It is well-known that there are no general approaches for observer and controller design for nonlinear systems. Instead, focus is placed upon design for classes of systems. On the other hand, a wide variety of dynamical systems belong to the class of state-affine systems. Amongst these are biological wastewater treatment processes, which are essential in order to prevent pollution in the environment and prevent disease in the consumption of recycled water. An interesting aspect found in biological wastewater treatment systems, and many typical industrial processes, are time-delays. In almost all systems there are time-delays and nonlinearities and it is not surprising that time-delay and nonlinear systems have received a great deal of attention in mathematics and control engineering. This project introduces new methodologies for the design of controllers and observers for a class of state-affine systems and a class of linear time-delay systems. Firstly, new observable and controllable canonical forms are introduced. These are then used to establish new controller and observer design methodologies for a class of state¬affine systems. In particular, an adaptive observer design is established. The methodologies are simple since they are based upon linear techniques. Secondly, a full-state controller and a separation principle are established for a class of single-input single-output linear time-delay systems. The designs are based on a new stability criterion and are derived from first principles. Finally, the new observer design methodology for the class of state-affine systems is used to produce observers for the estimation of biomass concentration in a biological wastewater treatment bioreactor. The observers are applied in theory and in simulation, where a full and a partial knowledge of the kinetic rate of reaction of biomass are considered. In addition, the performances are shown both in the absence and in the presence of measurement noise for a variety of influent flow characteristics.

Redundancy allocation, in the context of reliability driven design, is the process of multi-objective optimisation of system configuration with reliability and cost related objectives. Large systems, of any type and discipline, can be divided into several subsystems comprising modules and components. Such a hierarchical form of system arrangement is regarded as multilevel configuration. These systems have the performance capability beyond traditional binary reliability framework of either completely working or totally failed. Large systems normally have redundancies at different levels. In current practice, multi-level redundancy allocation takes place sequentially. This is mainly due to lack of a robust optimisation method capable of delivering large scale redundancy allocation problems. Development of such methods leads to design of enhanced systems with better performance in terms of cost and reliability. The overall aim of this project is to develop a method for multi-state reliability optimisation of large real-world systems. To achieve the overall goal, firstly, a genetic algorithm (GA) suitable for analysis of systems with multi-level redundancies is developed. For this GA, new multi-level chromosome, new crossover and mutation operators capable of combining building blocks at different level and mutation of solutions at various levels are designed. Whilst the GA chromosome and regeneration operators are specially designed for handling multi-level systems, in the second step a Non-dominated sorted genetic algorithm (NSGA-II) is developed for multi-dimensional search towards finding Pareto frontier solutions with respect to a number of cost-related, performance-related and reliability-rated objectives including cost, size, weight, availability and failure rate. In the final stage, the developed search and optimisation methods are implemented in a software tool written in MATLAB. Employing the optimisation tool for benchmark problems with multi-level redundancies, heating, ventilation and air conditioning (HVAC) systems, it has been shown how an integrated multi-level redundancy allocation, as opposed to sequential redundancy allocation, can lead to superior solutions.

Functionally graded materials (FGMs) are a novel class of materials having unique characteristics formed of two or more constituent phases with a continuously variable composition. The introduction of these materials to the sandwich structures creates more potentials to the structural applications with the ability of tailoring the material properties as well as the possibility of avoiding the delamination and stress concentration in conventional sandwich structures. With the rapid development of technology, it is now common to use FGMs in micro/nanoelectromechanical systems, e.g. thin films, sensors, actuators and other devices. At these scales, the use of experimentation to understand the structural behaviours is difficult and highly time-consuming, whilst the molecular modelling is computationally very expensive for the scales that are popular to structural engineers. Therefore, higher-order continuum theories, which were developed from the classical continua, become very popular in modelling micro/nano-scale structures. Based on one of these higher-order continuum theories namely the modified couple stress theory, this thesis aims to develop the analytical methods, i.e. Navier and state space based solutions, to analyse the static, free vibration and buckling behaviours of FG and FG-sandwich beams and plates. The governing equations and appropriate boundary conditions are developed for these structural behaviours of beams and plates at both micro and macro- scales using the variational principle. Numerical results are computed using MATLAB and verified with the published results to demonstrate the accuracy and efficiency of the developed theoretical formulation. The numerical applications include: · the free vibration and buckling behaviours of FG and FG sandwich macrobeams under arbitrary boundary conditions and mechanical/thermal loads, · the static, free vibration and buckling behaviours of simply supported FG microbeams, and the free vibration behaviour of bidirectional FG microbeams under arbitrary boundary conditions, · the static, free vibration and buckling behaviours of simply supported FG-sandwich microplates under mechanical/thermal loads, · the static, free vibration and buckling behaviours of FG-sandwich microplates with two opposite simply supported edges and various boundary conditions for other edges. The outcomes from this thesis emphasize the need of including couple stress in analyzing the structural behaviours of FG beams and plates at microscales. Some of them are presented at the first time and can be used as the benchmark results for numerical methods. These analytical methods can also be combined with other strong form methods to analyse various types of complex structures.

Rising concerns on climate change due to greenhouse gases have led to the UK Climate Change Act 2008 which sets a target to cut CO2 emissions by 80% of 1990 levels by 2050. Photovoltaic (PV) systems form one of the main technologies capable of delivering the target. Though the ability to deliver reductions in the installed costs of PV will determine the level of sector growth, this growth could be limited by several technical factors. As about 90% of the number of PV systems installed in the UK belong to the category of residential systems with individual ratings less than 4 kW, this study focuses on this sector. This sector represents 20% of the total installed capacity in the UK. This research aims to identify the key technical barriers and associated solutions to increase PV penetration in a distribution network in the UK. The research defines the realistic worst-case scenario to evaluate the performance of the distribution network with PV and then quantifies the percentage of PV penetration at which the presence of PV may adversely affect the performance of the distribution network. The steady-state analysis conducted shows that the voltage at parts of the feeder violates the statutory limits at 20% penetration for the realistic worst-case scenario, followed by reversal of net active power and low power factor at the secondary of the substation when penetration level is over 30%. The results indicate that the minimum load of the feeder under consideration during hours of daylight and the more common irradiance level at that geographic location should be used rather than a hypothetical worst-case scenario to evaluate the maximum allowable contribution of PV systems in the feeder. Analysis of the performance of distribution networks under fault indicates that the tripping time of the relay may be delayed under the presence of PV. However, the probability of false tripping of the relay is very low. This research also identifies solutions to increase the contribution of PV systems in the energy mix and evaluates the effectiveness of the solutions. The solutions in the order of decreasing effectiveness are changes to tap changer settings, reactive power control and PV generation curtailment. A strategy to increase the contribution is proposed. This includes changes to the settings of the tap changer (increases the PV contribution from 20 to 40%) followed by active power curtailment (which would increase PV contribution from 40 to 60%). A phased approach like this would enable the regulators to plan for the transitionary period to increase the contribution of PV.

As electrical energy prices continue to rise, accurate energy consumption monitoring is becoming increasingly important and the introduction of smart energy meters is well-known in this capacity. One of the key components in the smart energy meter is the current sensing shunt resistor and its resistance must be as low as possible, typically in the range 100 μΩ to 10 mΩ, to minimise energy usage. Although this low resistance requirement reduces power consumption, it is inherently difficult to manufacture shunt resistors in this micro-ohm range to the required precision and at reasonable cost. Typical resistance accuracy of commercially available shunts suitable in this application is 100 μΩ ±5%, which can in turn lead to ±5% errors in power measurement within the smart meter. This research presents a novel automated electro-mechanical trimming process to improve the accuracy and performance of 100 μΩ Manganin shunt resistors for use in smart energy meters. Theoretical and experimental investigations were carried out to determine the optimum technique and design geometry to remove the resistive material from the shunt. More specifically, the work focuses on the development of the precision trimming process to improve the resistance tolerance of the shunt resistors. A novel laboratory prototype of an automated concurrent trimming system is developed which combines the mechanical cutting process and electrical measurement system to remove controlled amounts of material from the Manganin shunt. Design of Experiments (DoE) is then conducted in order to find the optimum feed rate and cutting speed for the trimming process. The effects of under a varying the trimming geometry on the key performance crietria of the shunt resistors was investigated by simulating the conditions that the shunts will exposed to when positioned within a high current circuit and encapsulated within a smart energy meter. Tests have examined changes in physical structural conditions as well as electrical properties under a varying environmental conditions. By using concurrent trimming, the tolerance of the Manganin shunt resistors has been reduced from ±5% to less than ±1% within 5 seconds. Trimming does not have a significant effect on the key properties of the shunt resistors and the results obtained can be used to inform production processes for large scale manufacture of precision shunt resistors.

This investigation focuses and analyses the theoretical and practical performance of a dynamic system, which affords condition monitoring and robust fault diagnosis. The importance of robustness in fault diagnosis is becoming significant for controlled dynamic systems in order to improve operating reliability, critical-safety and reducing the cost often caused by interruption shut down and component repairing. There is a strong motivation to develop an effective real-time monitoring and fault diagnosis strategy so as to ensure a timely response by supervisory personnel to false alarms and damage control due to faults/malfunctions. Environmental disturbances/noises are unavoidable in practical engineering systems, the effects of which usually reduce the diagnostic ability of conventional fault diagnosis algorithms, and even cause false alarms. As a result, robust fault diagnosis is vital for practical application in control systems, which aims to maximize the fault detectability and minimize the effects of environment disturbances/noises. In this study, a genetic algorithm (GA) optimization model-based fault diagnosis algorithm is investigated for applications in wind turbine energy systems and induction motors through concerns for typical types of developing (incipient) and sudden (abrupt) faults. A robust fault detection approach is utilized by seeking an optimal observer gain when GA optimisation problems become solvable so that the residual is sensitive to the faults, but robust against environmental disturbances/noises. Also, robust fault estimation techniques are proposed by integrating augmented observer and GA optimisation techniques so that the estimation error dynamics have a good robustness against environmental disturbances/noises. The two case studies investigated in this project are: a 5MW wind turbine model where robust fault detection and robust fault estimation are discussed with details; and a 2kW induction motor experimental setup is investigated, where robust fault detection and robust fault estimation are both examined, and modelling errors are effectively attenuated by using the proposed algorithms. The simulations and experimental results have demonstrated the effectiveness of the proposed fault diagnosis methods.

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This thesis presents the application of coplanar circuit analysis in the design of compact single-feed circularly polarised (CP) and linearly polarised (LP) microstrip patch antennas. A CP nearly square patch antenna and a CP truncated corners square patch antenna are designed. Also a LP U-slot rectangular patch antenna is designed. In order to obtain a faster computational run-time, coplanar circuit analysis and segmentation method are applied for the impedance calculations. The coupling and self impedance formulas for both rectangular and right-angled isosceles triangular segments are given. Explicit formulas for the coupling impedance between a perimeter port and a probe port, and also the probe self impedance on both of these segments are new and are derived in detail. A CP nearly square patch antenna is designed using both the cavity and equivalent circuit models. New and simple design equations are derived to determine the dimensions of the patch with a feed in any given position. For a microstrip feed offset from a corner of the patch, the area of perturbation segment is increased which reduces the effect of manufacturing errors. A simple matching network consisting of a short length of microstrip line is designed to achieve a more compact form of the matched antenna. The results obtained from both models are good agreement. A CP truncated corners square patch antenna with a microstrip feed offset from the centre is presented. In previous work the design is a feed along the centre line and the areas of the deleted segments are very small so the performance of the antenna is very sensitive to manufacturing errors. Hence an offset feed is proposed in order to increase the perturbation area and so reduce the effect of the manufacturing errors. The segmentation method is used for which a new explicit matrix input impedance formula is derived. The impedance formula requires a computer run time less than half that required by simulation (full-wave software, Ansoft Ensemble). The change in area of the perturbed segment and input impedance with the microstrip offset feed position is examined. A compromise offset feed position was chosen so as to maximise the area of the perturbation segment and achieve good impedance matching for a compact antenna structure. A LP probe feed U-slot rectangular patch is designed and the input impedance is determined. A set of initial design equation is used to produce a first-pass design. In applying segmentation method a new explicit input impedance formula for the antenna is derived. The basic system of eleven coplanar circuit equations is reduced to seven equivalent circuit equations from which the explicit impedance formula is derived. The dimensions of the patch are adjusted to give good impedance matching. In respect of computational efficiency, the run time of the new matrix input impedance formula is at least 10 times faster than is required by simulation. A thicker substrate is also used in order to improve the bandwidth. The predicted, simulated and measured results of the above three compact patch antennas are in good agreement. Mathcad programming is used to implement the design calculations of the compact patch antennas.

In this thesis the development of light emitting diodes (LED) is reviewed. The emphasis is put on devices emitting at the blue region of the spectrum. The physical characteristics of these devices are considered. The main interest is based around the ability of blue LEDs to generate nanosecond range optical flashes. The fast pulsing electronic circuits capable of driving the devices are also reviewed. These are complemented by the potentially exploitable techniques that could provide further benefits for required fast optical pulse generation. The simple, compact and inexpensive electronic oscillator for producing nanosecond range pulses is developed. The circuitry is adapted for generation of pulses necessary to switch on and assist with the turn off of blue InGaN based LEDs. The resulting nanosecond range blue optical pulses are suitable for, but not limited to, the calibration of scintillation counters. These devices used in neutrino detection experiments could provide a better understanding of cosmology and particle physics.

In recent years, there has been growing interest towards integrating industry into the teaching and learning processes. This is due to many factors including increased concerns about the mismatch between the skills and abilities of the talent pool, strengthening partnership and improving quality of engineering education. Thus, greater emphasis on the teaching and learning processes to enhance the students’ learning experience leads to the university-industry partnership to the forefront interest of the university. On the other hand, exclusion of industry’s engagement in the teaching and learning processes have been identified as the main source of chronic criticism on the higher engineering education segment in recent years. This study demonstrates a research model that hypothesised the influence of teaching and learning domains on the university-industry partnership towards enhancing the learning experience of the engineering students. Using the structural equation modelling (SEM), the hypothesis was tested on the primary data collected from 212 communities of the industry. Furthermore, the study investigated the preference of industry on the type of linkages to foster university-industry partnership using analytical hierarchy process (AHP). The results revealed that nine out of the thirteen hypotheses had significant associations including six direct paths and three indirect effects in the model. The findings indicated the need for industry-university partnership in three main constructs including cooperation in education, the mobility of people and intellectual enhancement. Moreover, internship programme was the important linkage in achieving the overall university-industry partnerships goals, followed by the staff training programme, academic development, consultancy work, student learning activity and publication activity. In summary, the study demonstrates that teaching and learning relevance could be enhanced through optimizing industry’s enrichment activities into the learning process, improving the measures for accreditation in narrowing the gap between theory and practice and proactively improving the quality of teaching by exploring the staff training programmes.