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Metachronal paddling is a drag-based propulsion strategy observed in many aquatic arthropods in which a series of paddling appendages are stroked sequentially to form a traveling wave in the same direction as animal motion. Metach...
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Metachronal paddling is a drag-based propulsion strategy observed in many aquatic arthropods in which a series of paddling appendages are stroked sequentially to form a traveling wave in the same direction as animal motion. Metachronal paddling's relatively high force production makes these organisms highly agile, an attractive potential for bio-inspired autonomous underwater vehicles that is complicated by the lack of reduced order flow structure and dynamics models applicable to vehicle actuation and control design. This study uses particle image velocimetry to quantify the wake of a robot performing metachronal paddling. Then, dynamic mode decomposition is used to identify the frequency modes of the wake, which are used to reconstruct a reduced order model at Reynolds numbers of 32, 160, and 516. The results show that the kinetic energy in the metachronal paddling wake is well modeled using a superposition of the first 5 dynamic modes, and that there is typically little change in the reconstruction error when the reconstruction is performed with a higher number of dynamic modes. The low order paddling models identified using this method can be used to identify the physical mechanisms that differentiate metachronal paddling from synchronous paddling, and to develop control strategies to modulate these motions in bio-inspired autonomous underwater vehicles.
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The increase in atmospheric measurement applications of unmanned aerial systems (UAS), including the expansion to severe storm conditions involving both high wind magnitudes and high spatial and temporal derivatives, raises the qu...
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The increase in atmospheric measurement applications of unmanned aerial systems (UAS), including the expansion to severe storm conditions involving both high wind magnitudes and high spatial and temporal derivatives, raises the questions of which onboard wind estimation methods can perform well in those conditions. This paper reports on the performance of the most common wind estimation routine used during simulated flights in a tornadic wind field. This study defines a idealized tornado model and applies a spa-tiotemporal interpolation routine to obtain a tornadic wind field. In-flight wind estimation is then simulated in this field using noise characteristics of the sensors on an autopilot hardware, measured using static testing. The wind estimate error performance is quantified using root mean square error. The results suggests that these most common wind estimation routine shows significant error magnitudes in these conditions and need additional care.
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The mission endurance of micro-aerial vehicles is generally several orders of magnitude shorter than typical mission demands. These vehicles are extremely constrained in size, weight and power available, and are also highly sensit...
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The mission endurance of micro-aerial vehicles is generally several orders of magnitude shorter than typical mission demands. These vehicles are extremely constrained in size, weight and power available, and are also highly sensitive to atmospheric disturbances. Previous work has focused on quantifying and minimizing the effect of these disturbances. This paper introduces a method of maximizing the effect of the environmental disturbances and translate that into a net energy gain for the vehicle, by applying a control-theoretic framework that models the magnitude of the vehicle's disturbance and observability in conjunction with each other under a proposed "gust capture metric". A DATCOM-based flight dynamic model for a representative unmanned aerial system is used to create a non-linear simulation in Simulink. A gramian-aware speed-regulator implements the above strategy to command a speed that maximizes or minimizes the vehicle response to a sensed favorable or unfavorable vertical gust. The nonlinear simulations show an altitude gain for the vehicle with the aforementioned control law with respect to the open loop case flying over the same gust field.
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摘要 :
The mission endurance of micro-aerial vehicles is generally several orders of magnitude shorter than typical mission demands. These vehicles are extremely constrained in size, weight and power available, and are also highly sensit...
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The mission endurance of micro-aerial vehicles is generally several orders of magnitude shorter than typical mission demands. These vehicles are extremely constrained in size, weight and power available, and are also highly sensitive to atmospheric disturbances. Previous work has focused on quantifying and minimizing the effect of these disturbances. This paper introduces a method of maximizing the effect of the environmental disturbances and translate that into a net energy gain for the vehicle, by applying a control-theoretic framework that models the magnitude of the vehicle's disturbance and observability in conjunction with each other under a proposed "gust capture metric". A DATCOM-based flight dynamic model for a representative unmanned aerial system is used to create a non-linear simulation in Simulink. A gramian-aware speed-regulator implements the above strategy to command a speed that maximizes or minimizes the vehicle response to a sensed favorable or unfavorable vertical gust. The nonlinear simulations show an altitude gain for the vehicle with the aforementioned control law with respect to the open loop case flying over the same gust field.
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Reliable weather forecasting for tornadic events can be difficult due to the complex nature of how these events form. This paper aims to provide a system identification routine to estimate key parameters of a tornado based on data...
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Reliable weather forecasting for tornadic events can be difficult due to the complex nature of how these events form. This paper aims to provide a system identification routine to estimate key parameters of a tornado based on data collected from surrounding unmanned aerial systems (UAS). The UAS collect data on the wind field influenced by the tornado and identify parameters related to the size, strength, and location of the tornado. The quality of the estimates is compared with different flight maneuvers, which are used as the inputs for the system identification process. The most accurate estimates of the tornado were those that had the aircraft agents crossing different contour lines in the wind field.
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Diverse visual stimuli are being used to explore the visual control mechanisms of flies in tethered and free flight conditions. To perform a system identification of a honeybee flying position in response to a visual stimulus, an ...
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Diverse visual stimuli are being used to explore the visual control mechanisms of flies in tethered and free flight conditions. To perform a system identification of a honeybee flying position in response to a visual stimulus, an open loop experiment is demonstrated using a real-time multi camera based measurement and stimulus system. The number of recorded trajectories showing tracking response was quantified, and the tracking sections in each trajectory were isolated. Frequency domain system identification approach was applied to generate an experimental frequency response, which shows ideal tracking over the [0.1,1.7] Hz frequency band and identify a trial-dependent time delay between the moving stimulus and insect position which varies over [0.02,0.40] sec. These results suggest that honeybees achieving excellent tracking still show a diversity of time delay.
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SEASCAPE is a user-friendly autopilot code base for research and education that utilizes development and sensor boards such as Raspberry-pi and emlid Navio2. SEASCAPE leverages Internet of Things (IoTs) and open-source drivers and...
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SEASCAPE is a user-friendly autopilot code base for research and education that utilizes development and sensor boards such as Raspberry-pi and emlid Navio2. SEASCAPE leverages Internet of Things (IoTs) and open-source drivers and adds an application layer and development environment to provide an autopilot prototyping and development. The code structure is developed to handle multiple-IMU sensor integration for researchers, students, and hobbyist equally. The code allows multi-stage individual algorithm integration and provides a straightforward options to toggle between user and reference guidance, navigation, and control modules to compare and validate individual autopilot development components, allowing the user to focus on their specialization. Core functions and scripts are implemented in a multi-threaded C++ process to optimize speed performance, and additional Python processes are provided for a implementing custom estimator and controller with ease. The multi-threaded structure adds modularity to the system, allowing users to adjust the configuration via JavaScript Object Notation (JSON) properties. SEASCAPE has been continuously used in university coursework to teach and develop autopilot systems and for research purposes.
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This paper applies frequency and time domain system identification techniques to formulate a reduced order transfer function that describes the internal pneumatic dynamics within an active flow control aircraft using circulation c...
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This paper applies frequency and time domain system identification techniques to formulate a reduced order transfer function that describes the internal pneumatic dynamics within an active flow control aircraft using circulation control. This transfer function represents a simplified model of the pneumatic flow between multiple components within a pneumatic network, including supply tanks, ducting, valves, and plenum volumes. The input to this system consists of valves modulated to affect the airflow from a pre-charged supply tank, through a network of ducts, and out of an exit slot area located at the aileron of the wing. The output of the system is the momentum coefficient, C_μ, that is directly related to the localized lift generated at the aileron. Results indicate that two separate regions form within the open loop dynamics of this configuration and describe the charging and discharging of the system. Both the charging and discharging dynamics can be estimated from an identified transfer function that shows agreement with a second order system. An alternate identification method from the MATLAB system identification toolbox demonstrates agreement with a second order formulation with some phase angle differences.
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Insects navigating environments containing visual targets are used as model systems for computationally constrained micro aerial vehicles due to their visually-mediated dynamic responses to those targets, which may include adaptiv...
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Insects navigating environments containing visual targets are used as model systems for computationally constrained micro aerial vehicles due to their visually-mediated dynamic responses to those targets, which may include adaptive and time-varying controller structures. In this study, honeybees were induced to track a vertically moving target (hive entrance). To measure the trajectories, a three-camera real-time automatic tracking system was used to track and record multiple insects' three-dimensional positions and velocities. Frequency domain system identification was then used to identify the associated dynamic systems from the 3D position information. These results indicate the trajectories are described by dynamic system variation coupled with visuomotor delays distributed from 2-100 nis. The identified transfer function model structures include those with potentially challenging control design problems, including delays, non-minimum phase systems, and unstable dynamics. A model-based adaptive controller is implemented on unstable and non-minimum phase systems. The results for three different reference models show that the unstable system can follow the desired trajectories. This study serves as a structure for studying honeybee trajectory control and its relationship to adaptive control in a repeatable environment.
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This paper presents a method of identifying UAS technologies through acoustic detection. Detection is determined through a biologically inspired approach which compares the acoustic signature of an unknown system to a known refere...
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This paper presents a method of identifying UAS technologies through acoustic detection. Detection is determined through a biologically inspired approach which compares the acoustic signature of an unknown system to a known reference signature in the frequency domain. Experimental acoustic signatures were recorded in the Alfred Gessow Rotorcraft Center acoustic test chamber and used to test the efficacy of the prescribed approach. Modifications of the detection method were further made to reduce possible false positive detections. The results of both methods showed that the approach is able to distinguish between acoustic signatures produced by UAS technologies and those produced from other systems.
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