Geometric versus Model Predictive Control based guidance algorithms for fixed-wing UAVs in the presence of very strong wind fields.

The recent years have witnessed increased development of small, autonomous fixed-wing Unmanned Aerial Vehicles (UAVs). In order to unlock widespread applicability of these platforms, they need to be capable of operating under a variety of environmental conditions. Due to their small size, low weight, and low speeds, they require the capability of coping with wind speeds that are approaching or even faster than the nominal airspeed. In this thesis, a nonlinear-geometric guidance strategy is presented, addressing this problem. More broadly, a methodology is proposed for the high-level control of non-holonomic unicycle-like vehicles in the presence of strong flowfields (e.g. winds, underwater currents) which may outreach the maximum vehicle speed. The proposed strategy guarantees convergence to a safe and stable vehicle configuration with respect to the flowfield, while preserving some tracking performance with respect to the target path. As an alternative approach, an algorithm based on Model Predictive Control (MPC) is developed, and a comparison between advantages and disadvantages of both approaches is drawn. Evaluations in simulations and a challenging real-world flight experiment in very windy conditions confirm the feasibility of the proposed guidance approach.

An Economic Approach to Motor Vehicle Theft

Motor vehicle theft costs dearly to the Australian economy. Conservative estimates have put the annual cost of this form of illegal activity at 654 million during 1996. A number of initiatives aimed at reducing the incidence and cost of car theft have been implemented in recent years, yet statistics indicate that car theft is on the increase. Several authors have proposed an integrated approach to the regulation of markets for stolen property. Understanding property crime as a market is central to identifying approaches to its control. This paper discusses an industry model of crime and develops it on Australian data. Our model is an adaptation of one originally proposed by Vandeale (1978). It considers a production sector that uses inputs from a market of illegal labour to generate a supply of illegal goods that are traded in a product market. These sectors interact with each other and with a criminal justice sector. The model is applied to the analysis of car theft in Queensland.

Multirobot Tethering for Localization and Control

Particle filtering has proven to be an effective localization method for wheeled autonomous vehicles. For a given map, a sensor model, and observations, occasions arise where the vehicle could equally likely be in many locations of the map. Because particle filtering algorithms may generate low confidence pose estimates under these conditions, more robust localization strategies are required to produce reliable pose estimates. This becomes more critical if the state estimate is an integral part of system control. We investigate the use of particle filter estimation techniques on a hovercraft vehicle. The marginally stable dynamics of a hovercraft require reliable state estimates for proper stability and control. We use the Monte Carlo localization method, which implements a particle filter in a recursive state estimate algorithm. An H-infinity controller, designed to accommodate the latency inherent in our state estimation, provides stability and controllability to the hovercraft. In order to eliminate the low confidence estimates produced in certain environments, a multirobot system is designed to introduce mobile environment features. By tracking and controlling the secondary robot, we can position the mobile feature throughout the environment to ensure a high confidence estimate, thus maintaining stability in the system. A laser rangefinder is the sensor the hovercraft uses to track the secondary robot, observe the environment, and facilitate successful localization and stability in motion.

Control and charge management of a grid-connected photovoltaic system with plug-in hybrid vehicle as energy storage

This paper presents the control and charge management strategy of a photovoltaic system (PV) with plug-in hybrid electric vehicle (PHEV) as energy storage. The hybrid energy storage system (HESS) of PHEV consists of battery and supercapacitor. A simulation model for the PV system with PHEV energy storage has been developed using Matlab/SimpowerSystems. The system consists of PV arrays, SEPIC dc-dc converter with maximum power point tracking (MPPT), hybrid battery-supercapacitor energy storage with bidirectional dc-dc converter and inverter for grid connection. A charge management algorithm for the hybrid energy storage system is proposed to control the power flows among the PV system, energy storage and the grid. Results show that the proposed power management algorithm can control the power flows in an efficient manner.

MILITARY VEHICLE OPTIMIZATION AND CONTROL

It is remarkable that there are no deployed military hybrid vehicles since battlefield fuel is approximately 100 times the cost of civilian fuel. In the commercial marketplace, where fuel prices are much lower, electric hybrid vehicles have become increasingly common due to their increased fuel efficiency and the associated operating cost benefit. An absence of military hybrid vehicles is not due to a lack of investment in research and development, but rather because applying hybrid vehicle architectures to a military application has unique challenges. These challenges include inconsistent duty cycles for propulsion requirements and the absence of methods to look at vehicle energy in a holistic sense. This dissertation provides a remedy to these challenges by presenting a method to quantify the benefits of a military hybrid vehicle by regarding that vehicle as a microgrid. This innovative concept allowed for the creation of an expandable multiple input numerical optimization method that was implemented for both real-time control and system design optimization. An example of each of these implementations was presented. Optimization in the loop using this new method was compared to a traditional closed loop control system and proved to be more fuel efficient. System design optimization using this method successfully illustrated battery size optimization by iterating through various electric duty cycles. By utilizing this new multiple input numerical optimization method, a holistic view of duty cycle synthesis, vehicle energy use, and vehicle design optimization can be achieved.

Sticking non-stick: surface and structure control of diamond-like carbon in plasma enhanced chemical vapour deposition

This short review article explores the practical use of diamond-like carbon (DLC) produced by plasma enhanced chemical vapour deposition (PECVD). Using as an example issues relating to the DLC coating of a hand-held surgical device, we draw on previous works using atomic force microscopy, X-ray photoelectron spectroscopy, Raman spectroscopy, scanning electron microscopy, tensiometry and electron paramagnetic resonance. Utilising data from these techniques, we examine the surface structure, substrate-film interface and thin film microstructure, such as sp2/sp3 ratio (graphitic/diamond-like bonding ratio) and sp2 clustering. We explore the variations in parameters describing these characteristics, and relate these to the final device properties such as friction, wear resistance, and diffusion barrier integrity. The material and device characteristics are linked to the initial plasma and substrate conditions.

Likelihood-maximising frameworks for enhanced in-car speech recognition

Speech recognition in car environments has been identified as a valuable means for reducing driver distraction when operating non-critical in-car systems. Likelihood-maximising (LIMA) frameworks optimise speech enhancement algorithms based on recognised state sequences rather than traditional signal-level criteria such as maximising signal-to-noise ratio. Previously presented LIMA frameworks require calibration utterances to generate optimised enhancement parameters which are used for all subsequent utterances. Sub-optimal recognition performance occurs in noise conditions which are significantly different from that present during the calibration session - a serious problem in rapidly changing noise environments. We propose a dialog-based design which allows regular optimisation iterations in order to track the changing noise conditions. Experiments using Mel-filterbank spectral subtraction are performed to determine the optimisation requirements for vehicular environments and show that minimal optimisation assists real-time operation with improved speech recognition accuracy. It is also shown that the proposed design is able to provide improved recognition performance over frameworks incorporating a calibration session.

Virtual design process : design validation tool schematic approach in car carrier

An important aspect of designing any product is validation. Virtual design process (VDP) is an alternative to hardware prototyping in which analysis of designs can be done without manufacturing physical samples. In recent years, VDP have been generated either for animation or filming applications. This paper proposes a virtual reality design process model on one of the applications when used as a validation tool. This technique is used to generate a complete design guideline and validation tool of product design. To support the design process of a product, a virtual environment and VDP method were developed that supports validation and an initial design cycle performed by a designer. The product model car carrier is used as illustration for which virtual design was generated. The loading and unloading sequence of the model for the prototype was generated using automated reasoning techniques and was completed by interactively animating the product in the virtual environment before complete design was built. By using the VDP process critical issues like loading, unloading, Australian Design rules (ADR) and clearance analysis were done. The process would save time, money in physical sampling and to large extent in complete math generation. Since only schematic models are required, it saves time in math modelling and handling of bigger size assemblies due to complexity of the models. This extension of VDP process for design evaluation is unique and was developed, implemented successfully. In this paper a Toll logistics and J Smith and Sons car carrier which is developed under author’s responsibility has been used to illustrate our approach of generating design validation via VDP.

Passive control of a bi-ventricular assist device : an experimental and numerical investigation

For the last two decades heart disease has been the highest single cause of death for the human population. With an alarming number of patients requiring heart transplant, and donations not able to satisfy the demand, treatment looks to mechanical alternatives. Rotary Ventricular Assist Devices, VADs, are miniature pumps which can be implanted alongside the heart to assist its pumping function. These constant flow devices are smaller, more efficient and promise a longer operational life than more traditional pulsatile VADs. The development of rotary VADs has focused on single pumps assisting the left ventricle only to supply blood for the body. In many patients however, failure of both ventricles demands that an additional pulsatile device be used to support the failing right ventricle. This condition renders them hospital bound while they wait for an unlikely heart donation. Reported attempts to use two rotary pumps to support both ventricles concurrently have warned of inherent haemodynamic instability. Poor balancing of the pumps’ flow rates quickly leads to vascular congestion increasing the risk of oedema and ventricular ‘suckdown’ occluding the inlet to the pump. This thesis introduces a novel Bi-Ventricular Assist Device (BiVAD) configuration where the pump outputs are passively balanced by vascular pressure. The BiVAD consists of two rotary pumps straddling the mechanical passive controller. Fluctuations in vascular pressure induce small deflections within both pumps adjusting their outputs allowing them to maintain arterial pressure. To optimise the passive controller’s interaction with the circulation, the controller’s dynamic response is optimised with a spring, mass, damper arrangement. This two part study presents a comprehensive assessment of the prototype’s ‘viability’ as a support device. Its ‘viability’ was considered based on its sensitivity to pathogenic haemodynamics and the ability of the passive response to maintain healthy circulation. The first part of the study is an experimental investigation where a prototype device was designed and built, and then tested in a pulsatile mock circulation loop. The BiVAD was subjected to a range of haemodynamic imbalances as well as a dynamic analysis to assess the functionality of the mechanical damper. The second part introduces the development of a numerical program to simulate human circulation supported by the passively controlled BiVAD. Both investigations showed that the prototype was able to mimic the native baroreceptor response. Simulating hypertension, poor flow balancing and subsequent ventricular failure during BiVAD support allowed the passive controller’s response to be assessed. Triggered by the resulting pressure imbalance, the controller responded by passively adjusting the VAD outputs in order to maintain healthy arterial pressures. This baroreceptor-like response demonstrated the inherent stability of the auto regulating BiVAD prototype. Simulating pulmonary hypertension in the more observable numerical model, however, revealed a serious issue with the passive response. The subsequent decrease in venous return into the left heart went unnoticed by the passive controller. Meanwhile the coupled nature of the passive response not only decreased RVAD output to reduce pulmonary arterial pressure, but it also increased LVAD output. Consequently, the LVAD increased fluid evacuation from the left ventricle, LV, and so actually accelerated the onset of LV collapse. It was concluded that despite the inherently stable baroreceptor-like response of the passive controller, its lack of sensitivity to venous return made it unviable in its present configuration. The study revealed a number of other important findings. Perhaps the most significant was that the reduced pulse experienced during constant flow support unbalanced the ratio of effective resistances of both vascular circuits. Even during steady rotary support therefore, the resulting ventricle volume imbalance increased the likelihood of suckdown. Additionally, mechanical damping of the passive controller’s response successfully filtered out pressure fluctuations from residual ventricular function. Finally, the importance of recognising inertial contributions to blood flow in the atria and ventricles in a numerical simulation were highlighted. This thesis documents the first attempt to create a fully auto regulated rotary cardiac assist device. Initial results encourage development of an inlet configuration sensitive to low flow such as collapsible inlet cannulae. Combining this with the existing baroreceptor-like response of the passive controller will render a highly stable passively controlled BiVAD configuration. The prototype controller’s passive interaction with the vasculature is a significant step towards a highly stable new generation of artificial heart.

Operation and control of a microgrid containing inertial and non-inertial micro sources

In this paper, a new power sharing control method for a microgrid with several distributed generation units is proposed. The presence of both inertial and noninertial sources with different power ratings, maximum power point tracking, and various types of loads pose a great challenge for the power sharing and system stability. The conventional droop control method is modified to achieve the desired power sharing ensuring system stability in a highly resistive network. A transformation matrix is formed to derive equivalent real and reactive power output of the converter and equivalent feedback gain matrix for the modified droop equation. The proposed control strategy, aimed for the prototype microgrid planned at Queensland University of Technology, is validated through extensive simulation results using PSCAD/EMTDC software.

Sustainable transport and the impact on the built environment : Future trends and directions

We love the automobile and the independence that it gives us. We are more mobile than we have ever been before in recorded history. In Australia 80% of journeys are by private motor vehicle. But it is becoming increasingly obvious that this era has a very limited lifespan. Fuel prices have skyrocketed recently with no end in sight. In spite of massive amounts of road construction, our cities are becoming increasingly congested. We desperately need to address climate change and the automobile is a major contributor. Carbon trading schemes will put even more upward pressure on fuel prices. At some point in the near future, most of us will need to reconsider our automobile usage whether we like it or not. The time to plan for the future is now. But what will happen to our mobility when access to cheap and available petroleum becomes a thing of the past? Will we start driving electric/hydrogen/ethanol vehicles? Or will we flock to public transport? Will our public transport systems cope with a massive increase in demand? Will thousands of people take to alternatives such as bicycles? If so, where do we put them? How do we change our roads to cope? How do we change our buildings to suit? Will we need recharging stations in our car park for example? Some countries are less reliant on the car than others e.g. Holland and Germany. How can the rest of the world learn from them? This paper discusses many of the likely outcomes of the inevitable shift away from society’s reliance on petroleum and examines the expected impact on the built environment. It also looks at ways in which the built environment can be planned to help ease the transition to a fossil free world. 1.

Fusion of in-vehicle sensor data to develop Intelligent Driver Training System (IDTS)

The over represented number of novice drivers involved in crashes is alarming. Driver training is one of the interventions aimed at mitigating the number of crashes that involve young drivers. To our knowledge, Advanced Driver Assistance Systems (ADAS) have never been comprehensively used in designing an intelligent driver training system. Currently, there is a need to develop and evaluate ADAS that could assess driving competencies. The aim is to develop an unsupervised system called Intelligent Driver Training System (IDTS) that analyzes crash risks in a given driving situation. In order to design a comprehensive IDTS, data is collected from the Driver, Vehicle and Environment (DVE), synchronized and analyzed. The first implementation phase of this intelligent driver training system deals with synchronizing multiple variables acquired from DVE. RTMaps is used to collect and synchronize data like GPS, vehicle dynamics and driver head movement. After the data synchronization, maneuvers are segmented out as right turn, left turn and overtake. Each maneuver is composed of several individual tasks that are necessary to be performed in a sequential manner. This paper focuses on turn maneuvers. Some of the tasks required in the analysis of ‘turn’ maneuver are: detect the start and end of the turn, detect the indicator status change, check if the indicator was turned on within a safe distance and check the lane keeping during the turn maneuver. This paper proposes a fusion and analysis of heterogeneous data, mainly involved in driving, to determine the risk factor of particular maneuvers within the drive. It also explains the segmentation and risk analysis of the turn maneuver in a drive.

Heavy truck suspension optimization based on modified skyhook damping control

This paper presents a multi-objective optimization strategy for heavy truck suspension systems based on modified skyhook damping (MSD) control, which improves ride comfort and road-friendliness simultaneously. A four-axle heavy truck-road coupling system model was established using functional virtual prototype technology; the model was then validated through a ride comfort test. As the mechanical properties and time lag of dampers were taken into account, MSD control of active and semi-active dampers was implemented using Matlab/Simulink. Through co-simulations with Adams and Matlab, the effects of passive, semi-active MSD control, and active MSD control were analyzed and compared; thus, control parameters which afforded the best integrated performance were chosen. Simulation results indicated that MSD control improves a truck’s ride comfort and roadfriendliness, while the semi-active MSD control damper obtains road-friendliness comparable to the active MSD control damper.

A study on matching and multi-objective fuzzy control strategy of heavy truck suspension system

Matching method of heavy truck-rear air suspensions is discussed, and a fuzzy control strategy which improves both ride comfort and road friendliness of truck by adjusting damping coefficients of the suspension system is found. In the first place, a Dongfeng EQ1141G7DJ heavy truck’s ten DOF whole vehicle-road model was set up based on Matlab/Simulink and vehicle dynamics. Then appropriate passive air suspensions were chosen to replace the original rear leaf springs of the truck according to truck-suspension matching criterions, consequently, the stiffness of front leaf springs were adjusted too. Then the semi-active fuzzy controllers were designed for further enhancement of the truck’s ride comfort and the road friendliness. After the application of semi-active fuzzy control strategy through simulation, is was indicated that both ride comfort and road friendliness could be enhanced effectively under various road conditions. The strategy proposed may provide theory basis for design and development of truck suspension system in China.