Flight muscles and flight dynamics: towards an integrative framework

2005 ◽  
Vol 55 (1) ◽  
pp. 81-99 ◽  
Author(s):  
Graham Taylor
Keyword(s):  
Flight Control ◽  
Orbital Stability ◽  
Flight Dynamics ◽  
Flapping Flight ◽  
Reference State ◽  
Muscle Physiology ◽  
Body Parts ◽  
Integrative Framework ◽  
Flight Muscles ◽  
Neural Feedback

AbstractHere a conceptual framework is provided for analysing the role of the flight muscles in stability and control. Stability usually refers to the tendency of a system to return to a characteristic reference state, whether static, as in gliding, or oscillatory, as in flapping. Asymptotic Lyapunov stability and asymptotic orbital stability as formal definitions of gliding and flapping flight stability, respectively, are discussed and a limit cycle control analogy for flapping flight control proposed. Stability can arise inherently or through correctional control. Conceptually, inherent stability is that which would arise if all body parts were rigid and all articulation angles were constants (gliding) or periodic functions (flapping), both of which require muscular effort. Pose can be maintained during disturbances by neural feedback or isometric contraction of tonic muscles: cyclic pose changes can be buffered by neural feedback or viscous damping by phasic muscles. Correctional control serves to drive the system towards its reference state, which will usually involve a phasic response, if only because of the tendency of flying bodies to oscillate during disturbances. Muscles involved in correctional control must therefore be tuned to the characteristic frequencies of the system. Furthermore, in manoeuvre control, these frequencies set an upper limit on the timescales on which control inputs can be effective. Flight muscle physiology should therefore be evolutionarily co-tuned with the morphological parameters of the system that determine its frequency response. Understanding this fully will require us to integrate internal models of physiology with external models of flight dynamics.

Integrated Aircraft Modeling Research for Accurate Flight Control System Design

2013 ◽  
Vol 791-793 ◽  
pp. 658-662
Author(s):  
Chao Zhang ◽  
Yi Nan Liu ◽  
Jian Hui Xu
Keyword(s):  
Control System ◽  
System Design ◽  
Flight Control ◽  
Time Delays ◽  
Flight Dynamics ◽  
Control System Design ◽  
Control Law ◽  
Flight Control System ◽  
Aircraft Model ◽  
Simulation Results

In order to realize accurate flight control system design and simulation, an integrated scheme of aircraft model which consists of flight dynamics, fly-by-wire (FBW) platform and flight environment is proposed. Flight environment includes gravity, wind, and atmosphere. And the actuator and sensors such as gyroscope and accelerometer models are considered in the FBW platform. All parts of the integrated model are closely connected and interacted with each other. Simulation results confirm the effectiveness of the integrated aircraft model and also indicate that the (Flight Control Law) FCL must be designed with robustness to sensor noise and time delays with the FBW platform in addition to the required robustness to model uncertainty in flight dynamics.

scholarly journals Vision-based flight control in the hawkmoth Hyles lineata

2014 ◽  
Vol 11 (91) ◽  
pp. 20130921 ◽  
Author(s):  
Shane P. Windsor ◽  
Richard J. Bomphrey ◽  
Graham K. Taylor
Keyword(s):  
Flight Control ◽  
Insect Flight ◽  
Linear Time ◽  
Temporal Frequency ◽  
Sensory Modality ◽  
Flight Dynamics ◽  
Energetic Cost ◽  
Linear Time Invariant ◽  
Hyles Lineata ◽  
And Control

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 dependent 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 predictions. The moths produced coupled roll and yaw moments in response to yaw stimuli, which could help to reduce the energetic cost of correcting heading. Our results emphasize the close relationship between physics and physiology in the stabilization of insect flight.

Collision avoidance within flight dynamics constraints for UAV applications

2005 ◽  
Vol 109 (1094) ◽  
pp. 193-199 ◽  
Author(s):  
R. W. Penney
Keyword(s):  
Control Systems ◽  
Collision Avoidance ◽  
Flight Control ◽  
Flight Dynamics ◽  
Moving Obstacles ◽  
Temporal Features ◽  
Geometrical Shapes ◽  
Spatio Temporal ◽  
Temporal Trajectory ◽  
Optimisation Technique

Abstract Avoiding collisions with other aircraft is an absolutely fundamental capability for semi-autonomous UAVs. However, an aircraft avoiding moving obstacles requires an evasive tactic that is simultaneously very quick to compute, compatible with the platform’s flight dynamics, and deals with the subtle spatio-temporal features of the threat. We will give an overview of a novel prototype method of rapidly generating smooth flight-paths constrained to avoid moving obstacles, using an efficient trajectory-optimisation technique. Obstacles are described in terms of simple geometrical shapes, such as ellipsoids, whose centres and shapes can vary with time. The technique generates a spatio-temporal trajectory which offers a high likelihood of avoiding the volume in space-time excluded by the predicted motion of each of the known obstacles. Such a flight-path could then be passed to the aircraft’s flight-control systems to negotiate the threat posed by the obstacles. Results from a demonstration implementation of the collision-avoidance technique will be discussed, including non-trivial scenarios handled well within 100ms on a 300MHz processor.

scholarly journals Timing precision in fly flight control: integrating mechanosensory input with muscle physiology

2020 ◽  
Vol 287 (1941) ◽  
pp. 20201774
Author(s):  
Bradley H. Dickerson
Keyword(s):  
Motor Neurons ◽  
Flight Control ◽  
Neural Circuit ◽  
Biomechanical Properties ◽  
Steering System ◽  
Spike Timing ◽  
Muscle Physiology ◽  
Mechanical Power Output ◽  
Essential Input ◽  
Length Changes

Animals rapidly collect and act on incoming information to navigate complex environments, making the precise timing of sensory feedback critical in the context of neural circuit function. Moreover, the timing of sensory input determines the biomechanical properties of muscles that undergo cyclic length changes, as during locomotion. Both of these issues come to a head in the case of flying insects, as these animals execute steering manoeuvres at timescales approaching the upper limits of performance for neuromechanical systems. Among insects, flies stand out as especially adept given their ability to execute manoeuvres that require sub-millisecond control of steering muscles. Although vision is critical, here I review the role of rapid, wingbeat-synchronous mechanosensory feedback from the wings and structures unique to flies, the halteres. The visual system and descending interneurons of the brain employ a spike rate coding scheme to relay commands to the wing steering system. By contrast, mechanosensory feedback operates at faster timescales and in the language of motor neurons, i.e. spike timing, allowing wing and haltere input to dynamically structure the output of the wing steering system. Although the halteres have been long known to provide essential input to the wing steering system as gyroscopic sensors, recent evidence suggests that the feedback from these vestigial hindwings is under active control. Thus, flies may accomplish manoeuvres through a conserved hindwing circuit, regulating the firing phase—and thus, the mechanical power output—of the wing steering muscles.

Robust Backstepping Control for Longitudinal Flight Dynamics

2013 ◽  
Vol 300-301 ◽  
pp. 1589-1592
Author(s):  
Ming Suo Li ◽  
Mou Chen ◽  
Rong Mei
Keyword(s):  
Flight Control ◽  
Sliding Mode ◽  
External Disturbance ◽  
Flight Dynamics ◽  
Backstepping Technique ◽  
Control Performance ◽  
Sliding Mode Disturbance Observer ◽  
Control Scheme ◽  
Simulation Results ◽  
Robust Flight Control

In this paper, the robust longitudinal flight control is developed for the fighter using the backstepping technique. To improve the robust control performance for the unknown external disturbance, the sliding mode disturbance observer is employed to estimate the unknown external disturbance. Utilizing the disturbance estimate output, the robust backstepping flight control scheme is proposed for the fighter with the unknown external disturbance. Finally, simulation results are given to show the effectiveness of the proposed robust flight control scheme for longitudinal flight dynamics.

scholarly journals Identification of Aeroelastic Models for the X-56A Longitudinal Dynamics Using Multisine Inputs and Output Error in the Frequency Domain

Aerospace ◽  
2019 ◽  
Vol 6 (2) ◽  
pp. 24 ◽  
Author(s):  
Jared Grauer ◽  
Matthew Boucher
Keyword(s):  
System Identification ◽  
Test Data ◽  
Flight Control ◽  
Fourier Transforms ◽  
Flight Dynamics ◽  
Flight Test ◽  
Multiple Control ◽  
Output Error ◽  
Short Period ◽  
Flight Dynamics Model

System identification from measured flight test data was conducted using the X-56A aeroelastic demonstrator to identify a longitudinal flight dynamics model that included the short period, first symmetric wing bending, and first symmetric wing torsion modes. Orthogonal phase-optimized multisines were used to simultaneously excite multiple control effectors while a flight control system was active. Non-dimensional stability and control derivatives parameterizing an aeroelastic model were estimated using the output-error approach to match Fourier transforms of measured output response data. The predictive capability of the identified model was demonstrated using other flight test data with different inputs and at a different flight conditions. Modal characteristics of the identified model were explored and compared with other predictions. Practical aspects of the experiment design and system identification analysis, specific to flexible aircraft, are also discussed. Overall, the approach used was successful for identifying aeroelastic flight dynamics models from flight test data.

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