Andrew Kurdila

Morphing Wing Micro-Air-Vehicles via Macro-Fiber- Composite Actuators

*† ‡ § ** The design and implementation of a morphing unmanned aircraft using smart materials is presented. Articulated lifting surfaces and articulated wing sections actuated by servos are difficult to instrument and fabricate in a repeatable fashion on thin, composite wing microair-vehicles. Assembly is complex and time consuming. A type of piezoceramic composite actuator commonly known as Macro Fiber Composite is used for wing morphing. The actuation capability of this actuator on fiberglass unimorph was quantified by experimentation. Wind tunnel tests were performed to compare conventional trailing edge control surface effectiveness to an MFC actuated wing section. The continuous surface of the MFC actuated composite wing produced lower drag and wider actuation bandwidth. The MFC actuators were implemented on a 0.76 m wingspan aircraft. The remotely piloted experimental vehicle was flown using two MFC patches in an elevator/aileron (elevon) configuration. Preliminary testing has proven the stability and control of the design. I. Introduction This study investigates the use of macro fiber composites (MFCs) to control the roll and pitch maneuvers of micro air vehicles (MAVs). Design, manufacturing, and the control of MAVs in unsteady aerodynamic loading remain an active area of interest to researchers. The authors aim to understand the behavior of MFC actuated micro air vehicles under low speed, quasi steady air flow. Wind tunnel tests were conducted to quantify the effectiveness of MFC actuators. Results show that MFC actuation does have improved efficiency over a conventional control surface. The main goal for these experiments was to show the improved performance of a variable camber airfoil compared to a conventional control surface at low Reynolds Numbers. An experimental MAV designed and built by the authors was used as a test platform for the morphing wing concept. This paper first covers the background of the research. The next section presents the wind tunnel experimentation setup and test results. Next, the experimental aircraft design and initial flight results are presented. The paper concludes with a summary of results and discussion of future work.

L 1 adaptive controller for air-breathing hypersonic vehicle with flexible body dynamics

This paper presents a modified nonlinear longitudinal model for an air-breathing hypersonic vehicle and the design of an L1 adaptive controller for it. It is assumed that the mid-fuselage is a rigid-body, while the aft-fuselage is linearly elastic, and a rigid all-movable elevator is fixed at the end of the aft-fuselage. In the resulting mathematical model, the pitching moment depends not only on the control surface position, but also on the rate and acceleration of the control surface motion. For compensation of the modeling uncertainties including the flexible dynamics, the L1 adaptive control architecture is considered in this paper. It has a low-pass filter in the feedback loop allowing for arbitrarily fast adaptation with guaranteed robustness and transient performance for systems input and output signals. Simulation results demonstrate the benefits of the method.

Asymptotic Tracking of Uncertain Systems With Continuous Control Using Adaptive Bounding

This paper presents a robust adaptive control design method for a class of multiple-input-multiple-output uncertain nonlinear systems in the presence of parametric and nonparametric uncertainties and bounded disturbances. Using the approximation properties of the unknown continuous nonlinearities and the adaptive bounding technique, the developed controller achieves asymptotic convergence of the tracking error to zero, while ensuring boundedness of parameter estimation errors. The algorithm does not assume the knowledge of any bound on the unknown quantities in designing the controller. It is based on an integral technique involving the filtered tracking error and produces a continuous control. Theoretical developments are illustrated via simulation results.

Morphing wing aerodynamic control via macro-fiber-composite actuators in an unmanned aircraft

*† ‡ § ** An experimental, theoretical and computational evaluation of a remotely piloted morphing wing aircraft using smart materials is presented. A type of piezoceramic composite actuator commonly known as Macro Fiber Composite is used for wing morphing. The MFC actuators were implemented on a swept wing, 0.76 m wingspan aircraft. The experimental vehicle was flown using two MFC patches in an elevator/aileron (elevon) configuration. Preliminary testing has proven the stability and control of the design which was presented in the authors’ previous work. Flight tests were performed to quantify roll control using the actuators. Force and moment coefficients were measured in a lowspeed, open section wind tunnel, and a vortex lattice analysis complemented the database of aerodynamic derivatives used to analyze control response. The continuous surface of the MFC actuated composite wing produced lower drag and wider actuation bandwidth.

A receding horizon controller for motion planning in the presence of moving obstacles

We address the minimal risk motion planning problem in a two dimensional environment in the presence of both moving and static obstacles. Our approach is inspired by recent results due to Vladimirsky [20] in which path planning on time-varying maps is addressed using a new level-set approach, and for which computational costs are remarkably low. Toward practical implementation of these results for path planning in unstructured environments, we develop a receding-horizon formulation in which path planning for moving and static obstacles is addressed locally, while path planning for static obstacles is addressed globally. This formulation reduces the overall computational burden of path planning and makes it suitable for very large domains. The result is a suboptimal receding horizon planner and a matching condition that connects local planning with global planning. We present a rigorous analysis from which convergence to a desired endpoint is guaranteed.

Vision-based geometry estimation and receding horizon path planning for UAVs operating in urban environments

This paper presents a receding horizon control strategy to enable small unmanned air vehicles to fly autonomously through complex urban environments. An adaptive, multiresolution-based learning algorithm is employed to estimate the 3D geometry of the environment. This learning algorithm generates an adaptive approximation based on measurements of the 3D positions of static points in the environment, obtained via feature point tracking and structure from motion. A receding horizon path planning strategy is used to select a series of locally-optimal path points in front of the vehicle. These path points are selected in such a manner that the vehicle approaches an overall target point while avoiding static obstacles that may lie in its path. These obstacles are estimated via the adaptive learning algorithm, which provides constraints for the path planner. A standard waypoint controller is then used to fly the vehicle through the selected path points. This vision-based control strategy is demonstrated in simulations of a small UAV flying through a virtual urban environment

Fast Path Re-planning Based on Fast Marching and Level Sets

We investigate path planning algorithms that are based on level set methods for applications in which the environment is static, but where an a priori map is inaccurate and the environment is sensed in real-time. Our principal contribution is not a new path planning algorithm, but rather a formal analysis of path planning algorithms based on level set methods. Computational costs when planning paths with level set methods are due to the creation of the level set function. Once the level set function has been computed, the optimal path is simply gradient descent down the level set function. Our approach rests on the formal analysis of how value of the level set function changes when the changes in the environment are detected. We show that in many practical cases, only a small domain of the level set function needs to be re-computed when the environment changes. Simulation examples are presented to validate the effectiveness of the proposed method.

Adaptive control for bioinspired flapping wing robots

This paper derives the governing equations of motion for a flapping wing robot that is used to study and synthesize bio-inspired closed loop control laws. Lagranges equations are employed to derive the geometrically nonlinear equations of motion. The Denavit-Hartenberg convention is used to model the wing flapping kinematics and the aerodynamic loads are represented using quasi-steady models of aerodynamics over each of the wing sections. The governing system is then cast in terms of a standard first order system with matched uncertainties that are due to the aerodynamic contributions. The closed loop control drives the system states such that they asymptotically track trajectories obtained from experimental observations of flapping wings of birds. Convergence and asymptotic stability of the tracking error closed loop dynamics is discussed. Finally, sufficient conditions are discussed under which the Lyapunov analysis guarantees identification of the aerodynamic loads, a topic of great interest to the research community investigating the aerodynamics of flapping flight.

A receding horizon approach to generating dynamically feasible plans for vehicles that operate over large areas

We present an approach to planning dynamically feasible vehicle trajectories for applications where the vehicle operates in very large environments and for which a kinematic model is poor approximation of the vehicles dynamics. Using a standard receding horizon control framework, we compute a sequence of short-horizon optimal trajectories that can be computed in real-time. We also compute a global path that is updated only occasionally. Because the environment is very large, we presume that the global path cannot be updated in real-time. By selecting a terminal state cost in the finite-time optimal control problem that approximates the cost-to-go, we are able to propose a formal condition under which the sequence of dynamically feasible trajectories is guaranteed to converge to a desired goal location. Moreover, we show that the global path need be updated only when the formal condition is not satisfied, which allows us to delay update of the global path.

A graph theoretical approach toward a switched feedback controller for pursuit-evasion scenarios

This research introduces a novel method for constructing a switched feedback control system to be used for an autonomous agent. The state space is partitioned into sets of states where a specific control is applied. Each partition is represented by nodes of a digraph where the success of the control in traversing the partitions is represented by a connecting edge. Using the concept of capture sets in the field of differential games, it is shown that a set of states included in a particular partition is capable of reaching the target set if the eigenvalues of the adjacency matrix representing the digraph are all zero and none of the partitions are invariant. The advantage of this method is that it is possible to assign finite horizon controls to each partition that are easier to calculate than infinite horizon methods, but still maintain the infinite horizon guarantee of reaching the target. An example is given to illustrate the implementation of the proposed controller.