Tracking control for non-Gaussian stochastic distribution sampled-data fuzzy systems

2019 ◽  
Vol 356 ◽  
pp. 1-27 ◽  
Author(s):  
Yue Wu ◽  
Jiuxiang Dong
Keyword(s):  
Tracking Control ◽  
Fuzzy Systems ◽  
Sampled Data ◽  
Non Gaussian ◽  
Stochastic Distribution

scholarly journals Discrete-Time 2-Order Sliding Mode Fault-Tolerant Tracking Control for Non-Gaussian Nonlinear Stochastic Distribution Control Systems with Missing Measurements

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-13 ◽  
Author(s):  
Lifan Li ◽  
Lina Yao
Keyword(s):  
Fault Diagnosis ◽  
Discrete Time ◽  
Tracking Control ◽  
Fault Tolerant ◽  
Sliding Mode ◽  
General System ◽  
Missing Measurements ◽  
Non Gaussian ◽  
Probability Density Function Pdf ◽  
Stochastic Distribution

In this paper, a method of fault diagnosis (FD) and fault-tolerant tracking control (FTTC) is investigated for non-Gaussian nonlinear stochastic distribution control (SDC) systems with missing measurements. The phenomenon of the randomly occurring missing measurements is described as a Bernoulli process. The missing measurements during transmission are compensated with the data successfully transmitted at the previous moment. The residual signal of the fault diagnosis observer is different from that of the general system. Using the integral of the error of the output probability density function (PDF) as the driving information, the system state and fault can be estimated by an adaptive fault diagnosis observer. Then, a novel fault-tolerant tracking controller is designed based on a discrete-time 2-order sliding mode to make the post-fault PDF still track the target. Two simulated examples are included to illustrate the effectiveness of the theoretical results.

Aperiodic Sampled-Data Sliding-Mode Control of Fuzzy Systems With Communication Delays Via the Event-Triggered Method

2016 ◽  
Vol 24 (5) ◽  
pp. 1048-1057 ◽  
Author(s):  
Shiping Wen ◽  
Tingwen Huang ◽  
Xinghuo Yu ◽  
Michael Z. Q. Chen ◽  
Zhigang Zeng
Keyword(s):  
Sliding Mode Control ◽  
Fuzzy Systems ◽  
Sliding Mode ◽  
Communication Delays ◽  
Sampled Data ◽  
Mode Control ◽  
Event Triggered

Robust Tracking Control for Takagi–Sugeno Fuzzy Systems With Unmeasurable Premise Variables: Application to Tank System

2014 ◽  
Vol 136 (4) ◽  
Author(s):  
H. Ghorbel ◽  
A. El Hajjaji ◽  
M. Souissi ◽  
M. Chaabane
Keyword(s):  
Tracking Control ◽  
Fuzzy Systems ◽  
Design Procedure ◽  
Control Design ◽  
Linear Matrix ◽  
Robust Tracking Control ◽  
Fuzzy Observer ◽  
Tank System ◽  
System States ◽  
Takagi Sugeno

In this paper, a robust fuzzy observer-based tracking controller for continuous-time nonlinear systems presented by Takagi–Sugeno (TS) models with unmeasurable premise variables, is synthesized. Using the H∞ norm and Lyapunov approach, the control design for TS fuzzy systems with both unmeasurable premises and system states is developed to guarantee tracking performance of closed loop systems. Sufficient relaxed conditions for synthesis of the fuzzy observer and the fuzzy control are driven in terms of linear matrix inequalities (LMIs) constraints. The proposed method allows simplifying the design procedure and gives the observer and controller gains in only one step. Numerical simulation on a two tank system is provided to illustrate the tracking control design procedure and to confirm the efficiency of the proposed method.

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