Gold Coast 17 - 20 December 2017
Gold Coast Convention and Exhibition Centre
ASCC 2017 Workshops
Sunday, 17 December
Advances in distributed control and formation control systems
Workshop duration: Full day (10:00 – 17:00)
Workshop venue: Room 1, Level 1.
- Brian D. O. Anderson, Research School of Engineering, Australian National University, Australia
- Hyo-Sung Ahn, School of Mechanical Engineering, Gwangju Institute of Science and Technology, South Korea
- Shaoshuai Mou, College of Engineering, Purdue University, USA
- Daniel Zelazo, Faculty of Aerospace Engineering, Israel Institute of Technology, Israel
- Minh Hoang Trinh, School of Mechanical Engineering, Gwangju Institute of Science and Technology, South Korea
- Zhiyong Sun, Research School of Engineering, Australian National University, Australia
- Hector Garcia de Marina, Ecole Nationale de l'Aviation Civile (ENAC), Toulouse, France
- Zhiyun Lin, Hangzhou Dianzi University, Hangzhou, China
In recent years cooperative coordination control and distributed control systems have gained considerable attention in the control community. This has been motivated by various applications such as formation control, unmanned air vehicles, coordination in complex networks, sensor networks, distributed optimization, etc. The central themes in the study of cooperative control for networked multi-agent systems include the understanding of the role of cooperation, the mechanism of information sharing between distributed agents, the stability and achievement of a global task arising from local interactions, coordination and cooperation with measurement constraints, and the robustness against measurement/communication perturbations, among others.
Formation control, which is one of the most actively studied topics within the realm of distributed cooperative control, generally aims to drive multiple agents to achieve prescribed constraints on their states. Roughly speaking, formation control aims to design distributed controllers such that a group of spatially distributed agents could reach some pre-defined formations involving geometric relationships between them. Such geometric relationships can be described by relative positions, bearings, distances, or a mix of different geometric variables, depending on the context and control requirements.
In the recent decade there has been much advancement in formation control systems, including different techniques in formation control, bearing rigidity theory and its application in formation systems and network localization, stability and convergence of formation systems, robustness properties with practical considerations. However, there are still several unsolved problems, such as a complete understanding of formation systems involving nonlinear control laws, or the fundamental limitations or trade-offs between local controllers and a global formation task.
This workshop aims to bring together active researchers in this field to showcase their latest achievements of techniques, designs and applications, as well as new directions of formation control and distributed cooperative control arising in various engineering systems.
Challenges and Opportunities in Smart Grid
Workshop duration: 1 hour (11:00 – 12:00)
Workshop venue: Room 2, Level 1.
- Wei-Yu Chiu, Department of Electrical Engineering, National Tsing Hua University, Taiwan
There are several challenges for the current electricity grid: growing electricity demand, an aging grid infrastructure, ever-increasing penetration of renewables, and significant uptake of electric vehicles and energy storage with behind-the-meter applications for residential and commercial buildings. To address these challenges, there are a number of state-of-the-art technologies being developed. Among them, control methods seem to be most suitable for capturing the dynamical behaviors of underlying power grids, leading to plenty of research opportunities for researchers in the field of control engineering. In this talk, we will cover several interesting topics, including smart metering, smart grid privacy and security (related to state estimation), demand-side management (related to model predictive control), demand response, distributed and autonomous control of microgrids, smart electricity pricing (related to H∞control), electric vehicle management, and mobile computing for energy management systems. Finally, on-going research projects, possible research positions, and conferences and journals pertaining to the smart grid will be discussed.
Stabilization of Infinite Dimensional Systems
Workshop duration: 2 hours (13:00 – 15:00)
Workshop venue: Room 3, Level 1.
- Marius Tucsnak, Universite de Bordeaux, Institut de Mathematiques de Bordeaux (IMB), France
- Miroslav Krstic, Department of Mechanical & Aero. Eng. University of California, San Diego, La Jolla, CA 92093-0411, USA
- Ying Tan, Department of Electrical and Electronic Engineering, Melbourne School of Engineering, University of Melbourne, Australia
This workshop aims to be an introduction to stabilization theory for infinite dimensional dynamical systems, with emphasis on the linear time invariant case. This is a field of growing interest for new applications, namely to mechanical or aerospace engineering, medicine or ecology. New mathematical and computational tools developed within the last decade make now possible the development of efficient methods for the control and identification of highly complex systems, generally described by evolution partial differential equations. The tutorial is structured in 3 presentations:
1) Stability and stabilizability concepts for linear infinite dimensional dynamical systems (Marius Tucsnak).
This lecture begins by describing in an introductory manner various concepts of stability of infinite dimensional systems with emphasis that, unlike in classical infinite dimensional linear systems, a variety of non equivalent stability types can be encountered in relatively simple PDEs systems. The
second part of this presentation is devoted to some by now classical tools to establish stability properties, namely in the frequency domain. Finally, a particular attention will be devoted to examples described by hyperbolic PDEs, where stabilization is achieved using collocated actuators and sensors.
2) Backstepping methods (Miroslav Krstic).
The use of linear Volterra operators in constructing backstepping transformations and feedback laws for stabilization of PDE systems by boundary control will be reviewed. Basic PDEs of both parabolic and hyperbolic types will be covered. With time permitting, an example of backstepping in observer design with boundary sensing will be covered.
3) From finite to infinite dimensional systems: approximation and interconnection issues (Ying Tan).
In practical problems the control laws of infinite dimensional systems are computed using projections on finite dimensional systems. Moreover, some applications are naturally described by couplings of infinite dimensional systems with finite dimensional ones. This presentation to describe the interconnections of these systems and the properties of the control laws computed on projected systems when inserted in the original infinite dimensional ones.
Model Free Adaptive Control (MFAC): Progress and Applications
Workshop duration: 4 hours (10:00 – 15:00)
Workshop venue: Room 4, Level 1.
- Ronghu Chi, Qingdao University of Science and Technology
- Yuanming Zhu, East China University of Science and Technology
- Xuhui Bu, Henan Polytechnic University
- Zhongsheng Hou, Beijing Jiaotong University
With the development of information sciences and technologies, practical processes, such as chemical industry, metallurgy, machinery, electronics, transportation, and logistics, pose enormous research and technical challenges for control engineering and management due to their size, distributed and multi-domain nature, safety and quality requirements, complex dynamics and performance evaluation, maintenance and diagnosis. Modeling these processes accurately using first principles or identification is almost impossible although these plants produce and store huge amount of impersonal valuable data on the plant and equipment operations in every moment during production. This challenges the existing control theory and technology, and meanwhile urgently pushes scientists and engineers to develop new data driven control and methodology to solve control and optimization issues for these complex practical plants. The high-tech hard/software and the cloud computing enable us to have ability to perform a complex computation real time, which makes the implementation of data driven control and methodology in practice possible. Thus, it would be very significant if we can learn the systems’ behaviors and discover the correlation relationship of system variables by making full use of those on-line and off-line process data, and then design a controller directly, predict system states, perform real-time optimization, and realize system control. For this reason, the establishment and development of data-driven control theory and methodology are urgent in both the theory and applications.
This Tutorial consists of four parts:
Part 1. The Dynamic Linearization Technique (DLT) and MFAC for discrete-time nonlinear systems.
This part will introduce the concept of pseudo-partial derivative, generalized Lipschitz condition. Particular effort will be put on (1) different forms of the dynamic linearizations; (2) differences between the DLT with other existing linearizations; (3) MFAC system design and stability analysis; (4) simulations and applications.
Part 2. Controller dynamic linearization based MFAC .
This part will introduce (1) DLT on the ideal controller; (2) controller-DLT based MFAC; (3) MFAC system design and stability analysis; (4) simulations and applications.
Part 3. Dynamic linearization based MFAC for repetitive systems:
This part will investigate (1) The DLT for the repeatable operation systems. A particular interest will be focused on the data driven iterative learning control (ILC) system design; (2) data driven optimal iterative learning system design, including point-to-point ILC and terminal ILC; (3) stability analysis; (4) simulations and applications.
Part 4. MFAC for complex connected systems, modulized designing with the model based control methods. This part will present the MFAC methods for the complex connected systems, and the modulized designing with the model based control methods, and further research topics.
- Regular Papers (drafts)
- 28 July 17 (Final)
- Invited Session Proposals
- 24 July 17 (Final)
- Workshop Proposals
- 28 July 17 (Final)
- Author notifications
- 22 September 17
- Early registration deadline
- 03 October 17
- Final Papers
- 04 October 17
- Workshops & Tutorials
- 17 December 17
- 17 - 20 December 17