Integrated Feedback Control in Future Wireless Communication Networks. The aim of this project is to develop and analyse new feedback control methods to address emerging challenges in future wireless communication networks such as 5G. This new generation of mobile communications promises exceptional bandwidth, high reliability and low link delay. To achieve these leaps in performance, a paradigm shift to massive multiple-input-multiple-output (MIMO) antenna systems, very high frequency systems a ....Integrated Feedback Control in Future Wireless Communication Networks. The aim of this project is to develop and analyse new feedback control methods to address emerging challenges in future wireless communication networks such as 5G. This new generation of mobile communications promises exceptional bandwidth, high reliability and low link delay. To achieve these leaps in performance, a paradigm shift to massive multiple-input-multiple-output (MIMO) antenna systems, very high frequency systems and small cells is required. Critical feedback loops in areas such as narrow 3D beam steering for mobile users, control of multiflow systems must be developed to enable 5G communications to be successfully deployed. This new generation of communications is also expected to open up new control application domains, such as the use of vehicle-to-vehicle networks.Read moreRead less
Scheduling and quality of service in Long Term Evolution telecommunications. There is an explosion of mobile telecommunications with over 50 billion connections expected by 2020. The next generation of mobile broadband will be based on a new technology known as Long Term Evolution (LTE) and, in this context, the goal of this project is to improve the efficiency of these systems by developing new techniques for scheduling.
Learning deep resilient behaviour for uncertainty-aware autonomy. This research project aims to propose a novel framework for developing uncertainty-aware autonomous systems using deep learning. There are fundamental gaps in our knowledge of deep uncertainty quantification and its application for risk-aware decision making. Novel algorithms will be proposed to reliably generate deep uncertainty estimates with low computational overhead. These estimates will be then exploited by safety-critical s ....Learning deep resilient behaviour for uncertainty-aware autonomy. This research project aims to propose a novel framework for developing uncertainty-aware autonomous systems using deep learning. There are fundamental gaps in our knowledge of deep uncertainty quantification and its application for risk-aware decision making. Novel algorithms will be proposed to reliably generate deep uncertainty estimates with low computational overhead. These estimates will be then exploited by safety-critical systems such as autonomous robots to identify risky actions and avoid catastrophise. Developed algorithms will be implemented on an autonomous robotic system to make it averse to uncertainties. The outcomes will greatly increase reliable telerobotic applications in mining, manufacturing, defence, and health.Read moreRead less
Robustness, resilience and security of networked dynamic systems. This project will develop advanced digital control techniques to address security, resilience and robustness in complex networks and deliver fundamental advances in the technology for secure and reliable networks. The project will advance the theory on consensus of networked multi-agent systems to facilitate the fast adoption of the internet of things and the continuous growth of cyber-physical systems These systems in many cases ....Robustness, resilience and security of networked dynamic systems. This project will develop advanced digital control techniques to address security, resilience and robustness in complex networks and deliver fundamental advances in the technology for secure and reliable networks. The project will advance the theory on consensus of networked multi-agent systems to facilitate the fast adoption of the internet of things and the continuous growth of cyber-physical systems These systems in many cases work with high efficiency, stability, and low communication overheads. However, there are cases where disturbance amplification and cascading failures can arise from relatively small unforeseen events. The theoretical work will be complemented by detailed nonlinear networked simulations, using intelligent vehicle systems as a case study.Read moreRead less
The Role of Information in Game-Theoretic Decisions on Distributed Systems. Game theory is an important instrument for analysis and design of resource allocation algorithms on distributed systems. In many real-world problems, information available to agents is incomplete in contrast to the perfect information assumption often made. This project will investigate game-theoretic decisions and quantify information analytically using concepts from information theory. A better understanding and quanti ....The Role of Information in Game-Theoretic Decisions on Distributed Systems. Game theory is an important instrument for analysis and design of resource allocation algorithms on distributed systems. In many real-world problems, information available to agents is incomplete in contrast to the perfect information assumption often made. This project will investigate game-theoretic decisions and quantify information analytically using concepts from information theory. A better understanding and quantitative modelling of information will lead to distributed systems that are optimal and robust with respect to communication constraints. Project outcomes will be applicable to electrical power grids, renewable energy generation and storage, water irrigation networks, and communication systems.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE210101623
Funder
Australian Research Council
Funding Amount
$456,450.00
Summary
High-Fidelity Motion Simulator using Sickness-Free Motion Cueing Algorithm. This project aims to address the key deficiencies of driving and flight simulators by developing novel human perception-based motion cueing algorithms (MCAs) and leveraging advanced artificial intelligence techniques. Despite widespread applications, existing motion simulators fail to deliver the most accurate human sensation to the user. This failure is mainly attributable to the inefficiency and inflexibility of MCAs u ....High-Fidelity Motion Simulator using Sickness-Free Motion Cueing Algorithm. This project aims to address the key deficiencies of driving and flight simulators by developing novel human perception-based motion cueing algorithms (MCAs) and leveraging advanced artificial intelligence techniques. Despite widespread applications, existing motion simulators fail to deliver the most accurate human sensation to the user. This failure is mainly attributable to the inefficiency and inflexibility of MCAs used by simulators. It is expected that this project will significantly increase simulator motion fidelity and eliminate motion sickness. This will have substantial benefits to Australian research communities and industries, particularly where simulators are used for training, performance evaluation and virtual prototyping.Read moreRead less
DC optimisation based synthesis of systems in control, signal processing and wireless communication network. The conceptual advances with new optimisation based solvers to be developed in the area of control, signal processing and wireless communication. Major benefits of this project will be its direct applications to renewable technologies in automobile, health care, digital and communication network industries.
Linkage Infrastructure, Equipment And Facilities - Grant ID: LE120100215
Funder
Australian Research Council
Funding Amount
$300,000.00
Summary
Facility for characterisation of engineered microelectromechanical systems. This facility will provide Australian microelectromechanical (MEMS) researchers with a vital, world-class, capacity for characterisation of micro-machined devices and transducers, enabling them to compete internationally in this emerging field.
Feedback entropy in dynamical systems. This project aims to use the fundamental concept of entropy to help evaluate the decision-making effort in a variety of feedback control systems in science and engineering. This understanding will help develop smarter technologies and algorithms in areas such as manufacturing, vehicular technology and automated irrigation.
Nonstochastic information flows in networked dynamical systems. Feedback control is a crucial element of manufacturing, vehicular and energy systems, and is needed to guarantee hard performance bounds in safety- and mission-critical environments. When these control systems are implemented over communication networks, the amount of information flowing through them becomes a critical determinant of performance. However, the nonprobabilistic control objectives make standard information theory inapp ....Nonstochastic information flows in networked dynamical systems. Feedback control is a crucial element of manufacturing, vehicular and energy systems, and is needed to guarantee hard performance bounds in safety- and mission-critical environments. When these control systems are implemented over communication networks, the amount of information flowing through them becomes a critical determinant of performance. However, the nonprobabilistic control objectives make standard information theory inapplicable. This project aims to develop a novel, nonstochastic theory of information in order to analyse and design networked dynamical systems that obey worst-case performance limits. This will yield robust, probability-free algorithms for distributed control, filtering and causality inference.Read moreRead less