• Refine Query
  • Source
  • Publication year
  • to
  • Language
  • 82
  • 23
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • Tagged with
  • 145
  • 145
  • 51
  • 37
  • 25
  • 24
  • 23
  • 22
  • 17
  • 17
  • 15
  • 14
  • 14
  • 13
  • 12
  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
71

Simulation of Human Movements through Optimization

Pettersson, Robert January 2012 (has links)
Optimization has been used to simulate human neural control and resulting movement patterns. The short term aim was to develop the methodology required for solving the movement optimization problem often arising when modelling human movements. A long term aim is the contribution to increased knowledge about various human movements, wherein postures is one specific case. Simulation tools can give valuable information to improve orthopeadic treatments and technique for training and performance in sports. In one study a static 3D model with 30 muscle groups was used to analyse postures. The activation levels of these muscles are minimized in order to represent the individual’s choice of posture. Subject specific data in terms of anthropometry, strength and orthopedic aids serve as input. The specific aim of this part was to study effects from orthopedic treatment and altered abilities of the subject. Initial validation shows qualitative agreement of posture strategies but further details about passive stiffness and anthropometry are needed, especially to predict pelvis orientation. Four studies dealt with movement optimization. The main methodological advance was to introduce contact constraints to the movement optimization. A freetime multiple phase formulation was derived to be able to analyse movements where different constraints and degrees of freedom are present in subsequent phases of the movements. The athletic long jump, a two foot high jump, a backward somersault and rowing were used as applications with their different need of formulation. Maximum performance as well as least effort cost functions have been explored. Even though it has been a secondary aim in this work the results show reasonable agreement to expected movements in reality. Case specific subject properties and inclusion of muscle dynamics are required to draw conclusions about improvements in the sport activity, respectively. / <p>QC 20120910</p>
72

Real-time Trajectory Optimization for Terrain Following Based on Non-linear Model Predictive Control / Trajektorieoptimering för terrängföljning i realtid baserad på olinjär prediktionsreglering

Flood, Cecilia January 2001 (has links)
There are occasions when it is preferable that an aircraft flies asclose to the ground as possible. It is difficult for a pilot to predict the topography when he cannot see beyond the next hill, and this makes it hard for him to find the optimal flight trajectory. With the help of a terrain database in the aircraft, the forthcoming topography can be found in advance and a flight trajectory can be calculated in real-time. The main goal is to find an optimal control sequence to be used by the autopilot. The optimization algorithm, which is created for finding the optimal control sequence, has to be run often and therefore, it has to be fast. This thesis presents a terrain following algorithm based on Model Predictive Control which is a promising and robust way of solving the optimization problem. By using trajectory optimization, a trajectory which follows the terrain very good is found for the non-linear model of the aircraft.
73

Development of Novel Task-Based Configuration Optimization Methodologies for Modular and Reconfigurable Robots Using Multi-Solution Inverse Kinematic Algorithms

Tabandeh, Saleh 04 December 2009 (has links)
Modular and Reconfigurable Robots (MRRs) are those designed to address the increasing demand for flexible and versatile manipulators in manufacturing facilities. The term, modularity, indicates that they are constructed by using a limited number of interchangeable standardized modules which can be assembled in different kinematic configurations. Thereby, a wide variety of specialized robots can be built from a set of standard components. The term, reconfigurability, implies that the robots can be disassembled and rearranged to accommodate different products or tasks rather than being replaced. A set of MRR modules may consist of joints, links, and end-effectors. Different kinematic configurations are achieved by using different joint, link, and end-effector modules and by changing their relative orientation. The number of distinct kinematic configurations, attainable by a set of modules, varies with respect to the size of the module set from several tens to several thousands. Although determining the most suitable configuration for a specific task from a predefined set of modules is a highly nonlinear optimization problem in a hybrid continuous and discrete search space, a solution to this problem is crucial to effectively utilize MRRs in manufacturing facilities. The objective of this thesis is to develop novel optimization methods that can effectively search the Kinematic Configuration (KC) space to identify the most suitable manipulator for any given task. In specific terms, the goal is to develop and synthesize fast and efficient algorithms for a Task-Based Configuration Optimization (TBCO) from a given set of constraints and optimization criteria. To achieve such efficiency, a TBCO solver, based on Memetic Algorithms (MA), is proposed. MAs are hybrids of Genetic Algorithms (GAs) and local search algorithms. MAs benefit from the exploration abilities of GAs and the exploitation abilities of local search methods simultaneously. Consequently, MAs can significantly enhance the search efficiency of a wide range of optimization problems, including the TBCO. To achieve more optimal solutions, the proposed TBCO utilizes all the solutions of the Inverse Kinematics(IK) problem. Another objective is to develop a method for incorporating the multiple solutions of the IK problem in a trajectory optimization framework. The output of the proposed trajectory optimization method consists of a sequence of desired tasks and a single IK solution to reach each task point. Moreover, the total cost of the optimized trajectory is utilized in the TBCO as a performance measure, providing a means to identify kinematic configurations with more efficient optimized trajectories. The final objective is to develop novel IK solvers which are both general and complete. Generality means that the solvers are applicable to all the kinematic configurations which can be assembled from the available module inventory. Completeness entails the algorithm can obtain all the possible IK solutions.
74

Development of Novel Task-Based Configuration Optimization Methodologies for Modular and Reconfigurable Robots Using Multi-Solution Inverse Kinematic Algorithms

Tabandeh, Saleh 04 December 2009 (has links)
Modular and Reconfigurable Robots (MRRs) are those designed to address the increasing demand for flexible and versatile manipulators in manufacturing facilities. The term, modularity, indicates that they are constructed by using a limited number of interchangeable standardized modules which can be assembled in different kinematic configurations. Thereby, a wide variety of specialized robots can be built from a set of standard components. The term, reconfigurability, implies that the robots can be disassembled and rearranged to accommodate different products or tasks rather than being replaced. A set of MRR modules may consist of joints, links, and end-effectors. Different kinematic configurations are achieved by using different joint, link, and end-effector modules and by changing their relative orientation. The number of distinct kinematic configurations, attainable by a set of modules, varies with respect to the size of the module set from several tens to several thousands. Although determining the most suitable configuration for a specific task from a predefined set of modules is a highly nonlinear optimization problem in a hybrid continuous and discrete search space, a solution to this problem is crucial to effectively utilize MRRs in manufacturing facilities. The objective of this thesis is to develop novel optimization methods that can effectively search the Kinematic Configuration (KC) space to identify the most suitable manipulator for any given task. In specific terms, the goal is to develop and synthesize fast and efficient algorithms for a Task-Based Configuration Optimization (TBCO) from a given set of constraints and optimization criteria. To achieve such efficiency, a TBCO solver, based on Memetic Algorithms (MA), is proposed. MAs are hybrids of Genetic Algorithms (GAs) and local search algorithms. MAs benefit from the exploration abilities of GAs and the exploitation abilities of local search methods simultaneously. Consequently, MAs can significantly enhance the search efficiency of a wide range of optimization problems, including the TBCO. To achieve more optimal solutions, the proposed TBCO utilizes all the solutions of the Inverse Kinematics(IK) problem. Another objective is to develop a method for incorporating the multiple solutions of the IK problem in a trajectory optimization framework. The output of the proposed trajectory optimization method consists of a sequence of desired tasks and a single IK solution to reach each task point. Moreover, the total cost of the optimized trajectory is utilized in the TBCO as a performance measure, providing a means to identify kinematic configurations with more efficient optimized trajectories. The final objective is to develop novel IK solvers which are both general and complete. Generality means that the solvers are applicable to all the kinematic configurations which can be assembled from the available module inventory. Completeness entails the algorithm can obtain all the possible IK solutions.
75

Optimal Path Planning for Single and Multiple Aircraft Using a Reduced Order Formulation

Twigg, Shannon 09 April 2007 (has links)
High-flying unmanned reconnaissance and surveillance systems are now being used extensively in the United States military. Current development programs are producing demonstrations of next-generation unmanned flight systems that are designed to perform combat missions. Their use in first-strike combat operations will dictate operations in densely cluttered environments that include unknown obstacles and threats, and will require the use of terrain for masking. The demand for autonomy of operations in such environments dictates the need for advanced trajectory optimization capabilities. In addition, the ability to coordinate the movements of more than one aircraft in the same area is an emerging challenge. This thesis examines using an analytical reduced order formulation for trajectory generation for minimum time and terrain masking cases. First, pseudo-3D constant velocity equations of motion are used for path planning for a single vehicle. In addition, the inclusion of winds, moving targets and moving threats is considered. Then, this formulation is increased to using 3D equations of motion, both with a constant velocity and with a simplified varying velocity model. Next, the constant velocity equations of motion are expanded to include the simultaneous path planning of an unspecified number of vehicles, for both aircraft avoidance situations and formation flight cases.
76

A methodology for determining aircraft fuel burn using air traffic control radar data

Elliott, Matthew Price 05 April 2011 (has links)
The air traffic system in the United States is currently undergoing a complete overhaul known as "NextGen". NextGen is the FAA's initiative to update the antiquated National Airspace System (NAS) both procedurally and technologically to reduce costs to the users and negative impacts on the general public. There are currently numerous studies being conducted that are focused on finding optimal solutions to the problems of congestion, delay, and the high fuel and noise footprints associated aircraft operations. These studies require accurate simulation techniques to assess the potential benefits and drawbacks for new procedures and technology. One common method uses air traffic control radar data. As an aircraft travels through the air traffic control system, its latitude, longitude, and altitude are recorded at set intervals. From these values, estimates of groundspeed and heading can be derived. Researchers then use this data to estimate aircraft performance parameters such as engine thrust and aircraft configuration, variables essential to estimate fuel burn, noise, and emissions. This thesis creates a more accurate method of simulating aircraft performance based solely on air traffic control radar data during the arrival process. This tool will allow the benefits of different arrival procedures to be compared at a variety of airports and wind conditions before costly flight testing is required. The accuracy of the performance estimates will be increased using the Tool for Assessing Separation and Throughput (TASAT), a fast-time Monte Carlo aircraft simulator that can simulate multiple arrivals with a mixture of different aircraft types. The tool has succeeded in matching various recorded radar profiles and has produced fuel burn estimates with an RMS error of less than 200 pounds from top of descent to landing when compared to high fidelity operational data. The output from TASAT can also be ported to FAA software tools to make higher quality predictions of aircraft noise and emissions.
77

An Autonomous Guidance Scheme For Orbital Rendezvous

Shankar, G S 01 1900 (has links)
The word 'rendezvous' implies a pre-arranged meeting between two entities for a specific purpose. This term is used in the study of spacecraft operations, to describe a set of maneuvers performed by two spacecraft in order to achieve a match in position and velocity. The term 'orbital rendezvous' applies to rendezvous between spacecraft in earth-centered orbits. Considering its obvious scope for application in the assembly, maintenance and retrieval of earth satellites, the importance of orbital rendezvous towards maintaining a sustained presence in space can be easily appreciated. This particular study deals with the development of a guidance scheme for an orbital rendezvous operation, wherein only one of the spacecraft, called the chaser, is assumed to be provided with a capability to maneuver, while the other spacecraft, the target, is assumed to be thrust-free or passive. There is presently a lot of interest in autonomous trajectory planning and guidance schemes for orbital rendezvous missions. Autonomy here, refers to the absence of ground supervision and control over the on-board planning and guidance process, and is expected to result in greater mission flexibility and lower operating costs. The terms trajectory planning and guidance collectively refer to the optimization process used to determine minimum-fuel trajectories, and the means employed to make the spacecraft follow them, based on navigational updates. The challenge lies mainly in making the autonomous scheme real-time implementable, and at the same time compatible with the limited computational capabilities available on-board. It is well known that a large part of the computation times and costs, when determining optimal trajectories, are taken up by (1) the prediction of spacecraft motion using numerical integration schemes, and (2) the use of iterative numerical techniques to solve the non-linear, coupled system of equations obtained as boundary conditions in the trajectory optimization problem. There exists on the other hand, a wealth of results from analytical investigations into the motion of spacecraft, that can be profitably utilized by use of suitable assumptions, to reduce computation times and costs relating to trajectory prediction. The present thesis seeks to follow this course, while trying to ensure that the assumptions made do not influence in a negative manner the accuracy of the guidance scheme. The assumptions to be described below are based on the division of the total rendezvous maneuver into sub-phases. The trajectory optimization problems for the individual sub-phases are first considered independent of one another. A method is then found to combine the two sub-phases in an optimal manner. The initial or the homing phase of the rendezvous maneuver, consists of an open-loop orbit transfer, intended to place the chaser within a 'window of proximity' spanning a few hundreds of kilometers, of the target. In order to avoid time consuming numerical integration of the non-homogeneous, non-linear central force-field equations of motion, an impulsive thrust model is assumed. A parametric optimization method is used to determine the location, orientation and magnitude of the impulses for a minimum-fuel rendezvous transfer, as it is well known that parametric optimization methods are robust compared to the more general functional optimization methods. A two-impulse transfer is selected, knowing that at least two-impulses are required for a rendezvous maneuver, and that methods are available if necessary, to obtain optimal multi-impulse trajectories from a two-impulse solution. The total characteristic velocity, a scalar cost function related to fuel-consumption, is minimized with respect to a set of independent variables. The variables chosen in this case to determine the rendezvous transfer are (1) the transfer angle θc defining an initial coast in the chaser orbit C by the chaser, (2) the transfer angle θs defining a coast by the target to the position of the second impulse in the target orbit S and (3) a parameter (say p ) that determines the shape of the transfer orbit T between the first and second impulses.
78

Aircraft Trajectory Optimization with Tactical Constraints

Norsell, Martin January 2004 (has links)
<p>Aircrafttrajectory optimization is traditionally used forminimizing fuel consumption or time when going from one flightstate to another. This thesis presents a possible approach toincorporate tactical constraints in aircraft trajectoryoptimization.</p><p>The stealth technology of today focuses on making thetactics already in use more effective. Since tactics andstealth are closely interrelated, new and better results may beobtained if both aspects are considered simultaneously. Simplyreducing the radar cross section area in some directionswithout considering tactical aspects may result in little, ifany, improvement.</p><p>Flight tests have been performed in cooperation withEricsson Microwave Systems and the Swedish Air Force FlightAcademy. The aircraft used was the subsonic jet trainer Saab105, designated SK60 by the Swedish Air Force. The results showa decrease of 40% in the time interval between the instant theaircraft was first detected until it could pass above the radarstation. This corresponds to a reduced radar cross section(RCS) in the direction from the aircraft to the radar of almost90%, if classical RCS reduction techniques would have beenapplied.</p><p>If a modern aircraft with stealth properties would be used,the proposed methodology is believed to increase the possibleimprovements further. This is because the variation of themagnitude of RCS in different directions is greater for a shapeoptimized aircraft, which is the property exploited by thedeveloped method.</p><p>The methods presented are indeed an approach utilizing theideas of the network centric warfare (NCW) concept. Themethodology presented depends on accurate information about theadversary, while also providing up-to-date information to theother users in the information network.</p><p>The thesis focuses on aircraft but the methods are generaland may be adapted for missiles, shipsor land vehicles. Theproposed methods are also economically viable since they areuseful for existing platforms without costly modifications. Themethods presented are not limited to radar threats only. Thereasons for using radar in this thesis are the availablenon-classified data and that radar is known to pose a majorthreat against aircraft.</p>
79

Real-time Trajectory Optimization for Terrain Following Based on Non-linear Model Predictive Control / Trajektorieoptimering för terrängföljning i realtid baserad på olinjär prediktionsreglering

Flood, Cecilia January 2001 (has links)
<p>There are occasions when it is preferable that an aircraft flies asclose to the ground as possible. It is difficult for a pilot to predict the topography when he cannot see beyond the next hill, and this makes it hard for him to find the optimal flight trajectory. With the help of a terrain database in the aircraft, the forthcoming topography can be found in advance and a flight trajectory can be calculated in real-time. The main goal is to find an optimal control sequence to be used by the autopilot. The optimization algorithm, which is created for finding the optimal control sequence, has to be run often and therefore, it has to be fast. </p><p>This thesis presents a terrain following algorithm based on Model Predictive Control which is a promising and robust way of solving the optimization problem. By using trajectory optimization, a trajectory which follows the terrain very good is found for the non-linear model of the aircraft.</p>
80

Consensus seeking, formation keeping, and trajectory tracking in multiple vehicle cooperative control /

Ren, Wei, January 2004 (has links) (PDF)
Thesis (Ph. D.)--Brigham Young University. Dept. of Electrical and Computer Engineering, 2004. / Includes bibliographical references (p. 129-141).

Page generated in 0.0362 seconds