Journal ArticleDOI
Stabilization of Uncertain Discrete-Time Linear System With Limited Communication
TLDR
It is shown that the robust control law with aperiodic information ensures input-to-state stability of the original system in the presence of mismatched uncertainty, and derived the event-triggering condition for a discrete-time uncertain system.Abstract:
This technical note proposes a procedure to control an uncertain discrete-time networked system using an aperiodic stabilizing input information. The system is primarily affected by the time-varying, norm bounded, mismatched parametric uncertainty. Aperiodic exchange of information is done due to bandwidth constraint of the communication network. An event-triggered based robust control strategy is adopted to reduce the effects of system uncertainty in such bandwidth constrained networks. In event-triggered control, the control input is computed and actuated at the system end only when a pre-specified event condition is violated. The robust control input is derived to stabilize the uncertain system by solving an optimal control problem based on a virtual nominal dynamics and a modified cost-functional. It is shown that the robust control law with aperiodic information ensures input-to-state stability (ISS) of the original system in the presence of mismatched uncertainty. Deriving the event-triggering condition for a discrete-time uncertain system and ensuring the stability of such system analytically are the key contributions of this technical note. A numerical example is given to prove the efficacy of the proposed event-based control algorithm over the conventional periodic one.read more
Citations
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Journal ArticleDOI
Stability and stabilization for a class of complex production processes via LMIs
Journal ArticleDOI
Global convergence of the EM algorithm for ARX models with uncertain communication channels
TL;DR: An expectation maximization algorithm is presented for ARX modeling with uncertain communication channels and the Kullback–Leibler divergence and the submartingale are used to prove that the parameter estimates can converge to the true values with the EM algorithm.
Proceedings ArticleDOI
Off-policy reinforcement learning for robust control of discrete-time uncertain linear systems
TL;DR: In this paper, an off-policy RL method is developed for the robust stabilizing controller design of discrete-time uncertain linear systems, which does not require any knowledge of the system knowledge and efficiently utilizes the data collected from on-line to improve the performance of approximate optimal control policy.
Journal ArticleDOI
Robust stabilization of a class of nonlinear systems via aperiodic sensing and actuation
TL;DR: Two different event-triggered robust control laws are derived that stabilize the uncertain nonlinear system and satisfy the trade-off between control performance and saving in network bandwidth in the presence of uncertainty.
Journal ArticleDOI
Adaptive Finite-Time Fault-Tolerant Control of Uncertain Systems With Input Saturation
TL;DR: In this article , an adaptive finite-time fault-tolerant control (FTC) strategy is proposed for state tracking of uncertain systems subject to actuator faults and input saturation.
References
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Book
Matrix Analysis
Roger A. Horn,Charles R. Johnson +1 more
TL;DR: In this article, the authors present results of both classic and recent matrix analyses using canonical forms as a unifying theme, and demonstrate their importance in a variety of applications, such as linear algebra and matrix theory.
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Event-Triggered Real-Time Scheduling of Stabilizing Control Tasks
TL;DR: This note investigates a simple event-triggered scheduler based on the paradigm that a real-time scheduler could be regarded as a feedback controller that decides which task is executed at any given instant and shows how it leads to guaranteed performance thus relaxing the more traditional periodic execution requirements.
Journal ArticleDOI
Stability of networked control systems
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Optimal Sampled-Data Control Systems
Tongwen Chen,Bruce A. Francis +1 more
TL;DR: This paper proposes a direct attack in the continuous-time domain, where sampled-data systems are time-varying.
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