Guaranteed Cost Finite-Time Control of Uncertain Coupled Neural Networks

Output information-based intermittent optimal control for continuous-time nonlinear systems with unmatched uncertainties via adaptive dynamic programming

Intermittent control stands as a valuable strategy for resource conservation and cost reduction across diverse systems. Nonetheless, prevailing research is intractable to address the challenges posed by robust optimal intermittent control of nonlinear input-affine systems with unmatched uncertainties. This paper aims to fill this gap. Initially, we introduce an enhanced finite-time intermittent control approach to ensure stability within nonlinear dynamic systems harboring bounded errors. A neural networks (NNs) state observer is constructed to estimate system information. Subsequently, an optimal intermittent controller that operates within a finite time span, guaranteeing system stability by employing the Hamilton-Jacobi-Bellman (HJB) methodology. Furthermore, we devise an output information-based event-triggered intermittent (ETI) approach rooted in the robust adaptive dynamic programming (ADP) algorithm, furnishing an optimal intermittent control law. In this process, a critic NNs is introduced to estimate the cost function and optimal intermittent controller. Simulation results show that our proposed method is superior to existing intermittent control strategies.

Optimal guaranteed cost intermittent control to the efficient movement of freight trains

Freight train system is under constant pressure to optimize operational efficiency, a factor that has led the sector to spearhead many new technologies. To address this, the optimal guaranteed cost intermittent cruise control of freight train system with time-varying uncertain parameters is investigated. In particular, the guaranteed cost intermittent control approach is proposed, which can achieve both advantages of guaranteed cost control and intermittent control methods. In addition, the acceptable conditions for the guaranteed cost control laws are weakened to insure that the proposed strategy is suitable for the application in freight train systems. Moreover, to promote the optimal control design in the freight train system, the proposed optimal guaranteed cost intermittent control for the nonlinear system subjected to norm bounded parametric uncertainties is addressed. The results of numerical experiments are presented to ascertain the effectiveness of the proposed freight train control methodology and to compare it to prior methods.