Fuzzy Lyapunov-based approach to the design of fuzzy controllers

Margaliot, Michael; Langholz, G.

doi:10.1016/s0165-0114(98)00356-x

Cited by 90 publications

(30 citation statements)

References 3 publications

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“…The structure of a fuzzy controller will be different if different types of the components are used. There are various ways to design an asymptotically stable fuzzy logic controller [34,35]. In this paper, we used a Mamdani-type fuzzy inference system (FIS) to construct an asymptotically stable fuzzy s-dynamics (21 Input/output functions are mapped into fuzzy numbers using triangular and trapezoidal membership functions (Figs.…”

Section: Proposed Control Using the Tde And Fuzzy Logicmentioning

confidence: 99%

Control of Robot Manipulators Using Time-Delay Estimation and Fuzzy Logic Systems

Bae¹,

Jin²,

Suh³

et al. 2017

Journal of Electrical Engineering and Technology

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-A highly accurate model-free controller is proposed for trajectory tracking control of robot manipulators. The proposed controller incorporates time-delay estimation (TDE) to estimate and cancel continuous nonlinearities of robot dynamics, and exploits fuzzy logic systems to suppress the effect of the TDE error, which is due to discontinuous nonlinearities such as friction. To this end, integral sliding mode is defined using desired error dynamics, and a Mamdani-type fuzzy inference system is constructed. As a result, the proposed controller achieves the desired error dynamics well. Implementation of the proposed controller is easy because the design of the controller is intuitive and straightforward, and calculations of the complex robot dynamics are not required. The tracking performance of the proposed controller is verified experimentally using a 3-degree of freedom PUMAtype robot manipulator.

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Section: Proposed Control Using the Tde And Fuzzy Logicmentioning

confidence: 99%

Control of Robot Manipulators Using Time-Delay Estimation and Fuzzy Logic Systems

Bae¹,

Jin²,

Suh³

et al. 2017

Journal of Electrical Engineering and Technology

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“…The stability analysis of DFLC is carried out by using the method explained in Margaliot and Langholz (1999). In this method, a Lyapunov function candidate 'V(x)' is selected and following conditions are established: C1 :…”

Section: Appendix a Stability Analysismentioning

confidence: 99%

Design and tuning of a Decentralized Fuzzy Logic Controller for a MIMO type Pressurized Heavy Water Reactor

Wallam

Abbas

Abbasi

2015

Annals of Nuclear Energy

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“…Also, the stability analysis may be dependent of the system input as well as the initial condition. One major problem that nonlinear systems have is that an exact mathematical solution is in many cases impossible to obtain (see also [97]). …”

Section: Definition (Equilibrium Point)mentioning

confidence: 99%

An Overview of Fuzzy Control Theory

Peeters

2008

Foundations of Generic Optimization

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This chapter may serve as an introductory article, and is meant to give an overview of the mathematical methods applied in fuzzy control techniques, such as fuzzification, aggregation and defuzzification. We will also discuss the advantages and disadvantages of the several techniques, with respect to the achievability of their goals, and we will give a brief overview of "hybrid techniques", techniques that involves fuzzy control as well as other artificial intelligent computing methods, such as neural networks and genetic algorithms.

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Fuzzy Lyapunov-based approach to the design of fuzzy controllers

Cited by 90 publications

References 3 publications

Control of Robot Manipulators Using Time-Delay Estimation and Fuzzy Logic Systems

Control of Robot Manipulators Using Time-Delay Estimation and Fuzzy Logic Systems

Design and tuning of a Decentralized Fuzzy Logic Controller for a MIMO type Pressurized Heavy Water Reactor

An Overview of Fuzzy Control Theory

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