Title
Neural-network-based output-feedback control with stochastic communication protocols
Abstract
This paper is concerned with the neural-network-based (NN-based) output-feedback control issue for a class of nonlinear systems. For the purpose of effectively mitigating the phenomena of data congestion/collision, the stochastic communication protocols are favorably utilized to orchestrate the data transmissions, and the resultant closed-loop plant is represented by a so-called protocol-induced Markovian jump system with uncertain transition probability matrices. Taking such an uncertainty probability into account, a novel iterative adaptive dynamic programming (ADP) algorithm is developed to obtain the desired suboptimal solution with the help of auxiliary quasi-HJB equation, and the algorithm convergence is also investigated via the intensive use of the mathematical analysis. In this ADP framework, an NN-based observer with a novel adaptive tuning law is first adopted to reconstruct the system states. Then, based on the reconfigurable system, an actor–critic NN scheme with online learning is developed to realize the considered control strategy. Furthermore, in light of the Lyapunov theory, some sufficient conditions are derived to guarantee the stability of the zero equilibrium point of the closed-loop system as well as the boundedness of the estimation errors for critic and actor NN weights. Finally, a simulation example is employed to demonstrate the effectiveness of the developed suboptimal control scheme.
Year
DOI
Venue
2019
10.1016/j.automatica.2019.04.025
Automatica
Keywords
Field
DocType
Output-feedback control,Stochastic communication protocols,Adaptive dynamic programming,Actor–critic structures
Dynamic programming,Lyapunov function,Mathematical optimization,Nonlinear system,Control theory,Matrix (mathematics),Equilibrium point,Observer (quantum physics),Artificial neural network,Mathematics,Communications protocol
Journal
Volume
Issue
ISSN
106
1
0005-1098
Citations 
PageRank 
References 
5
0.40
0
Authors
3
Name
Order
Citations
PageRank
Derui Ding1122746.37
Zidong Wang211003578.11
Qing-Long Han36396315.39