2,470 research outputs found
Event-based State Estimation: An Emulation-based Approach
An event-based state estimation approach for reducing communication in a
networked control system is proposed. Multiple distributed sensor agents
observe a dynamic process and sporadically transmit their measurements to
estimator agents over a shared bus network. Local event-triggering protocols
ensure that data is transmitted only when necessary to meet a desired
estimation accuracy. The event-based design is shown to emulate the performance
of a centralised state observer design up to guaranteed bounds, but with
reduced communication. The stability results for state estimation are extended
to the distributed control system that results when the local estimates are
used for feedback control. Results from numerical simulations and hardware
experiments illustrate the effectiveness of the proposed approach in reducing
network communication.Comment: 21 pages, 8 figures, this article is based on the technical report
arXiv:1511.05223 and is accepted for publication in IET Control Theory &
Application
Distributed Event-Based State Estimation for Networked Systems: An LMI-Approach
In this work, a dynamic system is controlled by multiple sensor-actuator
agents, each of them commanding and observing parts of the system's input and
output. The different agents sporadically exchange data with each other via a
common bus network according to local event-triggering protocols. From these
data, each agent estimates the complete dynamic state of the system and uses
its estimate for feedback control. We propose a synthesis procedure for
designing the agents' state estimators and the event triggering thresholds. The
resulting distributed and event-based control system is guaranteed to be stable
and to satisfy a predefined estimation performance criterion. The approach is
applied to the control of a vehicle platoon, where the method's trade-off
between performance and communication, and the scalability in the number of
agents is demonstrated.Comment: This is an extended version of an article to appear in the IEEE
Transactions on Automatic Control (additional parts in the Appendix
Decentralized event-triggered control over wireless sensor/actuator networks
In recent years we have witnessed a move of the major industrial automation
providers into the wireless domain. While most of these companies already offer
wireless products for measurement and monitoring purposes, the ultimate goal is
to be able to close feedback loops over wireless networks interconnecting
sensors, computation devices, and actuators. In this paper we present a
decentralized event-triggered implementation, over sensor/actuator networks, of
centralized nonlinear controllers. Event-triggered control has been recently
proposed as an alternative to the more traditional periodic execution of
control tasks. In a typical event-triggered implementation, the control signals
are kept constant until the violation of a condition on the state of the plant
triggers the re-computation of the control signals. The possibility of reducing
the number of re-computations, and thus of transmissions, while guaranteeing
desired levels of performance makes event-triggered control very appealing in
the context of sensor/actuator networks. In these systems the communication
network is a shared resource and event-triggered implementations of control
laws offer a flexible way to reduce network utilization. Moreover reducing the
number of times that a feedback control law is executed implies a reduction in
transmissions and thus a reduction in energy expenditures of battery powered
wireless sensor nodes.Comment: 13 pages, 3 figures, journal submissio
On general systems with network-enhanced complexities
In recent years, the study of networked control systems (NCSs) has gradually become an active research area due to the advantages of using networked media in many aspects such as the ease of maintenance and installation, the large flexibility and the low cost. It is well known that the devices in networks are mutually connected via communication cables that are of limited capacity. Therefore, some network-induced phenomena have inevitably emerged in the areas of signal processing and control engineering. These phenomena include, but are not limited to, network-induced communication delays, missing data, signal quantization, saturations, and channel fading. It is of great importance to understand how these phenomena influence the closed-loop stability and performance properties
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
Robustness of Nonlinear Control Systems to Network-Induced Imperfections
Nowadays control systems are increasingly implemented over shared resource-constrained communication networks. Namely, sensors, controllers and actuators no longer exchange information through dedicated point-to-point connections but compete for network access, which gives rise to network-induced imperfections that adversely affect control performance. Prevalent network phenomena are scheduling protocols, nonuniform variable delays, quantization, packet dropouts, sampled and distorted data. Besides possessing usual robustness requirements (e.g., to modeling uncertainties or external disturbances), such control systems ought to be robust against the aforementioned network phenomena as well. This article brings a methodology to quantify control system robustness via Lp-gains as the control laws, communication delays, sampling intervals, noise levels or scheduling protocols change. Building upon impulsive delayed system modeling, Lyapunov stability and the small-gain theorem, the proposed methodology takes into account nonlinear time-varying dynamic controllers and plants as well as model-based estimation, output feedback and large delays. The inverted pendulum example is provided
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