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  • 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.

Performance enhancement of a fluidic oscillator

Furmidge, Neil January 1996 (has links)
The operational performance criteria of fluidic oscillators are described in relation to the requirements of a domestic water meter. The problems associated with developing a novel water meter using fluidic oscillatory technology are discussed and the performance enhancements required to develop a fluidic oscillator capable of meeting the BS5728 (1979) domestic water meter specifications are presented. A sensing configuration is described which provides adequate sensitivity over the range required for a water meter with a nominal flowrate of one cubic meter per hour. The nozzled imensions are investigated to reduce the pressure drop across the fluidic water meter whilst still maintaining the required turndown range and adequate sensitivity at low flowrates. The development of a novel fluidic oscillator flow conditioning device is described which radically improves the linearity of the fluidic oscillator and helps to reduce susceptibility to upstream disturbances. The device allows debris to pass through the meter without causing blockage and has an acceptable low pressure drop. Modifications to the fluidic oscillator transducer geometry are investigated which reduce the minimum point of oscillation, thus increasing the turndown range of the water meter. Also geometry modifications are developed which improve the strength of the jet oscillation at low flowrates and thereby significantly increase the strength of signal. The effects of geometry modification on meter linearity and meter factor response are investigated and a transducer design with enhanced range performance and improved linearity is described. Transducer designs are presented which are capable of meeting the BS5728 (1979) specification for both Class C and Class D QNLO domestic water meters.

The dynamics of obstacle traversal during terrestrial locomotion

Daniels, Katherine Alice Jane January 2013 (has links)
Obstacles in the path of travel are a common feature of natural and built environments. The ability to negotiate such terrain, traversing rather than avoiding obstacles, increases the versatility of animal locomotion. The aim of this thesis was to investigate how and why humans and dogs select characteristic changes to gait for obstacle traversal. In a series of experiments, subjects were presented with different types of obstacle and the kinematics of locomotion used to traverse them recorded. Fundamentally different traversal strategies viable for overlapping ranges of obstacle dimensions were identified based on the characteristic kinematics of traversal behaviour. Obstacle traversal strategies were systematically selected based on the dimensions of the obstacle. Adaptations to gait in advance of traversal were shown generally to be localised to the obstacle. The maximum amount by which step length was increased to leap over an obstacle was invariant with approach speed, although the mechanism for lengthening the step changed fundamentally with increasing speed of travel. Preferred traversal dynamics were associated with the minimisation of mechanical energy cost in some but not all of the obstacle conditions investigated. The position of the baseline of the obstacle was identified as an important property for the visual judgement of obstacle position. This body of work provides insight into the control of legged locomotion over irregular terrain. It has potential applications in the design of autonomous legged vehicles.

On the design of policies for the inspection, repair and replacement of 2-Phase Systems with Ageing. When can error-prone sensors help?

MacPherson, Andrew Jonathan January 2011 (has links)
The deterioration observed in many industrial systems may be modelled in two phases. In the first phase, a period during which the system operates fault free ends with entry into a worn state. In the second phase, the system spends time in the worn state prior to failure. Should the system be found to be in the worn state upon inspection, failure can be pre-empted by preventive maintenance. The first goal of analysis is the design of cost effective policies for the inspection, repair, and renewal of such systems. The thesis extends previous work by offering a choice between a (cheap) repair and a (more expensive) renewal of the system, should it be found to be in the worn state upon inspection. The decision-maker may also renew the system at any time without inspection. Simple, cost effective heuristic policies are proposed, whose design avoids the computational complexities of a full dynamic programming (DP) solution. The second goal of analysis is to determine when deployment of an error-prone sensor may be beneficial to the operation of such systems. It is supposed that a system is monitored continuously by such a sensor, which returns a positive result should entry into the worn state be detected. The sensor may produce errors of both kinds, false-positive and false-negative. Extending the earlier work of the thesis, simple, cost effective heuristics are developed for use with the sensor. In se- -i 11 lected cases, numerical investigation identifies operational characteristics for which use ofa sensor is (i) cost indifferent, (ii) beneficial, and (iii) not beneficial. The question of how sensor quality impacts upon heuristic design is also investigated. To the author's knowledge, the model proposed in this section of the thesis is new to the literature.

Routing and mission planning in autonomous systems

Razzaq, Sohail January 2012 (has links)
Autonomous systems are playing increasingly important roles in today's world. Technological advancements have allowed autonomous applications in many areas such as ground robotics (including factory robots), unmanned aerial vehicles (UAVs), unmanned underwater vehicles, unmanned spacecrafts etc. UAVs are relatively a new inclusion into the broader field of autonomous systems. The possibility of using UAVs for a diverse range of beneficial applications such as fire fighting, search and rescue missions, combating crime, etc. is a major motivational factor in this research program. Thus mission related work presented in this thesis, although generic In nature, relates heavily to UAVs. Mission planning involves many dimensions In general and the fundamental aspects explored in this research program i.e. route planning, resource allocation optimization, vehicle selection and mission collaboration, in particular. At the end of this research program a novel graph theoretic routing algorithm that offers deconfliction and efficient route computation has been developed and its performance experimentally examined using computer simulations. In addition, novel exhaustive as well as sub-optimal resource allocation mission planning schemes have been developed and applied to both deterministic and stochastic input variables. Furthermore the significant benefits obtained during a mission due to collaboration between acting UAVs have been examined and experimentally demonstrated. This collaborative behaviour has been achieved via the inclusion of data communication between UAVs and the mission Control Centre and in a way that allows for UAVs to coordinate their time of arrival to destination and thus maximize mission success.

Design and Modelling of Adaptive Foraging in Swarm Robotic Systems

Liu, Wenguo January 2008 (has links)
Swann robotics is a new approach to coordinate the behaviours of large number of relatively simple robots in decentralised manner. As the robots in the swann have only local perception and very limited local communication abilities, one of the challenges in designing swann robotic systems with desired collective behaviour is to understand the effect of individual behaviour on the group performance. This thesis dedicates the research on design and optimisation of interaction rules for a group of foraging robots that try to achieve energy efficiency collectively. The investigation starts with designing a set of interaction rules for the individual robots, inspired from the widely observed self-organisation phenomenon in biological system, so as improve the energy efficiency at the group level. A threshold-based controller, using two internal time thresholds - resting time and searching time threshold, is introduced to regulate the behaviours for the robot in order to improve the energy efficiency. Three cues: internal cues, social cues and environmental cues are then proposed to adjust the internal time thresholds in a self-organised manner. A number of strategies have been developed by combining these three cues and applied to the collective foraging task. Although the simulation results show that the robot swarm with adaptation mechanisms has the ability to guide the system towards energy optimisation collectively, there are difficulties in manually finding a set of parameters for the adaptation algorithm which can lead to the best energy efficiency under certain environmental conditions. This thesis focuses most of its effort into developing a macroscopic probabilistic model to understand the effect of individual parameters (internal time thresholds) on the performance of the system and therefore help to design the adaptation algorithm more efficiently. The modelling work is divided in two stages: A simplified situation for a swarm of homogeneous foraging robots without adaptation mechanism is considered first, then the macroscopic probabilistic model is extended for a robot swann with full adaptation ability. 3 The essential idea of the probabilistic modelling approach is to treat the interactions among robots, or between robots and environment, as stochastic events. First, a probabilistic finite state machine (PFSM), adapted from the robot controller, is used to describe the foraging task at the group level. A number of difference equations are then developed to capture the change of number of robot in each state. The state transition probabilities and other parameters used in the model are obtained through a novel geometrical approach, which makes sure that no free parameters exist in the model. In addition, the adaptation rules are encoded into the difference equations by introducing the concept of private resting/searching time thresholds and public resting/searching time thresholds. The proposed macroscopic model has been validated using simulation. The results show that the model achieves very good accuracy in predicting the net energy of the swarm, not only in the final stage but also in the instantaneous level. Finally, with the extended macroscopic model, a real-coded steady-state genetic algorithm (GA) is introduced to simplify the process of parameters selection for the adaptation algorithms. Experiments are carried out using the the best set of parameters found by the GA. It shows that the robot swarm with selected parameters can achieve a near-optimal energy efficiency under different environmental conditions.

Numerical methods for solving certain distributed parameter optimal control problems

Holliday, John H. January 1972 (has links)
In this work certain kinds of distributed parameter optimal control problem are considered, governed by non-linear partial differential equations of parabolic and hyperbolic type. Conditions necessary for optimality are developed. These are used to derive a range of numerical algorithms for solution of the control problem. Also described is an algorithm searching directly on the performance index, without requiring satisfaction of the necessary conditions. Five system examples exhibiting a wide range of distributed parameter system features are analysed using the different numerical methods and results are compared. A general discussion of the main characteristics' of the algorithms is given.

Agent based mission planning for multiple unmanned autonomous vehicles

Maqbool, Ayesha January 2012 (has links)
This thesis presents novel methods for agent-based mission planning sys- tem for multiple unmanned autonomous vehicles (MUAV). MUAV mission planning is the pinnacle of the intelligent systems. The ever-changing ad- verse environment and real-time co-operative decision making adds to the complexity of the system. Due to these inherent complexities, the progress from autonomic to autonomous MUAV system is still in its infancy. The conventional methods of distributed planning and decision making have shown some benefits but are not sufficient to develop the co-operative intelligence in MUAV system. Here we present agent-based approach for developing MUAV mission planning system by in-cooperative intelligent behaviours for self-organisation, self-awareness and intelligent decision making. These co-operative behaviours are aimed to add autonomy to the system. The requirements, interactions, functionalities and the role of these methods in overall system are established by in-depth study of existing control frameworks for MUAV management system. We also present a unified framework for NIUAV mission planning. This functional based framework provides a better yet simple understanding of the otherwise complex system. It serves the purpose of providing a better understanding of the challenges and opportunities in development of MUAV system by providing logical system construction of the MUAV mission planning in detail. To facilitate the self-awareness of the MUAV system, an efficient Advanced Integrated Method (AIM) path planning method is developed. AIM generates optimum obstacle free path from source to destination the consideration of UAV's safety. It combines the existing methods of Artificial potential, Maximum Clearance and Self Organizing Maps (SOM) for guaranteed convergence. We also present a model for the prediction of the future states of moving targets as stochastic processes with associated learned transition probabilities using Discrete Markov Chains (DMC). These predictions are then used for developing interception based target tracking. These predictions also provide fair and effective mean for target allocation among multiple UAV's and for target selection in the presence of multiple targets. The co-operative behaviour for MUAV system is further supported by a new and effective method of self-organisation. Inspired from thermodynamic systems, it introduces co-operative self-allocation of mission space with the objective of sharing surveillance responsibilities. These methods for path planning, prediction based decision making and self-allocation collectively provide the groundwork for building autonomous MUAV system.

Swarm intelligence modelling and active vibration control of flexible structures

Mohamad, Maziah January 2011 (has links)
This thesis presents investigations into development of modelling and control of flexible structures using swarm intelligence optimisation techniques. A smart flexible beam structure is used in this work as a candidate application. The smart flexible beam model is developed using finite difference method and a methodology of incorporating piezoelectric patch actuator into finite difference model is presented. The simulation model is developed in MATLAB/SIMULINK environment as a platform for test and verification of the control approaches developed in this work. Many heuristic search algorithms have been inspired by nature such as genetic algorithm (natural evolution), artificial neural network (biological neuron) and artificial immune system (immune system) where the algorithms try to mimic the biological process. Addition to nature inspired algorithms is the swarm intelligence method which has been inspired by the natural behaviour of a group of insects like foraging, flocking and schooling in ants, bees, fish and birds where particle swam optimisation (PSO) and ant colony optimisation (ACO) are the most popular methods. The study of parameter setting for PSO and continuous ACO (ACOr) is studied through parametric modelling of the beam. The performance of each algorithm in terms of computational time and convergence is discussed. In this study, vibration control of a flexible beam structure is developed based on the principle of wave interference, to result in optimal cancellation with adaptive model-based control and adaptive direct control. A single objective optimisation algorithm is developed and implemented using PSO and continuous ACO considering two conditions; optimisation of controller with pre-selected location of sensor and actuator and simultaneous optimisation of controller parameters and sensor and actuator location in single-input-single-output and single-input-multiple-output configurations. While single objective optimisation provides only one solution, the use of multi-objective optimisation results in several solutions to choose for implementation. An approach of multi-objective optimisation of controllers' parameters and sensor/actuator location is developed based on minimising vibration energy and minimising actuator force. Multi-objective PSO and multi-objective ACOr algorithms are developed in finding optimal system setup and controller parameters for AYC of the beam. Both PSO and ACO based algorithms are tested and their performances assessed in vibration control of the beam.

Monolithic design of flexible actuators for operation in confined liquid environments

Sareh, Sina January 2012 (has links)
This thesis presents novel contributions to the design, modelling and physical implementation of soft biomimetic actuators for operation in liquid environments. Single DOF and multi DOF monolithic actuators are designed by exploiting kirigami and electrical multi-segmentation techniques. Single degree of freedom actuators, Burstbot and Vonibot, are designed capable of generating complex biologically-inspired actuation profiles resembling the flexion of the mammalian cuspid valve and the coiled contractions of the Vorticella respectively_ The symmetric and asymmetric fluid interact ions of the Burstbot are investigated and the effectiveness in fluid transport applications is demonstrated. The Vortibot actuator is geometrically optimized as a camera positioner capable of 360 degree scanning. An artificial cilium actuator is developed based on quantitatively mimicking the structural design and stroke planar kinematics of the natural cilium. This actuator is modelled on the cilia movement of the alga Volvox, and represents the cilium as a piecewise constant-curvature robotic actuator that enables the subsequent direct translation of natural articulation into a multi-segment ionic polymer metal composite actuator. It is demonstrated how the combination of optimal segmentation pattern and biologically derived per-segment driving signals reproduce natural ciliary motion. The amenability of the artificial cilia to scaling is also demonstrated through the comparison of the Reynolds number achieved with that of natural cilia.

New developments in autotuning of PID controllers using model reference adaptive control and neural networks

Pirabakaran, Kandasamy January 2005 (has links)
No description available.

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