Finite‐time energy‐to‐peak quantized filtering for Markov jump networked systems under weighted try‐once‐discard protocol

Abstract

This work addresses the finite-time energy-to-peak filtering issue for networked systems subject to quantization effects and the weighted try-once-discard (WTOD) protocol, in which the random changes of coupling connections are governed by a Markov chain. To avoid the conflict in data transmission, the WTOD protocol is introduced to the communication between the sensor node and the filter, which guarantees that just one sensor node has access to send data at each transmission instant. In addition, the quantizer is employed to improve the reliability of data transmission. The objective of this article is to construct a filter such that the filtering error system satisfies the requirements of both the finite-time boundary and the specified energy-to-peak performance. Based on the Kronecker product, the Lyapunov stability theory and an improved matrix decoupling method, some sufficient conditions are established through disposing of convex optimization issues. Ultimately, the availability of the designed filter is illustrated via a numerical example. K E Y W O R D Senergy-to-peak filtering, finite-time boundary, Markov jump networked systems, weighted try-once-discard protocol

Dynamic output feedback model predictive control for asynchronous Markovian jump systems under try‐once‐discard protocol

“…To this aim, some data scheduling protocols have been willingly deployed in the shared communication network to orchestrate the data transmission so as to reduce the transmission burden and improve network utilization 33‐36 . Accordingly, three typical communication protocols can be found in the literature, namely, stochastic communication protocol, 37‐40 round‐robin protocol, 41‐43 and try‐once‐discard (TOD) protocol 44‐46 . Compared with the other two protocols, the TOD protocol is better at dynamical scheduling because it usually gives the highest priority to the node with significant necessity.…”

Asynchronous output feedback control for Markov jump systems under dynamic event‐triggered strategy

“…To better describe these systems, the Markov theory is introduced such that a class of dynamical systems named Markov jump systems (MJSs) is derived. Because of the remarkable modeling ability of stochastic switching processes, MJSs have been used in widespread fields, such as vehicles and crafts, power systems and networked control 1‐4 . As a significant role in the synthesis of MJSs, the control analysis has received much attention, such as sliding‐mode control, 5 model predictive control, 6 multiple frequency control, 7 dissipative control 8 and so on.…”

“…Because of the remarkable modeling ability of stochastic switching processes, MJSs have been used in widespread fields, such as vehicles and crafts, power systems and networked control. [1][2][3][4] As a significant role in the synthesis of MJSs, the control analysis has received much attention, such as sliding-mode control, 5 model predictive control, 6 multiple frequency control, 7 dissipative control 8 and so on. An obvious observation of the above literature is that all controllers are designed on the basis of the state feedback law.…”

Sliding mode control for multi‐agent systems under stochastic communication protocol

“…[17][18][19] However, real-time information transmission will exacerbate the stress of communication network with limited bandwidth, if the transmission network is granted to all nodes at the same time. A good way is to use the scheduling protocol to coordinate the signal transmission among system components, such as the round-robin (RR) protocol, [20][21][22][23][24] the weighted try-once-discard (WTOD) protocol, [25][26][27] and the stochastic communication protocol (SCP). 28,29 Under the SCP, only one sensor can obtain permission to the communication network and transmit its signal, and the signals from other sensors cannot get permission to the network at each instant, see the relevant works on fuzzy systems, 30 stochastic systems, 31,32 and so on.…”

“…However, real‐time information transmission will exacerbate the stress of communication network with limited bandwidth, if the transmission network is granted to all nodes at the same time. A good way is to use the scheduling protocol to coordinate the signal transmission among system components, such as the round‐robin (RR) protocol, 20‐24 the weighted try‐once‐discard (WTOD) protocol, 25‐27 and the stochastic communication protocol (SCP) 28,29 …”