17 research outputs found
Detectability of distributed consensus-based observer networks: An elementary analysis and extensions
This paper continues the study of local detectability and observability
requirements on components of distributed observers networks to ensure
detectability properties of the network. First, we present a sketch of an
elementary proof of the known result equating the multiplicity of the zero
eigenvalue of the Laplace matrix of a digraph to the number of its maximal
reachable subgraphs. Unlike the existing algebraic proof, we use a direct
analysis of the graph topology. This result is then used in the second part of
the paper to extend our previous results which connect the detectability of an
observer network with corresponding local detectability and observability
properties of its node observers. The proposed extension allows for
nonidentical matrices to be used in the interconnections.Comment: Accepted for presentation at the 2014 Australian Control Conference,
Canberra Australia, Nov 201
Event-based H∞ consensus control of multi-agent systems with relative output feedback: The finite-horizon case
In this technical note, the H∞ consensus control problem is investigated over a finite horizon for general discrete time-varying multi-agent systems subject to energy-bounded external disturbances. A decentralized estimation-based output feedback control protocol is put forward via the relative output measurements. A novel event-based mechanism is proposed for each intelligent agent to utilize the available information in order to decide when to broadcast messages and update control input. The aim of the problem addressed is to co-design the time-varying controller and estimator parameters such that the controlled multi-agent systems achieve consensus with a disturbance attenuation level γ over a finite horizon [0,T]. A constrained recursive Riccati difference equation approach is developed to derive the sufficient conditions under which the H∞ consensus performance is guaranteed in the framework of event-based scheme. Furthermore, the desired controller and estimator parameters can be iteratively computed by resorting to the Moore-Penrose pseudo inverse. Finally, the effectiveness of the developed event-based H∞ consensus control strategy is demonstrated in the numerical simulation
Detection and Mitigation of Biasing Attacks on Distributed Estimation Networks
The paper considers a problem of detecting and mitigating biasing attacks on
networks of state observers targeting cooperative state estimation algorithms.
The problem is cast within the recently developed framework of distributed
estimation utilizing the vector dissipativity approach. The paper shows that a
network of distributed observers can be endowed with an additional attack
detection layer capable of detecting biasing attacks and correcting their
effect on estimates produced by the network. An example is provided to
illustrate the performance of the proposed distributed attack detector.Comment: Accepted for publication in Automatic
Fixed-Time Convergent Distributed Observer Design of Linear Systems: A Kernel-Based Approach
The robust distributed state estimation for a class
of continuous-time linear time-invariant systems is achieved by a
novel kernel-based distributed observer, which, for the first time,
ensures fixed-time convergence properties. The communication
network between the agents is prescribed by a directed graph
in which each node involves a fixed-time convergent estimator.
The local observer estimates and broadcasts the observable states
among neighbours so that the full state vector can be recovered
at each node and the estimation error reaches zero after a predefined fixed time in the absence of perturbation. This represents a
new distributed estimation framework that enables faster convergence speed and further reduced information exchange compared
to a conventional Luenberger-like approach. The ubiquitous timevarying communication delay across the network is suitably
compensated by a prediction scheme. Moreover, the robustness
of the algorithm in the presence of bounded measurement
and process noise is characterised. Numerical simulations and
comparisons demonstrate the effectiveness of the observer and
its advantages over the existing methods
Distributed Estimation and Control for LTI Systems under Finite-Time Agreement
This paper considers a strongly connected network of agents, each capable of
partially observing and controlling a discrete-time linear time-invariant (LTI)
system that is jointly observable and controllable. Additionally, agents
collaborate to achieve a shared estimated state, computed as the average of
their local state estimates. Recent studies suggest that increasing the number
of average consensus steps between state estimation updates allows agents to
choose from a wider range of state feedback controllers, thereby potentially
enhancing control performance. However, such approaches require that agents
know the input matrices of all other nodes, and the selection of control gains
is, in general, centralized. Motivated by the limitations of such approaches,
we propose a new technique where: (i) estimation and control gain design is
fully distributed and finite-time, and (ii) agent coordination involves a
finite-time exact average consensus algorithm, allowing arbitrary selection of
estimation convergence rate despite the estimator's distributed nature. We
verify our methodology's effectiveness using illustrative numerical
simulations