Numerical optimal control with applications in aerospace

This thesis explores various computational aspects of solving nonlinear, continuous-time dynamic optimization problems (DOPs) numerically. Firstly, a direct transcription method for solving DOPs is proposed, named the integrated residual method (IRM). Instead of forcing the dynamic constraints to be satisfied only at a selected number of points as in direct collocation, this new approach alternates between minimizing and constraining the squared norm of the dynamic constraint residuals integrated along the whole solution trajectories. The method is capable of obtaining solutions of higher accuracy for the same mesh compared to direct collocation methods, enabling a flexible trade-off between solution accuracy and optimality, and providing reliable solutions for challenging problems, including those with singular arcs and high-index differential-algebraic equations. A number of techniques have also been proposed in this work for efficient numerical solution of large scale and challenging DOPs. A general approach for direct implementation of rate constraints on the discretization mesh is proposed. Unlike conventional approaches that may lead to singular control arcs, the solution of this on-mesh implementation has better numerical properties, while achieving computational speedups. Another development is related to the handling of inactive constraints, which do not contribute to the solution of DOPs, but increase the problem size and burden the numerical computations. A strategy to systematically remove the inactive and redundant constraints under a mesh refinement framework is proposed. The last part of this work focuses on the use of DOPs in aerospace applications, with a number of topics studied. Using example scenarios of intercontinental flights, the benefits of formulating DOPs directly according to problem specifications are demonstrated, with notable savings in fuel usage. The numerical challenges with direct collocation are also identified, with the IRM obtaining solutions of higher accuracy, and at the same time suppressing the singular arc fluctuations.Open Acces

Towards a Framework for Nonlinear Predictive Control using Derivative-Free Optimization

The use of derivative-based solvers to compute solutions to optimal control problems with non-differentiable cost or dynamics often requires reformulations or relaxations that complicate the implementation or increase computational complexity. We present an initial framework for using the derivative-free Mesh Adaptive Direct Search (MADS) algorithm to solve Nonlinear Model Predictive Control problems with non-differentiable features without the need for reformulation. The MADS algorithm performs a structured search of the input space by simulating selected system trajectories and computing the subsequent cost value. We propose handling the path constraints and the Lagrange cost term by augmenting the system dynamics with additional states to compute the violation and cost value alongside the state trajectories, eliminating the need for reconstructing the state trajectories in a separate phase. We demonstrate the practicality of this framework by solving a robust rocket control problem, where the objective is to reach a target altitude as close as possible, given a system with uncertain parameters. This example uses a non-differentiable cost function and simulates two different system trajectories simultaneously, with each system having its own free final time.Comment: Accepted for presentation at the 7th IFAC Conference on Nonlinear Model Predictive Contro

Aircraft Modeling for Upset Recovery and its Applications - Development of a tool chain from model generations to flight simulations

Aircraft departing from the nominal flight envelop and entering upset situations have become a major safety concern for the air transportation industry. Evidence shows that purely relying on pilots to conduct the recovery maneuvers may not be an effective approach, thus more advanced alternative solutions are required. This report includes reviews of previous works and findings in the field of aircraft upset recovery. Starting from the current status of upset prevention approaches, detailed descriptions are given for various extended flight dynamics modeling methods formerly developed using wind-tunnel measurements and computational fluid dynamics simulations. Earlier attempts on implementing the extended model into flight simulator training programs, and control system designs for upset recovery are also examined. It is discovered that all researches in this field are essentially in their beginning stage with only premature solutions offered. Lack of common standards for evaluation of results can also be observed among various reference materials. Throughout the course of this master’s project, a complete tool chain is developed for generating extended and enhanced flight models for low speed flights. Starting from geometric based automatic generation of the baseline model, mathematical algorithms are added to supplement the model for simulation of aircraft dynamics in near stall and post-stall regions using decambering theories, as well as dynamic stall and spin dynamics modelings. Together with additional functions of empirical corrections, drag estimations and weight calculations, significant enhancement was made to computational capability of the German Aerospace Center’s in-house designed vortex lattice method program. The model is validated based on various reference materials. Direct comparisons to some wind-tunnel measurements, manufacturer’s reports and other academic publishing indicate satisfactory modeling results for the lift, drag, moments and control surface effectiveness. Furthermore, the simulation results of the Fokker 100 aircraft model are directly compared to flight data recordings of five different accidents involving aircraft upsets. Promising results are obtained for upset types of over-banking, rudder hard-over, symmetric stall and asymmetric stall spin. The model is designed to be applied into applications of both fields of integrated aircraft design and upset recovery control action researches. Concerning this project, the implementation of the model into German Aerospace Center’s Robot Motion Simulator aims at enabling realistic simulations of upset motions unachievable by conventional hex-pod simulators. Due to hardware constrains, simulation of flight upset with the current setup is not possible; however, analyzing the preliminary software simulation results demonstrate that with minor modifications, the Robot Motion Simulator is very capable of reproducing the motions created by flight upsets. Furthermore, a preliminary research is conducted into the evaluations of upset recovery control actions based on the observations of various simulations using the extended model

EOTS: An Energy-consumption Optimization-oriented Task Scheduling Algorithm for Wireless Sensor Networks

The mismatch of task scheduling results in rapid network energy consumption during data transmission in wireless sensor networks. To address this issue, the paper proposed an Energy-consumption Optimization-oriented Task Scheduling Algorithm (EOTS algorithm) which formally described the overall power dissipation in the network system. On this basis, a network model was built up such that both the idle energy consumption in sensor nodes and energy consumption during the execution of tasks were taken into account, with which the whole task was effectively decomposed into sub-task sequences. They underwent simulated annealing and iterative refinement, with the intention of improving sensor nodes’ utilization rate, reducing local idle energy cost, as well as cutting down the overall energy consumption accordingly. The experiment result shows that under the environment of multi-task operation, from the perspective of energy cost optimization, the proposed scheduling strategy recorded an increase of 21.24% compared with the FIFO algorithm, and an increase of 16.77% in comparison to the EMRSA algorithm; while in light of network lifetimes, the EOTS algorithm surpassed the ECTA algorithm by a gain of 19.21%. Therefore, the effectiveness of the proposed EOTS algorithm is verified

Migration and Aggregation Behavior of Nickel and Iron in Low Grade Laterite Ore with New Additives

This study focused on the preparation of high-grade ferronickel concentrate, the behavior of efficient migration and the polymerization of ferronickel particles during reduction roasting, by adding calcium fluoride and a ferronickel concentrate to low-grade laterite ore from Yunnan. The effects of temperature, holding time, reductant content, ferronickel concentrate content and magnetic field intensity on the preparation of the ferronickel concentrate were studied and the optimum conditions were determined as follows: 30% ferronickel concentrate (metal Ni-4.68%, metal Fe-45.0%), 8% coal, 7% calcium fluoride, reduction temperature of 1250 °C, reduction time of 60 min and the intensity of magnetic separation is 150 mT. The proportion of nickel and iron in ferronickel concentrate was 88.7% (metal Ni-8.62%, metal Fe-80.1%), and the recovery efficiency of nickel and iron are 98.8% and 82.4%, respectively. X-ray diffraction and scanning electron microscopy indicated that ferronickel-concentrate, as an activating agent, improved the aggregation effect of ferronickel particles. The efficient migration and polymerization of ferronickel particles in the ore significantly increased the size of the ferronickel particles with additives, therefore a high-grade ferronickel concentrate was prepared, and the reduction and recovery efficiency of laterite nickel ore was improved

Amino Functionalization of Reduced Graphene Oxide/Tungsten Disulfide Hybrids and Their Bismaleimide Composites with Enhanced Mechanical Properties

A novel graphene-based nanocomposite particles (NH2-rGO/WS2), composed of reduced graphene oxide (rGO) and tungsten disulfide (WS2) grafted with active amino groups (NH2-rGO/WS2), was successfully synthesized by an effective and facile method. NH2-rGO/WS2 nanoparticles were then used to fabricate new bismaleimide (BMI) composites (NH2-rGO/WS2/BMI) via a casting method. The results demonstrated that a suitable amount of NH2-rGO/WS2 nanoparticles significantly improved the mechanical properties of the BMI resin. When the loading of NH2-rGO/WS2 was only 0.6 wt %, the impact and flexural strength of the composites increased by 91.3% and 62.6%, respectively, compared to the neat BMI resin. Rare studies have reported such tremendous enhancements on the mechanical properties of the BMI resin with trace amounts of fillers. This is attributable to the unique layered structure of NH2-rGO/WS2 nanoparticles, fine interfacial adhesion, and uniform dispersion of NH2-rGO/WS2 in the BMI resin. Besides, the thermal gravimetrical analysis (TGA) revealed that the addition of NH2-rGO/WS2 could also improve the stability of the composites

Aircraft Upset and Recovery Simulation with the DLR Robot Motion Simulator

Aiming at providing a more accessible alternative platform for upset recovery training and research, the feasibility of adapting the German Aerospace Center (DLR)'s Robot Motion Simulator is studied with use of the Fokker 100 extended flight dynamics model developed earlier. Adjustments are made to the S-function in the simulation software setup for better preserving the dynamic motions in stall and post-stall conditions. The configuration of the simulator with a cabin located on the top of a KUKA industrial robot arm provides seven axis of movement freedom, greatly enlarging the motion capability in comparison to the conventional hexapod simulators. Virtually all nominal ight conditions can be simulated well with the current setup; and with a slight modification of one axis for continuous rotations, the simulator shows good capability of reproducing the motions experienced in aircraft upset conditions and recovery maneuvers

Fuzzy-Ball Fluids Enhance the Production of Oil and Gas Wells: A Historical Review

Advancements in drilling technology are pivotal to optimizing the production and sustainability of oil and gas wells. One of the emerging innovations is the application of a specialized fluid known as “Fuzzy-ball” fluid. This paper comprehensively reviews the historical evolution and advancements in the utilization of fuzzy-ball fluid in drilling and well-repair processes. Fuzzy-ball fluid has been discovered to bolster a formation’s pressure-bearing capabilities and systematically augment resistance against oil, gas, and water flow. These attributes have been instrumental in the phased integration of fuzzy-ball fluid into procedures aiming to enhance production in oil and gas wells. This paper bridges the knowledge gap in the industry regarding the application of fuzzy-ball fluid, thereby circumventing the challenges of inadequate understanding and suboptimal designs. However, the study acknowledges the potential limitation of information loss despite the extensive data collection from diverse sources, such as articles, patents, and reports. As a future direction, this paper emphasizes the need for a more encompassing and critical evaluation of fuzzy-ball fluid’s performance and applications. This will enable a more informed decision-making process, fostering the expanded use and understanding of this fluid’s mechanism within the industry