Guaranteed Cost Networked Control for T–S Fuzzy Systems With Time Delays

Zhang, Huaguang; Yang, Dedong; Chai, Tianyou

doi:10.1109/tsmcc.2006.886983

Cited by 198 publications

(110 citation statements)

References 21 publications

Supporting

Mentioning

109

Contrasting

Unclassified

Order By: Relevance

“…As such, the phenomenon of packet dropout in network transmission occurs when > . According to such a fact, a guaranteed cost networked control problem has been developed for T-S fuzzy systems with both network-induced delays and packet dropouts in network transmission [19]. Recently, in [58], the fault-tolerant control approach for linear controlled plant has been extended to the case of the nonlinear networked control systems in the presence of networked-induced delay and packet dropout as well as external disturbance.…”

Section: T-s Fuzzy Control and Filtering With Packet Dropoutsmentioning

confidence: 99%

“…In this framework, the problem of T-S fuzzy control and filtering has long been a fascinating focus of research attracting constant attention. It is not surprising that there has been a rich body of relevant literature published in the past two decades; see, for example, [10][11][12][13][14][15][16][17][18][19] for control problems and [20][21][22][23][24][25][26] for filtering issues.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Analysis, Filtering, and Control for Takagi-Sugeno Fuzzy Models in Networked Systems

Zhang

Wang

et al. 2015

Abstract and Applied Analysis

View full text Add to dashboard Cite

The fuzzy logic theory has been proven to be effective in dealing with various nonlinear systems and has a great success in industry applications. Among different kinds of models for fuzzy systems, the so-called Takagi-Sugeno (T-S) fuzzy model has been quite popular due to its convenient and simple dynamic structure as well as its capability of approximating any smooth nonlinear function to any specified accuracy within any compact set. In terms of such a model, the performance analysis and the design of controllers and filters play important roles in the research of fuzzy systems. In this paper, we aim to survey some recent advances on the T-S fuzzy control and filtering problems with various network-induced phenomena. The network-induced phenomena under consideration mainly include communication delays, packet dropouts, signal quantization, and randomly occurring uncertainties (ROUs). With such network-induced phenomena, the developments on T-S fuzzy control and filtering issues are reviewed in detail. In addition, some latest results on this topic are highlighted. In the end, conclusions are drawn and some possible future research directions are pointed out.

show abstract

Section: T-s Fuzzy Control and Filtering With Packet Dropoutsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Analysis, Filtering, and Control for Takagi-Sugeno Fuzzy Models in Networked Systems

Zhang

Wang

et al. 2015

Abstract and Applied Analysis

View full text Add to dashboard Cite

show abstract

“…In paper [32] a T-S fuzzy model is employed to represent the nonlinear controlled network environment that includes network-induced delay, packet losses and out-oforder packets in transmission. Similarly, Zhang et al in [33] presented a guaranteed cost networked control method for the T-S fuzzy system with constant bounded time-delay in consideration of both network-induced delay and packet losses.…”

Section: Related Workmentioning

confidence: 99%

On the application of fuzzy-based flow control approach to High Altitude Platform communications

2009

View full text Add to dashboard Cite

Most of the research effort in the field of HAP communications until now has been invested in the physical layer of the protocol stack, and in the radio related issues in particular. However, the overall system throughput is limited by the performance of the transport layer. Since HAPs will be used in networks with different topological complexity, various kinds of wireless communications links, bit error rates, and various mixtures of multimedia traffic, the control flow in such networks may present itself as a non-linear and stochastic process. Therefore we introduced a fuzzy control of the throughput in the TCP. Our approach is based on the off-line synthesis of the Takagi-Sugeno fuzzy controller based on the simulation data and on-line flow control by the synthesized controller that is built in the conventional TCP. In the paper we present the ns2-based simulation results.

show abstract

“…The results were derived by using a single Lyapunov function (SLF) method, which in general leas to a conservative result. Designing fuzzy controllers for a class of nonlinear networked control systems was considered in [26][27][28] by solving approximate uncertain linear networked Takagi-Sugeno (T-S) models with both       x network induced-delay and packet dropout. However, they do not quantize the signals.…”

Section: Introductionmentioning

confidence: 99%

H<sub>∞</sub> Control of Uncertain Fuzzy Networked Control Systems with State Quantization

Mahmoud

2012

ICA

View full text Add to dashboard Cite

The problem of robust control for uncertain discrete-time Takagi and Sugeno (T-S) fuzzy networked control systems (NCSs) is investigated in this paper subject to state quantization. By taking into consideration network induced delays and packet dropouts, an improved model of network-based control is developed. A less conservative delay-dependent stability condition for the closed NCSs is derived by employing a fuzzy Lyapunov-Krasovskii functional. Robust fuzzy controller is constructed that guarantee asymptotic stabilization of the NCSs and expressed in LMIbased conditions. A numerical example illustrates the effectiveness of the developed technique.

show abstract

Guaranteed Cost Networked Control for T–S Fuzzy Systems With Time Delays

Cited by 198 publications

References 21 publications

Analysis, Filtering, and Control for Takagi-Sugeno Fuzzy Models in Networked Systems

Analysis, Filtering, and Control for Takagi-Sugeno Fuzzy Models in Networked Systems

On the application of fuzzy-based flow control approach to High Altitude Platform communications

H<sub>∞</sub> Control of Uncertain Fuzzy Networked Control Systems with State Quantization

Contact Info

Product

Resources

About

Guaranteed Cost Networked Control for T–S Fuzzy Systems With Time Delays

Cited by 198 publications

References 21 publications

Analysis, Filtering, and Control for Takagi-Sugeno Fuzzy Models in Networked Systems

Analysis, Filtering, and Control for Takagi-Sugeno Fuzzy Models in Networked Systems

On the application of fuzzy-based flow control approach to High Altitude Platform communications

H&lt;sub&gt;∞&lt;/sub&gt; Control of Uncertain Fuzzy Networked Control Systems with State Quantization

Contact Info

Product

Resources

About

H<sub>∞</sub> Control of Uncertain Fuzzy Networked Control Systems with State Quantization