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61 
Synthesis of continuous wholebody motion in hexapod robot for humanitarian deminingKhudher, Dhayaa Raissan January 2018 (has links)
In the context of control, the motion of a legged robot is very challenging compared with traditional fixed manipulator. Recently, many researches have been conducted to control the motion of legged robot with different techniques. On the other hand, manipulation tasks have been addressed in many applications. These researches solved either the mobility or the manipulation problems, but integrating both properties in one system is still not available. In this thesis, a control algorithm is presented to control both locomotion and manipulation in a six legged robot. Landmines detection process is considered as a case study of this project to accelerate the mine detection operation by performing both walking and scanning simultaneously. In order to qualify the robot to perform more tasks in addition to the walking task, the joint redundancy of the robot is exploited optimally. The tasks are arranged according to their importance to high level of priority and low level of priority. A new task priority redundancy resolution technique is developed to overcome the effect of the algorithmic singularities and the kinematic singularity. The computational aspects of the solution are also considered in view of a realtime implementation. Due to the dynamic changes in the size of the robot motion space, the algorithm has the ability to make a tradeoff between the number of achieved tasks and the imposed constraints. Furthermore, an appropriate hierarchy is imposed in order to ensure an accurate decoupling between the executed tasks. The dynamic effect of the arm on the overall performance of the robot is attenuated by reducing the optimisation variables. The effectiveness of the method is evaluated on a Computer Aided Design (CAD) model and the simulations of the whole operation are conducted using MATLAB and SimMechanics.

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OPTIMIZATION FOR STRUCTURAL EQUATION MODELING: APPLICATIONS TO SUBSTANCE USE DISORDERSZahery, Mahsa 01 January 2018 (has links)
Substance abuse is a serious issue in both modern and traditional societies. Besides health complications such as depression, cancer and HIV, social complications such as loss of concentration, loss of job, and legal problems are among the numerous hazards substance use disorder imposes on societies. Understanding the causes of substance abuse and preventing its negative effects continues to be the focus of much research.
Substance use behaviors, symptoms and signs are usually measured in form of ordinal data, which are often modeled under threshold models in Structural Equation Modeling (SEM). In this dissertation, we have developed a general nonlinear optimizer for the software package OpenMx, which is a SEM package in widespread use in the fields of psychology and genetics. The optimizer solves nonlinearly constrained optimization problems using a Sequential Quadratic Programming (SQP) algorithm. We have tested the performance of our optimizer on ordinal data and compared the results with two other optimizers (implementing SQP algorithm) available in the OpenMx package. While all three optimizers reach the same minimum, our new optimizer is faster than the other two.
We then applied OpenMx with our optimization engine to a very large populationbased drug abuse dataset, collected in Sweden from over one million pairs, to investigate the effects of genetic and environmental factors on liability to drug use.
Finally, we investigated the reasons behind better performance of our optimizer by profiling all three optimizers as well as analyzing their memory consumption. We found that objective function evaluation is the most expensive task for all three optimizers, and that our optimizer needs fewer number of calls to this function to find the minimum. In terms of memory consumption, the optimizers use the same amount of memory.

63 
A conic optimization approach to variants of the trust region subproblemYang, Boshi 01 July 2015 (has links)
The Trust Region Subproblem (TRS), which minimizes a nonconvex quadratic function over the unit ball, is an important subproblem in trust region methods for nonlinear optimization. Even though TRS is a nonconvex problem, it can be solved in polynomial time using, for example, a semidefinite programming (SDP) relaxation. Different variants of TRS have been considered from both theoretical and practical perspectives. In this thesis, we study three variants of TRS and their SDP/conic relaxations.
We first study an extended trust region subproblem (eTRS) in which the trust region equals the intersection of the unit ball with M linear cuts. When m = 0, when m = 1, or when m = 2 and the linear cuts are parallel, it is known that the eTRS optimal value equals the optimal value of a particular conic relaxation, which is solvable in polynomial time. However, it is also known that, when m ≥2 and at least two of the linear cuts intersect within the ball, i.e., some feasible point of the eTRS satisfies both linear constraints at equality, then the same conic relaxation may admit a gap with eTRS. We show that the conic relaxation admits no gap for arbitrary M as long as the linear cuts are nonintersecting.
We then extend our result to a more general setting. We study an eTRS in which a quadratic function is minimized over a structured nonconvex feasible region: the unit ball with M linear cuts and R hollows. In the special case when m = 0 and r = 1, it is known that the eTRS has a tight polynomialtime solvable conic relaxation. We show that a certain conic relaxation is also tight for general R and M as long as the cuts and hollows satisfy some nonintersecting assumptions that generalize the previous paragraph.
Finally, intersecting the feasible region of TRS with a second ellipsoid results in the twotrustregion subproblem (TTRS). Even though TTRS can also be solved in polynomialtime, existing approaches do not provide a concise conic relaxation. We investigate the use of conic relaxation for TTRS. Starting from the basic SDP relaxation of TTRS, which admits a gap, recent research has tightened the basic relaxation using valid secondordercone (SOC) inequalities. For the special case of TTRS in dimension n=2, we fully characterize the remaining valid inequalities, which can be viewed as strengthened versions of the SOC inequalities just mentioned. We also demonstrate that these valid inequalities can be used computationally even when n > 2 to solve TTRS instances that were previously unsolved using techniques of conic relaxation.

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The use of portfolio management with target costed process oriented products under conditions of uncertaintyHorton, Kevin G. 02 February 2010 (has links)
The present trend towards shorter product lives means that manufacturers are
faced with less time whereby production costs can be controlled and reduced. As a result
many companies are turning towards the use of Systems Engineering and cost
management techniques that are intended to reduce product costs during the design phases
of the product life.
<p>One of the many cost management tools that are presently in use is target costing.
An iterative process, target costing attempts to reduce the cost of manufacturing products
by using value engineering techniques so that identified target costs can be realized. As a
step improvement program, the ability of a company to obtain its target cost in not always
certain. Target profits from individual products are grouped together into portfolios and
then managed according to company strategic profit plans.
<p>This report investigates methods used for identifying the uncertainties that can
exist in the target costing process and suggests the potential use efficient portfolio
techniques for the management of process oriented or continuous products.
The report also suggests a number of followon projects that could encompass the
use of specific decision support systems for the examination of both target costing
uncertainties and portfolio management. / Master of Science

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JACKKNIFE MODEL AVERAGING ON FUNCTIONAL LOGISTIC MODELMa, Genuo January 2020 (has links)
No description available.

66 
Optimization Techniques Exploiting Problem Structure: Applications to Aerodynamic DesignShenoy, Ajit R. 11 April 1997 (has links)
The research presented in this dissertation investigates the use of allatonce methods applied to aerodynamic design. Allatonce schemes are usually based on the assumption of sufficient continuity in the constraints and objectives, and this assumption can be troublesome in the presence of shock discontinuities. Special treatment has to be considered for such problems and we study several approaches.
Our allatonce methods are based on the Sequential Quadratic Programming method, and are designed to exploit the structure inherent in a given problem. The first method is a Reduced Hessian formulation which projects the optimization problem to a lower dimension design space. The second method exploits the sparse structure in a given problem which can yield significant savings in terms of computational effort as well as storage requirements. An underlying theme in all our applications is that careful analysis of the given problem can often lead to an efficient implementation of these allatonce methods.
Chapter 2 describes a nozzle design problem involving onedimensional transonic flow. An initial formulation as an optimal control problem allows us to solve the problem as as twopoint boundary problem which provides useful insight into the nature of the problem. Using the Reduced Hessian formulation for this problem, we find that a conventional CFD method based on shock capturing produces poor performance. The numerical difficulties caused by the presence of the shock can be alleviated by reformulating the constraints so that the shock can be treated explicitly. This amounts to using a shock fitting technique. In Chapter 3, we study variants of a simplified temperature control problem. The control problem is solved using a sparse SQP scheme. We show that for problems where the underlying infinitedimensional problem is wellposed, the optimizer performs well, whereas it fails to produce good results for problems where the underlying infinitedimensional problem is illposed. A transonic airfoil design problem is studied in Chapter 4, using the Reduced SQP formulation. We propose a scheme for performing the optimization subtasks that is based on an Euler Implicit time integration scheme. The motivation is to preserve the solutionfinding structure used in the analysis algorithm. Preliminary results obtained using this method are promising. Numerical results have been presented for all the problems described. / Ph. D.

67 
Vehicle Routing for Emergency EvacuationsPereira, Victor Caon 22 November 2013 (has links)
This dissertation introduces and analyzes the Bus Evacuation Problem (BEP), a unique Vehicle Routing Problem motivated both by its humanitarian significance and by the routing and scheduling challenges of planning transitbased, regional evacuations. First, a variant where evacuees arrive at constant, locationspecific rates is introduced. In this problem, a fleet of capacitated buses must transport all evacuees to a depot/shelter such that the last scheduled pickup and the end of the evacuee arrival process occurs at a locationspecific time. The problem seeks to minimize their accumulated waiting time, restricts the number of pickups on each location, and exploits efficiencies from service choice and from allowing buses to unload evacuees at the depot multiple times. It is shown that, depending on the problem instance, increasing the maximum number of pickups allowed may reduce both the fleet size requirement and the evacuee waiting time, and that, past a certain threshold, there exist a range of values that guarantees an efficient usage of the available fleet and equitable reductions in waiting time across pickup locations. Second, an extension of the Ritter (1967) Relaxation Algorithm, which explores the inherent structure of problems with complicating variables and constraints, such as the aforementioned BEP variant, is presented. The modified algorithm allows problems with linear, integer, or mixedinteger subproblems and with linear or quadratic objective functions to be solved to optimality. Empirical studies demonstrate the algorithm viability to solve large optimization problems. Finally, a twostage stochastic formulation for the BEP is presented. Such variant assumes that all evacuees are at the pickup locations at the onset of the evacuation, that the set of possible demands is provided, and, more importantly, that the actual demands become known once buses visit the pickup locations for the first time. The effect of exploratory visits (sampling) and symmetry is explored, and the resulting insights used to develop an improved formulation for the problem. An iterative (dynamic) solution algorithm is proposed. / Ph. D.

68 
Control Design for a Microgrid in Normal and Resiliency Modes of a Distribution SystemAlvarez, Genesis Barbie 17 October 2019 (has links)
As inverterbased distributed energy resources (DERs) such as photovoltaic (PV) and battery energy storage system (BESS) penetrate within the distribution system. New challenges regarding how to utilize these devices to improve power quality arises. Before, PV systems were required to disconnect from the grid during a large disturbance, but now smart inverters are required to have dynamically controlled functions that allows them to remain connected to the grid. Monitoring power flow at the point of common coupling is one of the many functions the controller should perform. Smart inverters can inject active power to pick up critical load or inject reactive power to regulate voltage within the electric grid. In this context, this thesis focuses on a high level and local control design that incorporates DERs. Different controllers are implemented to stabilize the microgrid in an Islanding and resiliency mode. The microgrid can be used as a resiliency source when the distribution is unavailable. An average model in the DQ frame is calculated to analyze the inherent dynamics of the current controller for the point of common coupling (PCC). The space vector approach is applied to design the voltage and frequency controller. Secondly, using inverters for Volt/VAR control (VVC) can provide a faster response for voltage regulation than traditional voltage regulation devices. Another objective of this research is to demonstrate how smart inverters and capacitor banks in the system can be used to eliminate the voltage deviation. A mixedinteger quadratic problem (MIQP) is formulated to determine the amount of reactive power that should be injected or absorbed at the appropriate nodes by inverter. The Big M method is used to address the nonconvex problem. This contribution can be used by distribution operators to minimize the voltage deviation in the system. / Master of Science / Reliable power supply from the electric grid is an essential part of modern life. This critical infrastructure can be vulnerable to cascading failures or natural disasters. A solution to improve power systems resilience can be through microgrids. A microgrid is a small network of interconnected loads and distributed energy resources (DERs) such as microturbines, wind power, solar power, or traditional internal combustion engines. A microgrid can operate being connected or disconnected from the grid. This research emphases on the potentially use of a Microgrid as a resiliency source during grid restoration to pick up critical load. In this research, controllers are designed to pick up critical loads (i.e hospitals, street lights and military bases) from the distribution system in case the electric grid is unavailable. This case study includes the design of a Microgrid and it is being tested for its feasibility in an actual integration with the electric grid. Once the grid is restored the synchronization between the microgrid and electric must be conducted. Synchronization is a crucial task. An abnormal synchronization can cause a disturbance in the system, damage equipment, and overall lead to additional system outages. This thesis develops various controllers to conduct proper synchronization. Interconnecting inverterbased distributed energy resources (DERs) such as photovoltaic and battery storage within the distribution system can use the electronic devices to improve power quality. This research focuses on using these devices to improve the voltage profile within the distribution system and the frequency within the Microgrid.

69 
Preconditioning of KarushKuhnTucker Systems arising in Optimal Control ProblemsBattermann, Astrid 14 June 1996 (has links)
This work is concerned with the construction of preconditioners for indefinite linear systems. The systems under investigation arise in the numerical solution of quadratic programming problems, for example in the form of KarushKuhnTucker (KKT) optimality conditions or in interiorpoint methods. Therefore, the system matrix is referred to as a KKT matrix. It is not the purpose of this thesis to investigate systems arising from general quadratic programming problems, but to study systems arising in linear quadratic control problems governed by partial differential equations.
The KKT matrix is symmetric, nonsingular, and indefinite. For the solution of the linear systems generalizations of the conjugate gradient method, MINRES and SYMMLQ, are used. The performance of these iterative solution methods depends on the eigenvalue distribution of the matrix and of the cost of the multiplication of the system matrix with a vector. To increase the performance of these methods, one tries to transform the system to favorably change its eigenvalue distribution. This is called preconditioning and the nonsingular transformation matrices are called preconditioners. Since the overall performance of the iterative methods also depends on the cost of matrixvector multiplications, the preconditioner has to be constructed so that it can be applied efficiently.
The preconditioners designed in this thesis are positive definite and they maintain the symmetry of the system. For the construction of the preconditioners we strongly exploit the structure of the underlying system. The preconditioners are composed of preconditioners for the submatrices in the KKT system. Therefore, known efficient preconditioners can be readily adapted to this context. The derivation of the preconditioners is motivated by the properties of the KKT matrices arising in optimal control problems. An analysis of the preconditioners is given and various cases which are important for interior point methods are treated separately. The preconditioners are tested on a typical problem, a Neumann boundary control for an elliptic equation. In many important situations the preconditioners substantially reduce the number of iterations needed by the solvers. In some cases, it can even be shown that the number of iterations for the preconditioned system is independent of the refinement of the discretization of the partial differential equation. / Master of Science

70 
Application of Genetic Algorithm to a Forced Landing Manoeuvre on Transfer of Training AnalysisTong, Peter, mail@petertong.com January 2007 (has links)
This study raises some issues for training pilots to fly forced landings and examines the impact that these issues may have on the design of simulators for such training. It focuses on flight trajectories that a pilot of a singleengine general aviation aircraft should fly after engine failure and how pilots can be better simulator trained for this forced landing manoeuvre. A sensitivity study on the effects of errors and an investigation on the effect of tolerances in the aerodynamic parameters as prescribed in the Manual of Criteria for the Qualification of Flight Simulators have on the performance of flight simulators used for pilot training was carried out. It uses a simplified analytical model for the Beech Bonanza model E33A aircraft and a vertical atmospheric turbulence based on the MILF8785C specifications. It was found that the effect of the tolerances is highly sensitive on the nature of the manoeuvre flown and that in some cases, negative transfe r of training may be induced by the tolerances. A forced landing trajectory optimisation was carried out using Genetic Algorithm. The forced landing manoeuvre analyses with preselected touchdown locations and preselected final headings were carried out for an engine failure at 650 ft AGL for bank angles varying from banking left at 45° to banking right at 45°, and with an aircraft's speed varying from 75.6 mph to 208 mph, corresponding to 5% above airplane's stall speed and airplane's maximum speed respectively. The results show that certain preselected touchdown locations are more susceptible to horizontal wind. The results for the forced landing manoeuvre with a preselected location show minimal distance error while the quality of the results for the forced landing manoeuvre with a preselected location and a final heading show that the results depend on the end constraints. For certain preselected touchdown locations and final headings, the airplane may either touchdown very close to the preselected touchdown location but with greater final h eading error from the preselected final heading or touchdown with minimal final heading error from the preselected final heading but further away from the preselected touchdown location. Analyses for an obstacle avoidance forced landing manoeuvre were also carried out where an obstacle was intentionally placed in the flight path as found by the GA program developed for without obstacle. The methodology developed successfully found flight paths that will avoid the obstacle and touchdown near the preselected location. In some cases, there exist more than one ensemble grouping of flight paths. The distance error depends on both the preselected touchdown location and where the obstacle was placed. The distance error tends to increase with the addition of a specific final heading requirement for an obstacle avoidance forced landing manoeuvre. As with the case without specific final heading requirement, there is a trade off between touching down nearer to the preselected location and touching down with a smaller final heading error.

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