Interval type-2 Takagi-Sugeno fuzzy controller design for a class of nonlinear singular networked control systems

2012 ◽  
Author(s):  
Chwan-Lu Tseng ◽  
Shun-Yuan Wang ◽  
Shou-Chuang Lin ◽  
Yu-Yuan Chen
Keyword(s):  
Control Systems ◽  
Fuzzy Controller ◽  
Controller Design ◽  
Networked Control Systems ◽  
Networked Control ◽  
Interval Type ◽  
Takagi Sugeno

scholarly journals Actuator Saturated Fuzzy Controller Design for Interval Type-2 Takagi-Sugeno Fuzzy Models with Multiplicative Noises

Processes ◽  
2021 ◽  
Vol 9 (5) ◽  
pp. 823
Author(s):  
Wen-Jer Chang ◽  
Yu-Wei Lin ◽  
Yann-Horng Lin ◽  
Chin-Lin Pen ◽  
Ming-Hsuan Tsai
Keyword(s):  
Nonlinear Systems ◽  
Fuzzy Controller ◽  
Controller Design ◽  
Actuator Saturation ◽  
Design Method ◽  
Fuzzy Model ◽  
The Stability ◽  
Interval Type ◽  
Takagi Sugeno

In many practical systems, stochastic behaviors usually occur and need to be considered in the controller design. To ensure the system performance under the effect of stochastic behaviors, the controller may become bigger even beyond the capacity of practical applications. Therefore, the actuator saturation problem also must be considered in the controller design. The type-2 Takagi-Sugeno (T-S) fuzzy model can describe the parameter uncertainties more completely than the type-1 T-S fuzzy model for a class of nonlinear systems. A fuzzy controller design method is proposed in this paper based on the Interval Type-2 (IT2) T-S fuzzy model for stochastic nonlinear systems subject to actuator saturation. The stability analysis and some corresponding sufficient conditions for the IT2 T-S fuzzy model are developed using Lyapunov theory. Via transferring the stability and control problem into Linear Matrix Inequality (LMI) problem, the proposed fuzzy control problem can be solved by the convex optimization algorithm. Finally, a nonlinear ship steering system is considered in the simulations to verify the feasibility and efficiency of the proposed fuzzy controller design method.

scholarly journals Reducing the Impact of Uncertainties in Networked Control Systems Using Type-2 Fuzzy Logic

2015 ◽  
Vol 65 (6) ◽  
pp. 364-370 ◽  
Author(s):  
Blaho Michal ◽  
Murgaš J´n ◽  
Viszus Eugen ◽  
Fodrek Peter
Keyword(s):  
Control Systems ◽  
Time Delays ◽  
Fuzzy Controller ◽  
Networked Control Systems ◽  
Networked Control ◽  
Negative Effects ◽  
Packet Losses ◽  
Control Schemes ◽  
The Impact

Abstract The networked control systems (NCS) have grown in popularity in recent years. Despite their advantages over the traditional control schemes, some of their drawbacks emerged as well (time delays, packet losses). There are several ways of dealing with the time delays and packet losses in NCS, but only a few authors have ever used type-2 fuzzy controllers for this purpose to our knowledge. This paper is aimed at dealing with the negative effects that occur in NCS, by using type-2 fuzzy control systems. It is presented that this approach can be successfully used to decrease the effects of time delays and packet losses. A type-2 fuzzy controller has been designed and compared to a type-1 fuzzy controller. The intervals of type-2 fuzzy controller were optimized via genetic algorithm.

L1 control for Itô stochastic nonlinear networked control systems

2020 ◽  
Vol 42 (14) ◽  
pp. 2675-2685
Author(s):  
Ji Qi ◽  
Yanhui Li
Keyword(s):  
Control Systems ◽  
Fuzzy Controller ◽  
Controller Design ◽  
Networked Control Systems ◽  
Fuzzy Model ◽  
Networked Control ◽  
Linear Matrix ◽  
Packet Dropout ◽  
Data Packet Dropout ◽  
Nonlinear Networked Control Systems

This paper investigates L1 control problem for a class of nonlinear stochastic networked control systems (NCSs) described by Takagi-Sugeno (T-S) fuzzy model. By exploiting a delay-dependent and basis-dependent Lyapunov-Krasovskii function and by means of the Itô stochastic differential equation technique, results on stability and L1 performance are proposed for the T-S fuzzy stochastic NCS. Specially, attention is focused on the fuzzy controller design that guarantees the closed-loop T-S fuzzy stochastic NCS is mean-square asymptotically stable and satisfies a prescribed L1 noise attenuation level [Formula: see text] with respect to all persistent and amplitude-bounded disturbance input signals. To reduce the conservatism of design, the signal transmission delay, data packet dropout, and quantization have been taken into consideration in the controller design. The corresponding design problem of L1 controller is converted into a convex optimization problem by solving a set of linear matrix inequalities (LMIs). Finally, simulation examples are provided to illustrate the feasibility and effectiveness of the proposed method.

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