Abstract
This article proposes a framework to design a robust controller for a class of nonlinear networked control systems using aperiodic feedback information. Here, the nonlinearity and parameter variations of system model are considered as sources of uncertainty. To tackle the uncertainty in system dynamics, a linear robust control law is derived by applying the optimal control theory. Two different architectures of closed-loop systems are considered. In the first one, system and controller are not collocated; instead they are interconnected by means of a shared communication network. In the second architecture, system, controller and actuator are all collocated with their respective outputs available at all time-instead, sensors and controller are connected through a shared communication channel. In both architectures, the feedback loop is closed through the network. Owing to its shared nature, the network may suffer from bandwidth limitations. To save the network bandwidth, state and input information are transmitted aperiodically within the feedback loop. With this aim, the paper adopts an event-triggered control technique so as to reduce the transmission overhead. Applying Input-to-State Stability theory, we derive two different event-triggered robust control laws that stabilize the uncertain nonlinear system. Finally, we show that the designed event-triggered controllers satisfy the trade-off between control performance and saving in network bandwidth in the presence of uncertainty. The developed control algorithm is implemented and validated through numerical simulations.
Highlights
G ENERALLY, in Cyber-Physical Systems (CPSs) or Networked Control Systems (NCSs) each physical component shares its own local information with other subsystems through a communication network
Inspired by the results proposed in [26], [46], we consider both communication cost and system uncertainty, and propose an optimal control framework jointly optimizing both costs—communication cost and the cost associated with system uncertainty
In this paper, we consider a class of nonlinear systems afflicted with matched and mismatched uncertainty
Summary
G ENERALLY , in Cyber-Physical Systems (CPSs) or Networked Control Systems (NCSs) each physical component shares its own local information with other subsystems through a communication network. Tripathy et al.: Robust Stabilization of a Class of Nonlinear Systems via Aperiodic Sensing and Actuation and reported in [3], [45] In this self-triggered control approach, the subsequent time instant for event occurrence is determined using the system’s state or output information at the previous sampling instant. Yang & He [49] adopted an actor-critic based neural-network technique to address the robust stabilization problem of event-triggered nonlinear systems with input constraint To design such a robust controller, they have solved an infinite-time nonlinear optimal control problem. Ghodrat & Marquez [10] have applied the ISS theory to derive the event-triggering rule for a class of input-affine nonlinear systems under network constraints They showed that the proposed controller ensures stability in the presence of actuator errors and external disturbances. Some of the proofs and steps to realize the proposed control laws are included in Appendix
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