Decentralised static output feedback stabilisation and synchronisation of networks

Dynamic multi-agent networks are important in a wide range of areas in science and engineering, including mobile sensor networks, distributed robotics such as underwater vehicles and cooperative unmanned air vehicles, biological synchronisation, networked economics and social networks. The paper makes a fundamental theoretical contribution to the field by blending methods from graph theory and control theory. [Impact Factor: 2.631, second highest of all Control Engineering journals]This is the author's pre-print. The definitive published version is available via doi:10.1016/j.automatica.2009.09.029In this paper global stabilisation of a complex network is attained by applying local decentralised output feedback control to a minimum number of nodes of the network. The stabilisation of the network is treated as a rank constrained problem. Strict positive realness conditions on the node level dynamics allow nonlinearities/uncertainties which satisfy the sector conditions to be considered. A network of Chua oscillators with 75 nodes is considered to demonstrate the efficacy of the approach

Robust fault estimation using relative information in linear multi-agent networks

Journal ArticleIn this technical note, a robust fault estimation method, based on sliding mode observers, is proposed for a collection of agents undertaking a shared task and exchanging only relative information over a communication network. Since the 'system of systems' formed by the agents is not observable with respect to relative sensing information, by appropriate transformations and scalings of the inputs and outputs of the actual system, a meaningful observable subsystem is created. For this new subsystem, after modal decomposition based on the associated Laplacian, decoupled sliding mode observers, depending only on the individual node level dynamics of the network, can be created exploiting an existing design philosophy. These collectively form a centralized fault estimation scheme for the original system. © 1963-2012 IEEE

On distributed pinning observers for a network of dynamical systems

ArticleThis is the author accepted manuscript. The final version is available from IEEE via the DOI in this record.In this paper, a distributed observer structure is proposed to estimate the states of a large scale network of semi-linear systems interconnected by a positive, time varying coupling strength. The distributed observer comprises distinct sub-observers which require only local node level information and exchange their local state estimates with their ‘neighbouring’ observers. The key idea here is to use a minimum number, or at least relatively few, measurements from the network being monitored to reduce the sensor requirements. The problem is formulated as a two stage LMI optimization problem

Delayed static output feedback control of a network of double integrator agents

Journal ArticlePreprintThis paper considers a network of vehicles moving in a two dimensional plane. The overall network, described by a collection of double integrator dynamics, is controlled by a novel distributed static output feedback methodology to maintain a desired formation. The distributed control architecture stabilizes the network using static output feedback of position information only, by exploiting delays in communication of the relative information. An optimization algorithm, based on Linear Matrix Inequalities together with the DIRECT search algorithm, is used to synthesize the controller gains and the delay.© 2013 Elsevier Ltd. All rights reserved.UK India Education and Research Initiative (UKIERI

Fuzzy Distributed Cooperative Tracking For A Swarm Of Unmanned Aerial Vehicles With Heterogeneous Goals

Copyright © 2015 Taylor & Francis This is an Accepted Manuscript of an article published by Taylor & Francis in International Journal of Systems Science on 29 December 2015, available online: http://www.tandfonline.com/10.1080/00207721.2015.1126380This article proposes a systematic analysis for a tracking problem which ensures cooperation amongst a swarm of UAVs, modelled as nonlinear systems with linear and angular velocity constraints, in order to achieve different goals. A distributed Takagi-Sugeno (TS) framework design is adopted for the representation of the nonlinear model of the dynamics of the UAVs. The distributed control law which is introduced is composed of both node and network level information. Firstly feedback gains are synthesised using a Parallel Distributed Compensation (PDC) control law structure, for a collection of isolated UAVs; ignoring communications among the swarm. Then secondly, based on an alternation-like procedure, the resulting feedback gains are used to determine Lyapunov matrices which are utilised at network level to incorporate into the control law the relative differences in the states of the vehicles, and to induce cooperative behaviour. Eventually stability is guaranteed for the entire swarm. The control synthesis is performed using tools from linear control theory: in particular the design criteria are posed as Linear Matrix Inequalities (LMIs). An example based on a UAV tracking scenario is included to outline the efficacy of the approach.Engineering and Physical Sciences Research Council (EPSRC

Second order sliding mode observers for fault reconstruction in power networks

This is the author accepted manuscript. The final version is available from the publisher via the DOI in this record.This paper proposes a 2-sliding mode observer to detect and reconstruct a certain class of load altering faults in a power network. The observer design is based on the recently proposed multivariable super-twisting structure. The IEEE benchmark power networks used to test the scheme are modelled as a semi-explicit class of differential algebraic equations (DAEs). For the purpose of developing the detection scheme, only the phase angles of the generators are measured, which represent a subset of the differential states of the DAEs. The objective is to estimate the differential states (the phase angles and frequencies of the generators), the algebraic states (the phase angles of the load bus tensions) and to reconstruct a class of load altering faults affecting the network. The proposed observer is assessed in simulation on two IEEE benchmarks: the 9-bus and 14-bus networks, so as to verify its capability to correctly estimate the differential and algebraic states of the network in spite of its complexity and uncertainty. Moreover, the capability of the proposed scheme to detect the presence of a load altering fault, to exactly identify its position in the network, and to precisely reconstruct the shape of the fault itself is shown and discussed

Observer-based controller design with disturbance feedforward framework for formation control of satellites

Copyright © 2015 The Institution of Engineering and TechnologyIn this study, a bespoke sliding mode non-linear observer and a linear controller framework is proposed for achieving robust formation control of a cluster of satellites in the case of a circular reference orbit. Exploiting the structure of the satellite dynamics, a non-linear observer is proposed based on super-twist sliding mode ideas. The observer estimates the states and any unknown bounded disturbances in ‘finite time’. The stability properties of the observers are demonstrated using Lyapunov techniques. A distributed controller, based on the estimated states and the relative position output information, depending on the underlying communication topology, is proposed. A polytopic representation of the collective dynamics which depends on the eigenvalues of the Laplacian matrix associated with the communication topology is used to synthesise the gains of the proposed control laws. A simulation example is used to demonstrate the efficacy of the proposed approach

A solution for autonomous, adaptive monitoring of coastal ocean ecosystems: Integrating ocean robots and operational forecasts

This study presents a proof-of-concept for a fully automated and adaptive observing system for coastal ocean ecosystems. Such systems present a viable future observational framework for oceanography, reducing the cost and carbon footprint of marine research. An autonomous ocean robot (an ocean glider) was deployed for 11 weeks in the western English Channel and navigated by exchanging information with operational forecasting models. It aimed to track the onset and development of the spring phytoplankton bloom in 2021. A stochastic prediction model combined the real-time glider data with forecasts from an operational numerical model, which in turn assimilated the glider observations and other environmental data, to create high-resolution probabilistic predictions of phytoplankton and its chlorophyll signature. A series of waypoints were calculated at regular time intervals, to navigate the glider to where the phytoplankton bloom was most likely to be found. The glider successfully tracked the spring bloom at unprecedented temporal resolution, and the adaptive sampling strategy was shown to be feasible in an operational context. Assimilating the real-time glider data clearly improved operational biogeochemical forecasts when validated against independent observations at a nearby time series station, with a smaller impact at a more distant neighboring station. Remaining issues to be addressed were identified, for instance relating to quality control of near-real time data, accounting for differences between remote sensing and in situ observations, and extension to larger geographic domains. Based on these, recommendations are made for the development of future smart observing systems

On Connectivity Preservation in Mobile Wireless Multi-Agent/Node Mesh Networks

2013 American Control Conference (ACC), Washington, DC, USA, June 17-19, 2013The paper considers the development of a mission planning system for a so-called ‘non-cooperative’ multi-agent network. The network comprises two classes of agent: primary mission agents and relay agents. The primary mission agents have predefined tasks to execute and operate autonomously within the field of operation. Although these agents operate independently, from a mission planning perspective the base station is required to maintain contact. In order to ensure this, relay agents are employed under the direct command of the base station with the objective of maintaining connectivity. This paper proposes an architecture to control the relay agents in such a way that connectivity, as measured in terms of the Fiedler eigenvalue, is maximized subject to the cost of moving the relay agents. A model predictive control-like layer is used to generate a set of way-points to position the relay agents at specific places at specific instances of time to maximize connectivity. These way-points are then converted into continuous time paths for the relay agents to follow. A low level sliding mode controller implemented on each relay agent ensures that the proposed path is followed in a robust fashion