72,064 research outputs found
Utility Driven Sampled Data Control Under Imperfect Information
Computer based control systems, which are ubiquitous today, are essentially sampled data control systems. In the traditional time-triggered control systems, the sampling period is conservatively chosen, based on a worst case analysis. However, in many control systems, such as those implemented on embedded computers or over a network, parsimonious sampling and computation is helpful. In this context, state/data based aperiodic utility driven sampled data control systems are a promising alternative. This dissertation is concerned with the design of utility driven event-triggers in certain classes of problems where the information available to the triggering mechanisms is imperfect. In the first part, the problem of utility driven event-triggering under partial state information is considered - specifically in the context of (i) decentralized sensing and (ii) dynamic output feedback control. In the case of full state feedback, albeit with decentralized sensing, methods are developed for designing local and asynchronous event-triggers for asymptotic stabilization of an equilibrium point of a general nonlinear system. In the special case of Linear Time Invariant (LTI) systems, the developed method also holds for dynamic output feedback control, which extends naturally to control over Sensor-Controller-Actuator Networks (SCAN), wherein even the controller is decentralized. The second direction that is pursued in this dissertation is that of parsimonious utility driven sampling not only in time but also in space. A methodology of co-designing an event-trigger and a quantizer of the sampled data controller is developed. Effectively, the proposed methodology provides a discrete-event controller for asymptotic stabilization of an equilibrium point of a general continuous-time nonlinear system. In the last part, a method is proposed for designing utility driven event-triggers for the problem of trajectory tracking in general nonlinear systems, where the source of imperfect information is the exogenous reference inputs. Then, specifically in the context of robotic manipulators we develop utility driven sampled data implementation of an adaptive controller for trajectory tracking, wherein imperfect knowledge of system parameters is an added complication
Event-triggered gain scheduling of reaction-diffusion PDEs
This paper deals with the problem of boundary stabilization of 1D
reaction-diffusion PDEs with a time- and space- varying reaction coefficient.
The boundary control design relies on the backstepping approach. The gains of
the boundary control are scheduled under two suitable event-triggered
mechanisms. More precisely, gains are computed/updated on events according to
two state-dependent event-triggering conditions: static-based and dynamic-based
conditions, under which, the Zeno behavior is avoided and well-posedness as
well as exponential stability of the closed-loop system are guaranteed.
Numerical simulations are presented to illustrate the results.Comment: 20 pages, 5 figures, submitted to SICO
Performance analysis with network-enhanced complexities: On fading measurements, event-triggered mechanisms, and cyber attacks
Copyright © 2014 Derui Ding et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Nowadays, the real-world systems are usually subject to various complexities such as parameter uncertainties, time-delays, and nonlinear disturbances. For networked systems, especially large-scale systems such as multiagent systems and systems over sensor networks, the complexities are inevitably enhanced in terms of their degrees or intensities because of the usage of the communication networks. Therefore, it would be interesting to (1) examine how this kind of network-enhanced complexities affects the control or filtering performance; and (2) develop some suitable approaches for controller/filter design problems. In this paper, we aim to survey some recent advances on the performance analysis and synthesis with three sorts of fashionable network-enhanced complexities, namely, fading measurements, event-triggered mechanisms, and attack behaviors of adversaries. First, these three kinds of complexities are introduced in detail according to their engineering backgrounds, dynamical characteristic, and modelling techniques. Then, the developments of the performance analysis and synthesis issues for various networked systems are systematically reviewed. Furthermore, some challenges are illustrated by using a thorough literature review and some possible future research directions are highlighted.This work was supported in part by the National Natural Science Foundation of China under Grants 61134009, 61329301, 61203139, 61374127, and 61374010, the Royal Society of the UK, and the Alexander von Humboldt Foundation of Germany
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