scholarly journals Synchronization of Chaotic Systems with Dead Zones via Fuzzy Adaptive Variable-Structure Control

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Yongbing Huangfu ◽  
Kaijuan Xue
Keyword(s):  
Chaotic Systems ◽  
Fuzzy Inference ◽  
Fuzzy Variable ◽  
Variable Structure Control ◽  
Variable Structure ◽  
Dead Zones ◽  
Structure Control ◽  
Synchronization Problem ◽  
The Stability ◽  
Fuzzy Adaptive

This work is devoted to solving synchronization problem of uncertain chaotic systems with dead zones. Based on the Lyapunov stability theorems, by using fuzzy inference to estimate system uncertainties and by designing effective fuzzy adaptive controllers, the synchronization between two chaotic systems with dead zones is realized and a fuzzy variable-structure control is implemented. The stability is proven strictly, and all the states and signals are bounded in the closed-loop system. A simulation example is presented to test the theoretical results finally.

scholarly journals Fuzzy Adaptive Variable Structure Control of Second-Order Robotic Manipulators with Dead Zones

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Songyu Wang ◽  
Xianmin Hou
Keyword(s):  
Fuzzy Systems ◽  
Variable Structure ◽  
Second Order ◽  
Theoretical Derivation ◽  
Controlled System ◽  
Dead Zones ◽  
Structure Control ◽  
Adaptive Laws ◽  
The Stability ◽  
Fuzzy Adaptive

In this study, with respect to certain second-order robotic systems with dead zones, a fuzzy adaptive variable structure controller (VSC) is implemented. Some suitable adaptive fuzzy systems are used to estimate uncertain functions. Based on Lyapunov stability theorems, parameter adaptive laws are designed, and it is proven that all signals involved will remain bounded and the stability of the controlled system is also guaranteed. Our controller is effective for the system with or without sector nonlinearity. Finally, a simulation example is presented to illustrate the correctness of the theoretical derivation.

Enhanced Grey Variable Structure Control Methodology of Parallel-Connected DC-AC Inverters for Ultra-Precision Machining

2015 ◽  
Vol 661 ◽  
pp. 29-35
Author(s):  
En Chih Chang ◽  
Hung Liang Cheng ◽  
Chien Hsuan Chang ◽  
Jin Wei Liu ◽  
Chih Hsien Chuang ◽  
...  
Keyword(s):  
Output Voltage ◽  
Variable Structure Control ◽  
Variable Structure ◽  
Precision Machining ◽  
Structure Control ◽  
Highly Nonlinear ◽  
Ultra Precision ◽  
The Stability ◽  
Control Methodology ◽  
Voltage Harmonics

This paper develops an enhanced grey variable structure controlled DC-AC inverter in parallel, and is suitable for the application of ultra-precision machining (UPM). The enhanced grey variable structure control methodology consists of a nonlinear sliding function (NSF) and a grey model, GM(2,1). The NSF has finite system-state convergence time, and thus the AC output voltage regulation and balanced current-sharing among the parallel modules can be achieved. However, once the loading of the UPM is a highly nonlinear condition, the chatter still exists in NSF. The chatter may cause heat losses and high voltage harmonics in parallel-connected DC-AC inverter output, and thus deteriorates the stability and reliability of the UPM. To eliminate the chatter, the control gains of the NSF can be adjusted by the use of the GM(2,1) under system uncertainty bounds are overestimated. With the enhanced methodology, the parallel-connected DC-AC inverter yields a high-quality AC output voltage with low voltage harmonics and fast dynamic response under highly nonlinear loading, thus achieving the stability and reliability of the UPM. Experimental results are performed to demonstrate the enhanced methodology.

A New Fuzzy Variable Structure Control of a Type of Nonlinear Multivariable System

2006 ◽  
Vol 315-316 ◽  
pp. 623-627
Author(s):  
P. Wei ◽  
Z.L. Wang ◽  
L.H. Qiu
Keyword(s):  
High Efficiency ◽  
Control Method ◽  
Fuzzy Variable ◽  
Variable Structure Control ◽  
Variable Structure ◽  
Multivariable System ◽  
Robust Performance ◽  
Structure Control ◽  
System A ◽  
Novel Method

In order to improve the robust performance for a type of nonlinear multivariable system, a new fuzzy variable structure control method is introduced in detail, which combined the features of traditional variable structure control method with the advantages of the fuzzy control theory. The present work realized the linearization of the nonlinear multivariable system, and then the new fuzzy variable structure control method is applied to control the linearization system. The robust experiments were carried out on the novel method. The results indicated that the required robust performance could be achieved with high efficiency by utilizing the new method.

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