Learning event-triggered control from data through joint optimizationEvent-triggered controlReinforcement learningStability verificationNeural networksWe present a framework for model-free learning of event-triggered control strategies. Event-triggered methods aim to achieve high control performance while only ...
Under spatially point measurements (SPMs), this paper addresses event-triggered sampled-data (ETSD) fuzzy secure control for nonlinear space-varying parabolic partial differential equation (PDE) systems with stochastic actuator failures and deception attacks. Initially, a T-S fuzzy PDE model is present...
We study event-triggered control for stabilization of unstable linear plants over rate-limited communication channels subject to unknown, bounded delay. On one hand, the timing of event triggering carries implicit information about the state of the plant. On the other hand, the delay in the commun...
Guidance Subsystem Design for Path Following Control of Underactuated USV Control Subsystem Design for Path Following Control of Underactuated USV Simulation Results Conclusions Author Contributions Funding Institutional Review Board Statement Informed Consent Statement Data Availability Statement Conflicts of Interes...
Finally, numerical examples are presented to corroborate the merits of the proposed data‐driven event‐triggered control schemes relative to existing results. 展开 关键词: data‐driven control event‐trigger stability sampled‐da...
Eliminating the requirement of explicit models of MASs for consensus control, data-driven control directly learns control laws from data [24–29]. For example, data-driven distributed protocols for MAS synchronization were developed based on reinforcement learning techniques in [30, 31]. However, ...
FDIA and RA, which appear randomly on the data communication channel from sensor to controller, are modeled in a unified framework through Bernoulli process. The state-dependent event-triggered control scheme (ETCS), which reduce the demand for network bandwidth, is adopted to update control ...
However, conventional control methods such as finite control set model predictive control (FCS-MPC) suffer from a heavy computational burden and sensitivity to system parameter variations, limiting the performance of MMCs. This paper proposes a data-driven approach based on model-free adaptive control...
This paper presents a novel method for designing event-triggered dissipative observer-based control for discrete-time Takagi-Sugeno fuzzy singular systems, addressing admissibility, dissipativity, observer-based control, and event-triggered data challenges simultaneously. The distinctive strength of our method...
An atomic basic block (ABB) is a section of the control ?ow that has to be executed atomically in order to ensure the consistency of data, that is affected within this ABB. Most of these ABBs are identical to minimal basic blocks known from compiler construction, but an ABB can also ...