Generalized Constraint Representation of Comparative Adjectives and Its Type-2 Fuzzy Modeling in PNL

This study presents a vibration control using actively tunable vibration absorbers (ATVA) to suppress vibration of a thin plate. The ATVA’s is made of a sandwich hollow structure embedded with the electrorheological fluid (ERF). ERF is considered to be one of the most important smart fluids and it is suitable to be embedded in a smart structure due to its controllable viscosity property. ERF’s apparent viscosity can be controlled in response to the electric field and the change is reversible in 10 microseconds. Therefore, the physical properties of the ERF-embedded smart structure, such as the stiffness and damping coefficients, can be changed in response to the applied electric field. A mathematical model is difficult to be obtained to describe the exact characteristics of the ERF embedded ATVA because of the nonlinearity of ERF’s viscosity. Therefore, a fuzzy modeling and experimental validations of ERF-based ATVA from stationary random vibrations of thin plates are presented in this study. Because Type-2 fuzzy sets generalize Type-1 fuzzy sets so that more modelling uncertainties can be handled, a semi-active vibration controller is proposed based on Type-2 fuzzy sets. To investigate the different performances by using different types of fuzzy controllers, the experimental measurements employing type-1 fuzzy and interval type-2 fuzzy controllers are implemented by the Compact RIO embedded system. The fuzzy modeling framework and solution methods presented in this work can be used for design, performance analysis, and optimization of ATVA from stationary random vibration of thin plates.

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Type-2 fuzzy instrumental variable algorithm for evolving neural-fuzzy modeling of nonlinear dynamic systems in noisy environment

Engineering Applications of Artificial Intelligence ◽

10.1016/j.engappai.2021.104620 ◽

2022 ◽

Vol 109 ◽

pp. 104620

Author(s):

Anderson Pablo Freitas Evangelista ◽

Ginalber Luiz de Oliveira Serra

Keyword(s):

Dynamic Systems ◽

Nonlinear Dynamic ◽

Instrumental Variable ◽

Fuzzy Modeling ◽

Nonlinear Dynamic Systems ◽

Noisy Environment ◽

Neural Fuzzy

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Type-2 Fuzzy Modeling for Acoustic Emission Signal in Precision Manufacturing

Modelling and Simulation in Engineering ◽

10.1155/2011/696947 ◽

2011 ◽

Vol 2011 ◽

pp. 1-12 ◽

Cited By ~ 5

Author(s):

Qun Ren ◽

Luc Baron ◽

Marek Balazinski

Keyword(s):

Acoustic Emission ◽

Tool Wear ◽

Fuzzy Modeling ◽

Machining Process ◽

Precision Machining ◽

Precision Manufacturing ◽

Emission Signal ◽

Tool Condition ◽

Ae Signal

This paper presents an application of type-2 fuzzy logic on acoustic emission (AE) signal modeling in precision manufacturing. Type-2 fuzzy modeling is used to identify the AE signal in precision machining. It provides a simple way to arrive at a definite conclusion without understanding the exact physics of the machining process. Moreover, the interval set of the output from the type-2 fuzzy approach assesses the information about the uncertainty in the AE signal, which can be of great value for investigation of tool wear conditions. Experiments show that the development of the AE signal uncertainty trend corresponds to that of the tool wear. Information from the AE uncertainty scheme can be used to make decisions or investigate the tool condition so as to enhance the reliability of tool wear.

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Towards a coevolutionary approach for interval type-2 fuzzy modeling

2011 IEEE Symposium on Advances in Type-2 Fuzzy Logic Systems (T2FUZZ) ◽

10.1109/t2fuzz.2011.5949563 ◽

2011 ◽

Cited By ~ 1

Author(s):

Hector Hostos ◽

Federico Sanabria ◽

Oscar Mendez ◽

Miguel Melgarejo

Keyword(s):

Fuzzy Modeling ◽

Interval Type

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Type-2 Fuzzy Modeling and Control of Nonlinear Steer-by-Wire Systems With Actuator Fault and Event-Triggered Communication

10.21203/rs.3.rs-273143/v1 ◽

2021 ◽

Author(s):

Bingxin Ma ◽

Yongfu Wang

Keyword(s):

Sliding Mode Control ◽

Sliding Mode ◽

Fuzzy Modeling ◽

Time Varying ◽

Actuator Fault ◽

Modeling And Control ◽

Steer By Wire ◽

And Control ◽

Event Triggered

Abstract This paper proposes the adaptive fuzzy modeling and control method for steer-by-wire (SbW) systems with uncertain nonlinearity, time-varying disturbance, actuator fault, and event-triggered communication. First, the adaptive interval type-2 fuzzy logic system (IT2 FLS) is developed to modeling the uncertain nonlinearity of SbW systems. The Lyapunov-based adaptive law can guarantee the modeling performance of IT2 FLS. Then, considering the limited communication channel bandwidth of the controller-area-network (CAN), the time-varying disturbance, and actuator fault of SbW systems, an event-triggered sliding mode control is proposed for SbW systems. The chattering phenomenon of the sliding mode control system can be eliminated by using the nested adaptive technology. Theoretical analysis shows that the practical finite-time stability of the closed-loop system can be achieved while avoiding the Zeno-behavior. Finally, numerical simulations and vehicle experiments are given to evaluate the effectiveness of the proposed methods.

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