given a particular functional weight. A simple model that incorporates these results with previous findings is shown in Fig.·6. In this model, the dynamics of the two sensory channels are represented by transfer functions. These functions, determined by our previous frequency response analysis (Sherman and Dickinson, 2003), represent the input–output relationship between angular velocity and wingbeat amplitude response. Thus, they comprise multiple elements along the sensorimotor pathway, including signal transduction, sensory processing and flight muscle dynamics, each of which contributes temporal characteristics to the net response. The visual system transfer function can be approximated as a low pass filter, since only slow rotations elicit large responses. Although the haltere-mediated wingbeat response increases with increasing velocity, the gain of the system is approximately constant in the operating region, thus the transfer function can be approximated as a band pass filter (Sherman and Dickinson, 2003). The results described in the present study have provided the appropriate weighting functions for each channel; a switch can model the visual system weighting function, and a unity gain block can model the weight on the haltere signal. While this model does not provide insight into the physiology behind these interactions, it does create a framework useful for characterizing the interaction between multiple sensory feedback channels and the flight motor.
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Flight Test Results for the F-16XL With a Digital Flight Control System

Flight Test Results for the F-16XL With a Digital Flight Control System

The F-16XL ship 1 aircraft was flown with a digital flight control system (DFLCS) for the first time in December 1997. The F-16XL has its origins in the early 1980s when the General Dynamics Corporation (Ft. Worth, Texas) (now Lockheed Martin Tactical Aircraft Systems (LMTAS)) developed a prototype concept for a derivative fighter evaluation program conducted by the Air Force between 1982 and 1985. The concept was to modify the existing F-16 design to extend the fuselage length and incorporate a large area delta wing planform. The resulting F-16XL had a greater range because of increased fuel capacity in the wing tanks, and a larger load capability because of increased wing area. Two airplanes were built and extensively flight-tested (ref. 1).
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New experimental approaches to the biology of flight control systems

New experimental approaches to the biology of flight control systems

However sophisticated tethered-flight paradigms may become, it goes without saying that the natural state of flight is free flight. It does not follow, however, that free flight is necessarily natural flight – in most experimental situations, the subject will be trailing leadwires, carrying a load, flying in a wind tunnel, or simply flying in a confined space. Nevertheless, it is only possible to have the chance of identifying true closed-loop dynamics in free flight, and for this reason free-flight paradigms are likely to play an increasingly important part in our developing understanding of animal flight control. The key difficulty from a flight dynamics perspective is that the forces and moments cannot be directly measured – only the animal’s consequent motion. This is problematic because although Newton’s Second Law tells us that knowledge of mass and acceleration is equivalent to knowledge of force for a moving particle, things are more complicated for a solid body. For example, a measured roll acceleration might reflect the direct application of a roll torque, but it might also reflect a non- zero product of the angular velocity components about the pitch and yaw axes if their moments of inertia are unequal. The issues of coupling alluded to in section 2.1.2 therefore mean that it will not in general be possible to treat different degrees of freedom separately.
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The role of lateral optic flow cues in hawkmoth flight control

The role of lateral optic flow cues in hawkmoth flight control

Flying animals require sensory feedback on changes of their body position, as well as on their distance from nearby objects. The apparent image motion, or optic flow, which is generated as animals move through the air, can provide this information. Flight tunnel experiments have been crucial for our understanding of how insects use optic flow for flight control in confined spaces. However, previous work mainly focused on species from two insect orders: Hymenoptera and Diptera. We therefore set out to investigate whether the previously described control strategies to navigate enclosed environments are also used by insects with a different optical system, flight kinematics and phylogenetic background. We tested the role of lateral visual cues for forward flight control in the hummingbird hawkmoth Macroglossum stellatarum (Sphingidae, Lepidoptera), which possesses superposition compound eyes, and has the ability to hover in addition to its capacity for fast forward flight. Our results show that hawkmoths use a similar strategy for lateral position control to bees and flies in balancing the magnitude of translational optic flow perceived in both eyes. However, the influence of lateral optic flow on flight speed in hawkmoths differed from that in bees and flies. Moreover, hawkmoths showed individually attributable differences in position and speed control when the presented optic flow was unbalanced.
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Reliable Robust Sampled-Data H∞ Output Tracking Control with Application to Flight Control

Reliable Robust Sampled-Data H∞ Output Tracking Control with Application to Flight Control

As is well known, with the fast development of microprocessor and electronic technologies, digital computers are widely used to control continuous-time systems in modern control systems. For example, in a flight control system about airship (see Figure 1), a microcontroller is usually used to sample and quantize a continuous-time measurement signal, and then produce a discrete-time control input signal, which can be further converted into a continuous-time control input signal using a zero-order holder. Such control systems involve both continuous-time and discrete-time signals in continuous-time framework are referred to as sampled-data systems. Considerable research efforts have been made on various aspects of sampled-data systems, such as control systems [10-12] and filtering problems [13-15]. It is worth mentioning that little progress has been made to design controllers for uncertain sampled-data systems to make the output
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Flexible strategies for flight control: an active role for the abdomen

Flexible strategies for flight control: an active role for the abdomen

Moving animals orchestrate myriad motor systems in response to multimodal sensory inputs. Coordinating movement is particularly challenging in flight control, where animals deal with potential instability and multiple degrees of freedom of movement. Prior studies have focused on wings as the primary flight control structures, for which changes in angle of attack or shape are used to modulate lift and drag forces. However, other actuators that may impact flight performance are reflexively activated during flight. We investigated the visual–abdominal reflex displayed by the hawkmoth Manduca sexta to determine its role in flight control. We measured the open-loop stimulus–response characteristics (measured as a transfer function) between the visual stimulus and abdominal response in tethered moths. The transfer function reveals a 41  ms delay and a high-pass filter behavior with a pass band starting at ~0.5  Hz. We also developed a simplified mathematical model of hovering flight wherein articulation of the thoracic–abdominal joint redirects an average lift force provided by the wings. We show that control of the joint, subject to a high-pass filter, is sufficient to maintain stable hovering, but with a slim stability margin. Our experiments and models suggest a novel mechanism by which articulation of the body or ʻairframeʼ of an animal can be used to redirect lift forces for effective flight control. Furthermore, the small stability margin may increase flight agility by easing the transition from stable flight to a more maneuverable, unstable regime.
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Visual flight control in the honeybee

Visual flight control in the honeybee

The navigational achievements of the honeybee have for centuries fascinated apiarists, researchers and casual observers alike. The interest in honeybee navigation is due not only to their ability to fly up to ten kilometres to a food source and fly the shortest route back, but also to their ability to communicate the location of the food source to other foragers in the hive (for a review, see: von Frisch 1993). These navigational feats are made possible by the honeybee’s ability to maintain stable flight. To achieve this, honeybees must be able to control the principal forces of drag and lift by regulating both their ground speed and their ground height in a reliable way. Despite possessing a brain that contains less than one million neurons, honeybees are able to process with extraordinary accuracy all of the complex sensory information that is necessary for achieving stable flight. Honeybees overcome the limitations of their small brain by employing a range of computationally simple techniques to aid flight control and navigation. By studying the mechanisms of ground speed and ground height control in the honeybee, it is possible to gain some insight into how a small and relatively simple brain can achieve the high level of sophistication that is necessary for stable flight and navigation.
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Multi-objective design of robust flight control systems

Multi-objective design of robust flight control systems

controller gains that minimize a weighted combination of the infinite–norm of the sensitivity function (for disturbance attenuation requirements) and complementary sensitivity function (for robust stability requirements). After considering a single operating point for a level flight trim condition of a F-16 fighter aircraft model, two different approaches will then be considered to extend the domain of validity of the control law: 1) the controller is designed for different operating points and gain scheduling is adopted; 2) a single control law is designed for all the considered operating points by multiobjective minimisation. The two approaches will be an- alyzed and compared in terms of efficacy and required human and computational resources.
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Resource Localization and Multimodal Flight Control in Drosophila melanogaster

Resource Localization and Multimodal Flight Control in Drosophila melanogaster

The short-term effects of plume contact on a variety of trajectory parameters were quantified in order to extract a profile of the mean plume contact response. The time-series averages for the first episode of plume contact by each fly, aligned relative to the moment of plume contact, are plotted in Fig. 3.7. It is apparent that while there are substantial changes in a variety of these parameters following plume contact, they are often accompanied by slower changes, with the same sign, in the control group. It probably should not be surprising that similar effects are evident in both groups, simply as a result of tunnel geometry. For instance, in both groups, cross-wind velocity apparently peaked at the time of plume contact. In order to encounter the plume, an insect flying upwind needs to displace laterally (or vertically, though that is apparently less common, see Fig. 3.6), yielding an increase in cross-wind velocity. This trajectory modification is likely to evoke a collision avoidance response as the fly approaches the tunnel wall, with the resulting turn tending to be biased towards upwind as a result of the anemotactic response described earlier.
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Simple Adaptive Delta Operator Aircraft Flight Control for Accommodation of  Loss of Control Effectiveness

Simple Adaptive Delta Operator Aircraft Flight Control for Accommodation of Loss of Control Effectiveness

For the following set of simulations we introduce a wind gust disturbance of magnitude v m = 5 (ft/s) as de- scribed in Equation (44), which occurs at t = 10 sec and has a duration of 10 sec. The gust length T in Equation (44) is chosen to be to be the inverse of the natural frequency ω n of the closed loop complex eigenvalue pair of the unfailed aircraft; here ω n = 3 so that T = 1 ω n = 0.3333 sec. Here the amount of failure and weighting matrices are the same as those used in the simulations of Figure 5. The non-adaptive time responses are shown on the left side of Figure 6, where the black line corresponds to the reference model time response, the red line corresponds to a 50% elevon failure, the green line corresponds to a 50% all moving tip failure, and the blue line corresponds to a 50% yaw thrust vectoring failure. By comparing the left sides of Figure 5 and Figure 6, we can clearly see that the fixed controller performance deteriorates considerably due to the disturbance. Observe how the fixed controller, on the left side of Figure 6, starts diverging once the wind gust occurs, as can be seen in the bank angle and yaw rate outputs, and does not recover. Compare this to the response of the adaptive con- troller shown in the right side of Figure 6 which exhibits almost perfect tracking and is able to successfully ac- commodate considerable loss of control effectiveness failures even in the presence of a bounded lateral wind gust disturbance.
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Fault Tolerant Flight Control of Unmanned Aerial

Vehicles

Fault Tolerant Flight Control of Unmanned Aerial Vehicles

As mentioned before, helicopters have high manoeuvrability and hovering ability making them a suitable testbed for various missions. They are well suited to agile target tracking tasks, as well as inspection and monitoring tasks that require to maintain a position and to obtain detailed views. Furthermore, the vertical take-off and landing capabilities of he- licopters is very desirable in many applications. Helicopters are inherently unstable and dynamically fast. Even with improved stability augmentation devices, a skilled, experi- enced pilot is required to control them during flight. Autonomous helicopter control is a challenging task involving a multivariable nonlinear open-loop unstable system with actu- ator saturation. Moreover, helicopters do not have the graceful degradation properties of fixed-wing aircrafts due to direct lift-to-power characteristics as well as the inherent insta- bility. Thus, a failure in any part of the autonomous helicopter (actuators, sensors, control computer, etc.) can be catastrophic. Hence, fault-tolerant flight controllers are essential for such platforms.
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Vision-based flight control in the hawkmoth Hyles lineata

Vision-based flight control in the hawkmoth Hyles lineata

Vision is a key sensory modality for flying insects, playing an important role in guidance, navigation and control. Here, we use a virtual-reality flight simulator to measure the optomotor responses of the hawkmoth Hyles lineata, and use a published linear-time invariant model of the flight dynamics to interpret the function of the measured responses in flight stabilization and control. We recorded the forces and moments produced during oscillation of the visual field in roll, pitch and yaw, varying the temporal frequency, amplitude or spatial frequency of the stimulus. The moths’ responses were strongly depen- dent upon contrast frequency, as expected if the optomotor system uses correlation-type motion detectors to sense self-motion. The flight dynamics model predicts that roll angle feedback is needed to stabilize the lateral dynamics, and that a combination of pitch angle and pitch rate feedback is most effective in stabilizing the longitudinal dynamics. The moths’ responses to roll and pitch stimuli coincided qualitatively with these functional pre- dictions. The moths produced coupled roll and yaw moments in response to yaw stimuli, which could help to reduce the energetic cost of correcting head- ing. Our results emphasize the close relationship between physics and physiology in the stabilization of insect flight.
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Adaptive Quaternion Attitude Control of Aerodynamic Flight Control Vehicles

Adaptive Quaternion Attitude Control of Aerodynamic Flight Control Vehicles

Attitude control of flight vehicles has been a momentousissue such that a lot of publication shave been presented in this areaduring the past decades. The plenitude of attitude control be divided almost into two categories: first, the methods which control the attitude by using the physical attitude parameters such as Euler angles which sufferfrom singularity large orientation maneuvers [1,2] and second, the methods which are based on Euler axis and the fixed frame rotation with respect to that axis. singularities obstacle that were discovered in Euler angles approaches are A large number of and nonlinear control approaches are proposed to control the quaternion attitude based on minimization of some performance objectives
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Reconfigurable flight control system

Reconfigurable flight control system

The time interval over which the reconfiguration system has wrong information about the faults / failures need not be known. If the reconfiguration system eventually generates an accurate estimate of the failure parameters, the proposed approach will result in provided increased controllability and stability of airplane under adverse flight conditions. The paper obtained the transfer functions of the longitudinal motion of the aircraft taking into account the special situation of additives that will synthesize and analyze highly automated system reconfiguration control aircraft. Analysis of the results of mathematical modeling allows us to prevent the possibility of an emergency in flight due to reconfiguration of aircraft control.
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Flight mechanics and control of escape manoeuvres in hummingbirds  II  Aerodynamic force production, flight control and performance limitations

Flight mechanics and control of escape manoeuvres in hummingbirds II Aerodynamic force production, flight control and performance limitations

2); however, they imposed different requirements on neural sensing and motor control (Fig. 5). The allowable time delay for roll dynamics is approximately 60 ms for both species, significantly greater than the escape reaction time of ∼ 21 ms (magnificent hummingbird) and ∼ 29 ms (black-chinned hummingbird) (Cheng et al., 2016), which is a coarse, conservative estimate of Δt . Thus, for roll manoeuvring, observed closed-loop performance can be achieved in the presence of potential delays using a PI controller. For pitch dynamics, allowable time delays are ∼ 25 ms (magnificent hummingbird) and ∼ 32 ms (black-chinned hummingbird) (Fig. 5A,C), only slightly higher than escape reaction times. This indicates that to achieve the observed closed-loop performance, the hummingbirds may have reached performance limitations imposed by the neural delay if it is close to the estimated reaction. Although the lack of accurate component-level information on the processing of the neural system prevents us from making firm conclusions, we infer that if the actual delay was longer than 30 ms, for example, in poor ambient light, the observed performance of pitch manoeuvring cannot be achieved with the assumed PI control, and a more sophisticated controller that requires higher neural computation, such as prediction using internal models of the flight dynamics (which has been found in insect flight; e.g. Mischiati et al., 2015), could have been used by the hummingbirds. The contour of measured τ CL in Fig. 5 shows that pitch manoeuvring
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Quadrotor Helicopter Flight Dynamics and Control: Theory and Experiment

Quadrotor Helicopter Flight Dynamics and Control: Theory and Experiment

Quadrotor helicopters are emerging as a popular platform for unmanned aerial vehicle (UAV) research, due to the simplicity of their construction and maintenance, their ability to hover, and their vertical take off and landing (VTOL) capability. Current designs have often considered only nominal operating conditions for vehicle control design. This work seeks to address issues that arise when deviating significantly from the hover flight regime. Aided by well established research for helicopter flight control, three separate aerodynamic effects are investigated as they pertain to quadrotor flight, due to vehicular velocity, angle of attack, and airframe design. They cause moments that affect attitude control, and thrust variation that affects altitude control. Where possible, a theoretical development is first presented, and is then validated through both thrust test stand measurements and vehicle flight tests using the Stanford Testbed of Autonomous Rotorcraft for Multi-Agent Control (STARMAC) quadrotor helicopter. The results enabled improved controller performance.
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