Decentralized Control for Networked Control Systems With Asymmetric Information

Liang

Asian Journal of Control

et al. 2023

Self Cite

The decentralized linear–quadratic–Gaussian (LQG) control problem for networked control systems (NCSs) with asymmetric information is investigated, where controller 1 shares its historical information with controller 2, and not vice versa. The asymmetry of the information structure leads to the coupling between controller 2 and estimator 1, and hence the classical separation principle fails. Through the assumption of linear control strategy, the coupling between controller 2 and estimator 1 (CCE) is decoupled, but the estimation gain is still coupled with the control gain. It is noted that the control gain conforms to the backward Riccati equation while estimation gain abides by the forward equation, which is computationally challenging. Applying the stochastic maximum principle, the solvability of the decentralized LQG control problem is reduced to that of corresponding forward and backward stochastic difference equations (FBSDEs). Further, necessary and sufficient conditions for the solvability of optimal control problem are presented by two Riccati equations, one of which is nonsymmetric. Moreover, a novel iterative forward method is proposed to calculate the coupled backward control gain and forward estimation gain.

Section: Theorem 1 Problem 1 Has the Unique Solution If And Only Ifmentioning

confidence: 99%

“…Decentralized control has attracted many researchers' interest because of the above restrictions of centralized control; see [11][12][13][14]. Decentralized control may have several feedback loops and multiple controllers, which have access to different information and make decisions, respectively.…”

Section: Introductionmentioning

confidence: 99%

Decentralized linear–quadratic–Gaussian control of networked control systems with asymmetric information

Liang

Asian Journal of Control

et al. 2023

Self Cite

“…Actually, the packet loss systems can be viewed as one kind of multiplicative noise systems, and some results can be found in Reference 17 and the reference therein. It can be seen that the referred results in References 11‐17 are mainly concentrated on the scalar i.i.d. packet loss systems.…”

Section: Introductionmentioning

confidence: 99%

“…Surveys of optimal control and stabilization on NCSs with scalar i.i.d. packet losses can be found in References 11‐17. Based on the asynchronous dynamical systems approach and the average dwell‐time method, Zhang et al 11 proposed a sufficient conditions for the exponential stability of NCS with i.i.d.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Optimal control and stabilization for discrete‐time networked control systems with multichannel Markovian packet losses

Han

Zhang

Optim Control Appl Methods

et al. 2023

This article is concerned with the optimal control and stabilization for the discrete‐time networked control systems with Markovian fading channels in a diagonal form, which indicates that different channel possesses different correlated fading property. To overcome the essential difficulty resulting from the multi communication channel packet losses and the correlation of the Markov chain, a new multistate Markov chain is introduced, by which the optimal control and stabilization for the NCSs with the diagonal form of Markovian fading channels are transformed into the ones for the general Markovian jump linear system. According to the converted system, a new modified maximum principle is presented, that is, a forward‐backward stochastic difference equation (FBSDE) is obtained. In the finite horizon design, the key step is to seek for the relationship between the system state and optimal costate. By the obtained relation and based on a new coupled difference Riccati equation (CDRE), a necessary and sufficient solvability condition for the optimal control is obtained as well as an explicit expression for the optimal controller. For the infinite horizon case, a new type of coupled Lyapunov function is defined, which keeps consistent with the finite horizon optimal performance index. By introducing a new coupled algebraic Riccati equation and using the defined Lyapunov function, a necessary and sufficient stabilization condition in the mean‐square sense and an infinite horizon optimal controller are presented. Finally, a numerical example is supplied to illustrate the efficiency of the proposed results.

Team optimal decentralized estimation by multiple agents with asymmetric information

Sun

Optim Control Appl Methods

et al. 2023

In this paper, we are concerned with the team optimal decentralized state estimation problem where the state is transmitted to a remote agent with packet dropouts and is observed by local agents with additive noises. In particular, the information of the remote agent is available to all local agents with hierarchical relationships, which leads to an asymmetric information structure. The main contribution is to derive the analytical expressions for the team optimal decentralized state estimation. Different from the existing decentralized estimation results, the novelty of the paper is to comprehensively investigate the influence of packet dropouts and additive noises, which occur frequently in networked control systems.