Structural Damage Identification from Limited Measurement Data

The research focused on the development of a new method to identify damaged structural elements from a large flexible space structure on-orbit, using limited measured modal data. Limited measured modal data is loosely defined as measured data containing only a few modal frequencies and less than 10% of the total structural degrees-of-freedom. This effort was decomposed into four specific tasks. The first is the identification of partial modal properties from measured data of the nominal space structure. Second, the finite element model must be adjusted to match the measured nominal partial data. The third task is an analysis of the extent to which structural damage can be localized to individual structural elements using the measured data. In conjunction with this task is the determination of where to best place the limited number of sensors on the structure. Lastly, the identification of structural damage must be performed using the limited measured modal data from a damaged space structure. Identification of the modal parameters was accomplished using the Eigensystem Realization Algorithm, a time domain based method, adopted for use with averaged measured frequency response functions. Model tuning was performed using the Automated Structural Optimization Software package, adapted for model tuning. The method minimizes a cost function based on the mismatch between the measured and analytical eigenstructure. The minimization is solved using the eigenvalue and eigen-vector sensitivities at each iteration step. The determination of prioritized sensor locations and damage localization is performed using the eigenvalue and eigenvector sensitivities

Storage and Behavior of Plant and Diet-Fed Adult Cereal Leaf Beetle, Oulema Melanopus (Coleoptera: Chrysomelidae)

The univoltine life cycle of the cereal leaf beetle Oulema melanopus (L.) in Michigan (Castro et al. 1965) is similar to that reported by Venturi (1942) in Europe. Adults emerge from pupal cells in the soil in mid-June to early July, feed voraciously for about three weeks, and enter aestivation sites. For the remainder of the summer and early autumn only a few adults can be found feeding on late-maturing native grasses. The beetles overwinter and usually emerge in late March to early April and resume feeding. Mating and oviposition occur, and larval development is usually completed by late June in southern Michigan. Techniques for rearing the cereal leaf beetle on greenhouse-grown small grain seedlings have been developed by Connin, et al. (1968). Maintaining these cultures requires collecting field adults, growing host material, and handling the cultures to insure that all stages will be available for study. In Michigan during July adults can be collected more economically and in greater numbers in the field than by rearing in the laboratory. A summary of collection techniques, laboratory feeding and storage conditions for large numbers of field-collected cereal leaf beetles is presented in this paper. In addition, the mortality during storage of newly emerged field collected beetles fed either barley seedlings or an artificial diet is compared

Passive Rotation Joint Design Considerations for Lift and Thrust Generation for a Biomimetic Flapping Wing

Maximizing the available lift and thrust force is important for designing efficient flapping wing micro air vehicles. Research to date showed the passive rotation joint between the wing and four-bar linkage is an important design aspect. Two key hinge parameters are the angle of attack stop and passive rotation joint stiffness. In this work these design parameters were independently varied. Their impact on lift and thrust force generation, and the ratio of the first and second system resonance frequencies were measured and compared through experiments utilizing prototype hardware of varying design. The prototype hardware and flapping wing controller is based on previous work, focused on using biomimetic wings combined with a design that only requires two piezoelectric actuators, and will be briefly reviewed. The angle of attack stops tested were 30°, 40°, 45°, 50°, and 60°. Five different passive rotation joints were tested of varying stiffness. Optimal angle of attack stops and passive rotation joint designs were found from the experimental results and combined into a best design, which was tested and compared to the optimal results from the independent designs. Results show that while individual selection of angle stop and passive rotation joint stiffness can be optimized, the intersection between the two precludes simply choosing the best of both as the best combined

Experimental Structural Dynamic Characterization of the Hawkmoth (ManducaSexta) Forewing

While many bio-inspired flapping wing micro air vehicle wing designs continue to be conceived and studied in earnest, a general consensus of which physical attributes of the biological entity are important for flight is still at-large. It is proposed herein that the eigenstructure of the wing should figure prominently among rigorous engineering metrics for guiding flapping wing micro air vehicle wing designs at the scales of large insects. With virtually no compelling work done in this area to date, the method and results of system identification tests for the forewings of a representative sample of hawkmoth (Manduca Sexta) are presented, revealing the underlying structural nature of this incredibly agile flyer\u27s wings. Despite their inherent biological variability, these wings show very little variability in eigenstructure which may suggest it as a critical attribute for robust flight. Further supporting this hypothesis, the wings of four other insect species are briefly examined and show remarkable similarity with the hawkmoth wing\u27s eigenstructure

An Experimental Investigation into the Effect of Flap Angles for a Piezo-Driven Wing

This article presents a comparison of results from six degree of freedom force and moment measurements and Particle Image Velocimetry (PIV) data taken on the Air Force Institute of Technology\u27s (AFIT) piezoelectrically actuated, biomimetically designed Hawkmoth, Manduca Sexta, class engineered wing, at varying amplitudes and flapping frequencies, for both trimmed and asymmetric flapping conditions to assess control moment changes. To preserve test specimen integrity, the wing was driven at a voltage amplitude 50% below the maximum necessary to achieve the maximal Hawkmoth total stroke angle. 86 and 65 stroke angles were achieved for the trimmed and asymmetric tests respectively. Flapping tests were performed at system structural resonance, and at 10% off system resonance at a single amplitude, and PZT power consumption was calculated for each test condition. Two-dimensional PIV visualization measurements were taken transverse to the wing planform, recorded at the mid-span, for a single frequency and amplitude setting, for both trimmed and asymmetric flapping to correlate with the 6-DoF balance data. Linear velocity data was extracted from the 2-D PIV imagery at 1/2 and 1 chord locations above and below the wing, and the mean velocities were calculated for four separate wing phases during the flap cycle. The mean forces developed during a flap cycle were approximated using a modification of the Rankine-Froude axial actuator disk model to calculate the transport of momentum flux as a measure of vertical thrust produced during a static hover flight condition. Values of vertical force calculated from the 2-D PIV measurements were within 20% of the 6-DOF force balance experiments. Power calculations confirmed flapping at system resonance required less power than at off resonance frequencies, which is a critical finding necessary for future vehicle design considerations

Simplex Solutions for Optimal Control Flight Paths in Urban Environments

This paper identifies feasible fight paths for Small Unmanned Aircraft Systems in a highly constrained environment. Optimal control software has long been used for vehicle path planning and has proven most successful when an adequate initial guess is presented flight to an optimal control solver. Leveraging fast geometric planning techniques, a large search space is discretized into a set of simplexes where a Dubins path solution is generated and contained in a polygonal search corridor free of path constraints. Direct optimal control methods are then used to determine the optimal flight path through the newly defined search corridor. Two scenarios are evaluated. The first is limited to heading rate control only, requiring the air vehicle to maintain constant speed. The second allows for velocity control which permits slower speeds, reducing the vehicles minimum turn radius and increasing the search domain. Results illustrate the benefits gained when including speed control to path planning algorithms by comparing trajectory and convergence times, resulting in a reliable, hybrid solution method to the SUAS constrained optimal control problem

Stochastic Real-time Optimal Control for Bearing-only Trajectory Planning

A method is presented to simultaneously solve the optimal control problem and the optimal estimation problem for a bearing-only sensor. For bearing-only systems that require a minimum level of certainty in position relative to a source for mission accomplishment, some amount of maneuver is required to measure range. Traditional methods of trajectory optimization and optimal estimation minimize an information metric. This paper proposes constraining the final value of the information states with known time propagation dynamics relative to a given trajectory which allows for attainment of the required level of information with minimal deviation from a general performance index that can be tailored to a specific vehicle. The proposed method does not suffer from compression of the information metric into a scalar, and provides a route that will attain a particular target estimate quality while maneuvering to a desired relative point or set. An algorithm is created to apply the method in real-time, iteratively estimating target position with an Unscented Kalman Filter and updating the trajectory with an efficient pseudospectral method. Methods and tools required for hardware implementation are presented that apply to any real-time optimal control (RTOC) system. The algorithm is validated with both simulation and flight test, autonomously landing a quadrotor on a wire

Storage and Behavior of Plant and Diet-Fed Adult Cereal Leaf Beetle, Oulema Melanopus (Coleoptera: Chrysomelidae)

The univoltine life cycle of the cereal leaf beetle Oulema melanopus (L.) in Michigan (Castro et al. 1965) is similar to that reported by Venturi (1942) in Europe. Adults emerge from pupal cells in the soil in mid-June to early July, feed voraciously for about three weeks, and enter aestivation sites. For the remainder of the summer and early autumn only a few adults can be found feeding on late-maturing native grasses. The beetles overwinter and usually emerge in late March to early April and resume feeding. Mating and oviposition occur, and larval development is usually completed by late June in southern Michigan. Techniques for rearing the cereal leaf beetle on greenhouse-grown small grain seedlings have been developed by Connin, et al. (1968). Maintaining these cultures requires collecting field adults, growing host material, and handling the cultures to insure that all stages will be available for study. In Michigan during July adults can be collected more economically and in greater numbers in the field than by rearing in the laboratory. A summary of collection techniques, laboratory feeding and storage conditions for large numbers of field-collected cereal leaf beetles is presented in this paper. In addition, the mortality during storage of newly emerged field collected beetles fed either barley seedlings or an artificial diet is compared

Implementing Conditional Inequality Constraints for Optimal Collision Avoidance

Current Federal Aviation Administration regulations require that passing aircraft must either meet a specified horizontal or vertical separation distance. However, solving for optimal avoidance trajectories with conditional inequality path constraints is problematic for gradient-based numerical nonlinear programming solvers since conditional constraints typically possess non-differentiable points. Further, the literature is silent on robust treatment of approximation methods to implement conditional inequality path constraints for gradient-based numerical nonlinear programming solvers. This paper proposes two efficient methods to enforce conditional inequality path constraints in the optimal control problem formulation and compares and contrasts these approaches on representative airborne avoidance scenarios. The first approach is based on a minimum area enclosing superellipse function and the second is based on use of sigmoid functions. These proposed methods are not only robust, but also conservative, that is, their construction is such that the approximate feasible region is a subset of the true feasible region. Further, these methods admit analytically derived bounds for the over-estimation of the infeasible region with a demonstrated maximum error of no greater than 0.3% using the superellipse method, which is less than the resolution of typical sensors used to calculate aircraft position or altitude. However, the superellipse method is not practical in all cases to enforce conditional inequality path constraints that may arise in the nonlinear airborne collision avoidance problem. Therefore, this paper also highlights by example when the use of sigmoid functions are more appropriate

A Hybrid Technique applied to the Intermediate-Target Optimal Control Problem

The DoD has introduced the concept of Manned-Unmanned Teaming, a subset of which is the loyal wingman. Optimal control techniques have been proposed as a method for rapidly solving the intermediate-target (mid-point constraint) optimal control problem. Initial results using direct orthogonal collocation and a gradient-based method for solving the resulting nonlinear program reveals a tendency to converge to or to get `stuck’ in locally optimal solutions. The literature suggested a hybrid technique in which a particle swarm optimization is used to quickly find a neighborhood of a more globally minimal solution, at which point the algorithm switches to a gradient-based nonlinear programming solver to converge on the globally optimal solution. The work herein applies the hybrid optimization technique to rapidly solve the loyal wingman optimal control problem. After establishing the background and describing the loyal wingman particle swarm optimization algorithm, the problem is solved first using the gradient-based direct orthogonal collocation method, then re-solved using a hybrid approach in which the results of the particle swarm optimization algorithm are used as the initial guess for the gradient-based direct orthogonal collocation method. Results comparing the final trajectory and convergence time, demonstrate the hybrid technique as a reliable method for producing rapid, autonomous, and feasible solutions to the loyal wingman optimal control problem