The last decade has witnessed an increased interest in physical systems controlled over wireless networks (networked control systems). These systems allow the computation of control signals via processors that are not attached to the physical systems, and the feedback loops are closed over wireless networks. The contribution of this paper is to design and analyze event-triggered decentralized and distributed adaptive control architectures for uncertain networked large-scale modular systems; that is, systems consist of physically-interconnected modules controlled over wireless networks. Specifically, the proposed adaptive architectures guarantee overall system stability while reducing wireless network utilization and achieving a given system performance in the presence of system uncertainties that can result from modeling and degraded modes of operation of the modules and their interconnections between each other. In addition to the theoretical findings including rigorous system stability and the boundedness analysis of the closed-loop dynamical system, as well as the characterization of the effect of user-defined event-triggering thresholds and the design parameters of the proposed adaptive architectures on the overall system performance, an illustrative numerical example is further provided to demonstrate the efficacy of the proposed decentralized and distributed control approaches.
In this paper, we present a new adaptive control methodology that allows a desirable command performance while the proposed controller exchanges data with the physical system through a real-time network. Specifically, we utilize tools and methods from event-triggering control theory to schedule data exchange dependent upon errors exceeding user-defined thresholds and show the boundedness of the overall closed-loop system using Lyapunov stability. An illustrative numerical example is provided to demonstrate the efficacy of the proposed adaptive control approach.
In this paper, we study the design and analysis of adaptive control systems over wireless networks using event-triggering control theory. The proposed event-triggered adaptive control methodology schedules the data exchange dependent upon errors exceeding userdefined thresholds to reduce wireless network utilization and guarantees system stability and command following performance in the presence of system uncertainties. Specifically, we analyze stability and boundedness of the overall closed-loop dynamical system, characterize the effect of user-defined thresholds and adaptive controller design parameters to the system performance, and discuss conditions to make the resulting command following performance error sufficiently small. An illustrative numerical example is provided to demonstrate the efficacy of the proposed approach.
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