Guaranteed cost control of singular networked control systems with time-delay

Author(s):  
Li-li Liu ◽  
Ning Li ◽  
Qing-ling Zhang
2014 ◽  
Vol 926-930 ◽  
pp. 1580-1583
Author(s):  
Meng Meng Wang ◽  
Bin Liu ◽  
Bo Xiao

The guaranteed cost of networked control systems with long time delay is researched. Using the algorithm of augmented vectors, the form of the state equation of the system is changed and it becomes more simple. Then the corresponding performance index is given. Finally, a suitable guaranteed cost control law of the NCSs (Networked Control Systems) is designed by simple matrix inequalities. The results meet the stability of the system and the requirement of performance index. An simulation example is employed to illustrate the validity of the method.


2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
Linqin Cai ◽  
Zhuo Yang ◽  
Jimin Yu ◽  
Zhenhua Zhang

This paper deals with the problem of guaranteed cost control for a class of nonlinear networked control systems (NCSs) with time-varying delay. A guaranteed cost controller design method is proposed to achieve the desired control performance based on the switched T-S fuzzy model. The switching mechanism is introduced to handle the uncertainties of NCSs. Based on Lyapunov functional approach, some sufficient conditions for the existence of state feedback robust guaranteed cost controller are presented. Simulation results show that the proposed method is effective to guarantee system’s global asymptotic stability and quality of service (QoS).


Author(s):  
SHANBIN LI ◽  
YONGQIANG WANG ◽  
FENG XIA ◽  
YOUXIAN SUN

In this paper, the random time-delays and packet losses issues of networked control systems (NCS) within the framework of guaranteed cost control for Markovian jump linear systems (MJLSs) are addressed. A new delay-dependent sufficient condition for the existence of guaranteed cost controller and an upper bound of the cost function are presented by a new stochastic Lyapunov–Krasovskii functional. The state feedback problem for such system is formulated as a convex optimization over a set of linear matrix inequalities (LMIs) which can be very efficiently solved by interior-point methods. As examples to verify the proposed method, two plants in the networked setup are considered. The simulation results demonstrate the effectiveness of the method.


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