Kamran Turkoglu

Real-Time Insitu Strategies for Enhancing UAV Endurance by Utilizing Wind Energy

This paper presents real-time practical strategies for enhancing the endurance of Unmanned Aerial Vehicle (UAV) flights by utilizing wind energy. Consistent with actual flight, no regional knowledge of the wind field is assumed. Rather, the technique relies solely on making “optimal” decisions at each successive time instant, given the instantaneous values of estimated local wind speeds. Based on these estimates, optimal airspeed and/or heading angle corrections are determined to minimize the instantaneous power requirement for steady level flight. UAV dynamics are described in terms of a dynamic point-mass model, and vehicle motion is constrained via boundary controls to a three-dimensional region around a specified target point. Models of closed-loop trajectory tracking are developed using the method of dynamic inversion for both airspeed vector tracking and boundary trajectory tracking. A nominal reference trajectory is assumed in which the UAV flies a fixed radius, constant altitude orbit with an airspeed that would maximize the endurance in zero wind. Simulations conducted for varying wind patterns compare the average power consumption of the proposed strategy with that of the reference trajectory. Obtained results indicate a potential saving in power consumption and in endurance of the UAV by simply using the appropriate wind component instantaneously during the flight regime.

Distributed Real-Time Non-Linear Receding Horizon Control Methodology for Multi-Agent Consensus Problems

This work investigates the consensus problem for multi-agent nonlinear systems through the real-time nonlinear receding horizon control methodology. A scheme is developed to reach the consensus for nonlinear multi-agent systems under fixed directed/undirected graph(s) without any linearization technique. The problem of consensus is converted into an optimization problem and is directly solved by the backwards sweep Riccati method to generate the control protocol which is a non-iterative algorithm. Stability analysis is conducted to provide convergence guarantees. An extension to the leader-following consensus problem of nonlinear systems is presented. Several examples are provided to validate the effectiveness of the presented scheme.

Development of a Low-Cost Experimental Quadcopter Testbed Using an Arduino Controller for Video Surveillance

This paper outlines the process of assembling an autonomous quadcopter platform from scratch and designing control laws to stabilize it using an Arduino Mega. Quadcopter dynamics are explored through the equations of motion. Then a quadcopter is designed and assembled using off-the-shelf, low-cost products to carry a camera payload which is utilized for video surveillance missions. The unstable, non-linear quadcopter dynamics are stabilized using a generic PID controller. System identification of the quadcopter is accomplished through the use of sweep data and CIFER to obtain the dynamic model.

Adaptive Differential Thrust Methodology for Lateral/Directional Stability of an Aircraft with a Completely Damaged Vertical Stabilizer

This paper investigates the utilization of differential thrust to help a commercial aircraft with a damaged vertical stabilizer regain its lateral/directional stability. In the event of an aircraft losing its vertical stabilizer, the consequential loss of the lateral/directional stability and control is likely to cause a fatal crash. In this paper, an aircraft with a completely damaged vertical stabilizer is investigated, and a unique differential thrust based adaptive control approach is proposed to achieve a stable flight envelope. The propulsion dynamics of the aircraft is modeled as a system of differential equations with engine time constant and time delay terms to study the engine response time with respect to a differential thrust input. The proposed differential thrust control module is then presented to map the rudder input to differential thrust input. Model reference adaptive control based on the Lyapunov stability approach is implemented to test the ability of the damaged aircraft to track the model aircrafts (reference) response in an extreme scenario. Investigation results demonstrate successful application of such differential thrust approach to regain lateral/directional stability of a damaged aircraft with no vertical stabilizer. Finally, the conducted robustness and uncertainty analysis results conclude that the stability and performance of the damaged aircraft remain within desirable limits, and demonstrate a safe flight mission through the proposed adaptive control methodology.

Optimal Trajectory Determination and Mission Design for Asteroid/Deep-Space Exploration via Multibody Gravity Assist Maneuvers

This paper investigates a genetic algorithm based space exploration mission design and trajectory development procedure that allows to determine non-intuitive optimal transfer trajectories to deep-space objects (such as asteroids) that might otherwise be difficult to approach using simpler, analytical methods. Through this methodology, two algorithms are developed. The first one calculates a direct trajectory to Ceres from Earth, and the second calculates a trajectory to Ceres that gets a gravity assist from Mars en route. Simulation results demonstrate the power of such genetic algorithms based methodologies of obtaining global optimal solutions/paths/trajectories.

Non-linear receding horizon control based real-time guidance and control methodologies for launch vehicles

This paper investigates a novel application of real-time nonlinear receding horizon control methodology with emphasis on launch vehicles. Through this work, we demonstrate a non-iterative nonlinear receding horizon control scheme, which can be implemented and run in real-time. Theory is demonstrated on a 2 state missile dynamics example, where the outcomes of the preliminary results demonstrate the applicability of such framework on complex missile dynamics and frameworks.

Utilization of differential thrust to regain lateral/directional stability of a commercial aircraft with a damaged vertical stabilizer

This paper studies the utilization of differential thrust to help a commercial aircraft with a damaged vertical stabilizer regain its lateral/directional stability. The vertical stabilizer is the key aerodynamic surface that provides an aircraft with its directional stability characteristic while the ailerons and rudder are the primary control surfaces that give the pilots the control authority of the yawing and banking maneuvers. In the event of an aircraft losing its entire vertical stabilizer, the consequential loss of the lateral/directional stability and control is likely to cause a fatal crash. In this paper, lateral/directional equations of motion are revisited to incorporate differential thrust as a control input. The engine dynamics of the jet aircraft is modeled as a system of differential equations with engine time constant and time delay terms to study the engine response time with respect to a differential thrust input. The novel differential thrust control module is then presented to map rudder input to differential thrust input. The investigation of the aircrafts open loop system response is also presented. Finally, model reference adaptive control based on the Lyapunov stability approach is implemented to test the ability of the damaged aircraft to track the undamaged aircrafts (reference) response in an extreme scenario.

Real-time guidance strategies for optimizing aircraft performance in stochastic wind conditions

This study presents real-time guidance strategies for unmanned aerial vehicles (UAVs) that can be used to enhance their flight endurance by utilizing insitu measurements of wind speeds and wind gradients. In these strategies, periodic adjustments can be made in the airspeed and/or heading angle command for the UAV to minimize a projected power requirement at some future time. In this research, UAV flights are described by a three-dimensional dynamic point-mass model. Onboard closed-loop trajectory tracking logics that follow airspeed vector commands are modeled using the method of feedback linearization. To evaluate the benefits of these strategies in enhancing UAV flight endurance, a reference strategy is introduced in which the UAV would follow the optimal airspeed command in a steady level flight under zero wind conditions. A performance measure is defined as the average power consumption both over a specified time interval and over different initial heading angles of the UAV. A relative benefit criterion is then defined as the percentage improvement in the performance measure of a proposed strategy over that of the reference strategy. Extensive numerical simulations are conducted to show efficiency and applicability of the proposed algorithms. Results demonstrate the efficiency, benefits and trends of power savings of the proposed real-time guidance strategies in level flights.

Estimation of CD4+ T Cell Count Parameters in HIV/AIDS Patients Based on Real-time Nonlinear Receding Horizon Control

An increasing number of control techniques are introduced to HIV infection problem to explore the options of helping clinical testing, optimizing drug treatments and to study the drug resistance. In such cases, complete/accurate knowledge of the HIV model and/or parameters is critical not only to monitor the dynamics of the system, but also to adjust the therapy accordingly. In those studies, existence of any type of unknown parameters imposes severe set-backs and becomes problematic for the treatment of the patients. In this work, we develop a real-time nonlinear receding horizon control approach to aid such scenarios and to estimate unknown constant/time-varying parameters of nonlinear HIV system models. For this purpose, the estimation procedure is reduced to a series of finite-time optimization problem which can be solved by backwards sweep Riccati method in real time without employing any iterative techniques. The simulation results demonstrate that proposed algorithm is able to estimate, effectively, unknown constant/time-varying parameters of HIV/AIDS model with disturbance and provide a unique, adaptive solution to an important open problem.

A Parallel Processing and Diversified-Hidden-Gene-Based Genetic Algorithm Framework for Fuel-Optimal Trajectory Design for Interplanetary Spacecraft Missions

A PARALLEL PROCESSING AND DIVERSIFIED-HIDDEN-GENE-BASED GENETIC ALGORITHM FRAMEWORK FOR FUEL-OPTIMAL TRAJECTORY DESIGN FOR INTERPLANETARY SPACECRAFT MISSIONS by Dhathri H. Somavarapu This thesis proposes a new parallel computing Genetic Algorithm framework for designing fuel-optimal trajectories for interplanetary spacecraft missions. The framework can capture the deep search-space of the problem with the use of a fixed chromosome structure and hidden-genes concept, can explore the diverse set of candidate solutions with the use of the Adaptive and Twin-Space Crowding techniques, can execute on any High-Performance Computing (HPC) platform with the adoption of the portable Message Passing Interface (MPI) standard. The algorithm is implemented in C++ with the use of the MPICH implementation of the MPI standard. The algorithm uses a patched-conic approach with two-body dynamics assumptions. New procedures are developed for determining trajectories in the V∞-Leveraging legs of the flight from the launch and non-launch planets, and deep-space maneuver legs of the flight from the launch and non-launch planets. The chromosome structure maintains the time of flight as a free parameter within certain boundaries. The fitness or the cost function of the algorithm uses only the mission ∆V , and does not include time of flight. Optimization is conducted with two variations for the mission gravity-assist sequence, the 4-gravity-assist and the 3-gravity-assist, with a maximum of 5 gravity-assists allowed in both the cases. In both the variations, an optimal trajectory is found with a mission cost (total ∆V ) comparable to the cost of the bench mark Cassini 2 mission of Gad and Abdelkhalik [1].