A Comparison of Flight Control Strategies for Hypersonic Reentry Vehicles with Lateral-Directional Coupling Dynamics

2018 ◽  
Author(s):  
Ding Jiayuan ◽  
Tang Peng ◽  
Zhang Shuguang ◽  
Liu Tao
Keyword(s):  
Flight Control ◽  
Control Strategies ◽  
Directional Coupling ◽  
Reentry Vehicles ◽  
Coupling Dynamics

scholarly journals Stator Fixed Deadbeat Predictive Torque and Flux Control of a PMSM Drive with Modulated Duty Cycle

Energies ◽  
2021 ◽  
Vol 14 (10) ◽  
pp. 2769
Author(s):  
Omar Sandre Hernandez ◽  
Jorge S. Cervantes-Rojas ◽  
Jesus P. Ordaz Oliver ◽  
Carlos Cuvas Castillo
Keyword(s):  
Duty Cycle ◽  
Reference Frames ◽  
Control Strategies ◽  
Synchronous Machines ◽  
Permanent Magnet Synchronous Machines ◽  
Flux Control ◽  
Voltage Vector ◽  
Parameter Variations ◽  
Coupling Dynamics ◽  
Stationary Reference Frame

Conventional deadbeat control strategies for permanent magnet synchronous machines (PMSMs) are commonly developed reference frames, however, coupling dynamics affect the performance drive, and rotational transformations are required for the synthesis of the final voltage vector (VV). To improve robustness against parameter variations and to directly synthesize the reference voltage vector, in this paper a deadbeat predictive torque and flux control for a PMSM is presented. The proposed controller is developed in the stationary reference frame (α−β). First, the reference VV is obtained from a predictive deadbeat controller. Then, the reference VV is applied to the power inverter by the combination of two voltage vectors. A duty cycle optimization is employed to calculate the required time for the application of each voltage vector. Experimental results based on an FPGA and a comparison of the conventional and the proposed deadbeat controller are presented to validate the proposed methodology.

Modeling and control for ultra-low altitude cargo airdrop

2018 ◽  
Vol 90 (1) ◽  
pp. 219-228
Author(s):  
Yanhua Han
Keyword(s):  
Numerical Simulation ◽  
Flight Control ◽  
Control Law ◽  
Dynamics Model ◽  
Aerodynamic Coefficients ◽  
Content Type ◽  
Coupling Dynamics ◽  
Low Altitude ◽  
And Control ◽  
Kane Method

Purpose The purpose of this paper is to model the aircraft-cargo’s coupling dynamics during ultra-low altitude heavy cargo airdrop and to design the aircraft’s robust flight control law counteracting its aerodynamic coefficients perturbation induced by ground effect and the disturbance from the sliding cargo inside. Design/methodology/approach Aircraft-cargo system coupling dynamics model in vertical plane is derived using the Kane method. Trimmed point is calculated when the cargo fixed in the cabin and then the approximate linearized motion equation of the aircraft upon it is derived. The robust stability and robust H∞ optimal disturbance restraint flight control law are designed countering the aircraft’s aerodynamic coefficients perturbation and the disturbance moment, respectively. Findings Numerical simulation shows the effectiveness of the proposed control law with elevator deflection as a unique control input. Practical implications The model derived and control law designed in the paper can be applied to heavy cargo airdrop integrated design and relevant parameters choice. Originality/value The dynamics model derived is closed, namely, the model can be called in numerical simulation free of assuming the values of parachute’s extraction force or cargo’s relative sliding acceleration or velocity as seen in many literatures. The modeling is simplified using Kane method rather than Newton’s laws. The robust control law proposed is effective in guaranteeing the aircraft’s flight stability and disturbance restraint performance in the presence of aerodynamic coefficients perturbation.

scholarly journals Sensory processing by motoneurons: a numerical model for low-level flight control in flies

2018 ◽  
Vol 15 (145) ◽  
pp. 20180408 ◽  
Author(s):  
Jan Bartussek ◽  
Fritz-Olaf Lehmann
Keyword(s):  
Numerical Model ◽  
Sensory Processing ◽  
Flight Control ◽  
Muscle Activation ◽  
Muscle Power ◽  
Control Strategies ◽  
Underlying Mechanism ◽  
Cellular Level ◽  
Central Brain ◽  
Experimental Findings

Rhythmic locomotor behaviour in animals requires exact timing of muscle activation within the locomotor cycle. In rapidly oscillating motor systems, conventional control strategies may be affected by neural delays, making these strategies inappropriate for precise timing control. In flies, wing control thus requires sensory processing within the peripheral nervous system, circumventing the central brain. The underlying mechanism, with which flies integrate graded depolarization of visual interneurons and spiking proprioceptive feedback for precise muscle activation, is under debate. Based on physiological parameters, we developed a numerical model of spike initiation in flight muscles of a blowfly. The simulated Hodgkin–Huxley neuron reproduces multiple experimental findings and explains on the cellular level how vision might control wing kinematics. Sensory processing by single motoneurons appears to be sufficient for control of muscle power during flight in flies and potentially other flying insects, reducing computational load on the central brain during body posture reflexes and manoeuvring flight.

scholarly journals Gull-inspired joint-driven wing morphing allows adaptive longitudinal flight control

2021 ◽  
Vol 18 (179) ◽  
pp. 20210132
Author(s):  
C. Harvey ◽  
V. B. Baliga ◽  
C. D. Goates ◽  
D. F. Hunsaker ◽  
D. J. Inman
Keyword(s):  
Flight Control ◽  
Control Strategies ◽  
Three Dimensional ◽  
Aerodynamic Characteristics ◽  
Pitching Moment ◽  
Motion Trajectories ◽  
Aerodynamic Properties ◽  
Aerial Vehicle ◽  
Wing Morphing ◽  
Lifting Line

Birds dynamically adapt to disparate flight behaviours and unpredictable environments by actively manipulating their skeletal joints to change their wing shape. This in-flight adaptability has inspired many unmanned aerial vehicle (UAV) wings, which predominately morph within a single geometric plane. By contrast, avian joint-driven wing morphing produces a diverse set of non-planar wing shapes. Here, we investigated if joint-driven wing morphing is desirable for UAVs by quantifying the longitudinal aerodynamic characteristics of gull-inspired wing-body configurations. We used a numerical lifting-line algorithm (MachUpX) to determine the aerodynamic loads across the range of motion of the elbow and wrist, which was validated with wind tunnel tests using three-dimensional printed wing-body models. We found that joint-driven wing morphing effectively controls lift, pitching moment and static margin, but other mechanisms are required to trim. Within the range of wing extension capability, specific paths of joint motion (trajectories) permit distinct longitudinal flight control strategies. We identified two unique trajectories that decoupled stability from lift and pitching moment generation. Further, extension along the trajectory inherent to the musculoskeletal linkage system produced the largest changes to the investigated aerodynamic properties. Collectively, our results show that gull-inspired joint-driven wing morphing allows adaptive longitudinal flight control and could promote multifunctional UAV designs.

Flight Control Strategies for Performance Computers

Navigation ◽  
1980 ◽  
Vol 27 (2) ◽  
pp. 132-141
Author(s):  
J. M. H. BRUCKNER ◽  
J. S. SADOWSKY
Keyword(s):  
Flight Control ◽  
Control Strategies

Image Schema Based Landing and Navigation for Rotorcraft MAV-s

2015 ◽  
Author(s):  
Eniko T. Enikov ◽  
Juan-Antonio Escareno ◽  
Micky Rakotondrabe
Keyword(s):  
Flight Control ◽  
Learning Algorithm ◽  
Control Strategies ◽  
Micro Air Vehicles ◽  
The Body ◽  
Navigation Systems ◽  
Image Schemas ◽  
Gradient Based ◽  
Artificial Neural ◽  
Artificial Neural Network Ann

To date, most autonomous micro air vehicles (MAV-s) operate in a controlled environment, where the location of and attitude of the aircraft are measured with an infrared (IR) tracking systems. If MAV-s are to ever exit the lab, their flight control needs to become autonomous and based on on-board image and attitude sensors. To address this need, several groups are developing monocular and binocular image based navigation systems. One of the challenges of these systems is the need for exact calibration in order to determine the vehicle’s position and attitude through the solution of an inverse problem. Body schemas are a biologically-inspired approach, emulating the plasticity of the animal brain, which allows it to learn non-linear mappings between the body configurations, i.e. its generalized coordinates and the resulting sensory outputs. The advantages of body schemas has long been recognized in the cognitive robotic literature and resulting studies on human-robot interactions based on artificial neural networks, however little effort has been made so far to develop avian-inspired flight control strategies utilizing body and image schemas. This paper presents a numerical experiment of controlling the trajectory of a miniature rotorcraft during landing maneuvers suing the notion of body and image schemas. More specifically, we demonstrate how trajectory planning can be executed in the image space using gradient-based maximum seeking algorithm of a pseudo-potential. It is demonstrated that a neural-gas type artificial neural network (ANN), trained through Hebbian-type learning algorithm, can be effective in learning a mapping between the rotorcraft’s position/attitude and the output of its vision sensors. Numerical simulation of the landing performance, including resulting landing errors are presented using an experimentally validated rotorcraft model.

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