Fuzzy logic based multistage relaying model for cascaded intelligent fault protection scheme

Samonto, Soumyadeep; Kar, Samarjit; Pal, Sagarika; Sekh, Arif Ahmed

doi:10.1016/j.epsr.2020.106341

Cited by 9 publications

(5 citation statements)

References 4 publications

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“…The system explained here is an over current system. The purpose of selecting Gaussian membership function as an input function is because of its centre which is given in Equation (1). In this work, a comparative analysis is performed among Gaussian, Trapezoidal and Triplets as an input membership function of the fuzzy inference system (FIS) as shown in Figure 7, Figures 9-10 respectively.…”

Section: Resultsmentioning

confidence: 99%

“…Incorporation of intelligent system in protection domain has nowadays become one of the most discussed agenda in the field of electrical engineering. Various works have been explored on power system protection by introducing artificial intelligence [1] [2] into various categories of breaker, like [3] [4] [5] [6]. Fault is an unbalanced state that occurs in any normal system.…”

Section: Introductionmentioning

confidence: 99%

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Fuzzy Based Algorithm for Stage-I of Cascaded Intelligent Relaying

Samonto¹,

Kar²,

Pal³

et al. 2021

IJIS

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Fuzzy Based Algorithm for Stage-I of Cascaded Intelligent Relaying

Samonto¹,

Kar²,

Pal³

et al. 2021

IJIS

Self Cite

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“…There are various types and shapes [38][39][40][41][42] of membership functions (MF) used at the fuzzyfication layer. In this paper the type II Gaussian MF with uncertain standard deviation [43][44][45] has been proposed.…”

Section: Fuzzyfication Layermentioning

confidence: 99%

“…The structure of the NN is inspired by the Elman model. Another visible path are fuzzy systems, these are used not only for motors but also for the stability of energy systems [39,40], and others [41].…”

Section: Introductionmentioning

confidence: 99%

Fuzzy Adaptive Type II Controller for Two-Mass System

et al. 2022

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This paper presents original concepts of control systems for an electrical drive with an elastic mechanical coupling between the motor and the driven mechanism. The synthesis procedure of the speed controller uses a proposed quality index (cost function) of system operation ensures the minimization of both tracking errors and torsional vibrations. Proper selection of the cost function focusses more on the reduction of torsional vibrations due to their negative influence on the drive’s mechanical coupling vitality. The omission of the plant identification of an adaptive fuzzy controller was proposed. Two types of fuzzy controllers were analyzed, namely with type I and type II fuzzy membership functions. The novelty of the presented approach is in the application of a Petri transition layer in a type II fuzzy controller which reduces the numerical complexity in case of a large number of complicated type II fuzzy sets. The presented simulation and experimental results prove that the best dumping of mechanical vibrations ensures the adaptive fuzzy controller with type II functions and a Petri transition layer.

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“…However, checking all Figures 10-12, they are symmetric around the origin and have an odd number of MFs, as specified in Section 3.1. The MFs for the angular velocity error input for both joints were originally defined, as it is shown for the input of the system in [29], where a multistage intelligent relaying in priority based decision is controlled via a fuzzy inference system, with some gaps in the definition of the sets; however, such gaps contradict the conditions outlined in Section 3.1, which were corrected via a Genetic Algorithms optimisation, as it is indicated in the following paragraphs. Singletons were used for the output fuzzy sets in order to expedite the computation of the SFC when it is implemented in real-time, as was defined in Section 3.1 without a loss of generalisation.…”

Section: Sfc Plus Feedforward Designmentioning

confidence: 99%

Sectorial Fuzzy Controller Plus Feedforward for the Trajectory Tracking of Robotic Arms in Joint Space

et al. 2021

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In this paper, we propose a Sectorial Fuzzy Controller (SFC) with a feedforward compensation of the robot dynamics in joint space, evaluated at the desired angular positions, velocities, and accelerations, applied to the trajectory tracking of all revolute joints robotic arms. Global uniform asymptotic stability proof applying the direct Lyapunov theorem, is introduced for this new control scheme by using a strict Lyapunov function. This strict Lyapunov function is the first one within the field of fuzzy control that is applied to the trajectory control of robotic manipulators. With this strict Lyapunov function, a sensitivity analysis was also computed for this novel control scheme. Additionally, physical and simulation experimental results are given in comparison to the original control scheme, in which this new controller is inspired: the Proportional-Derivative (PD) controller plus feedforward compensation. The experimental results yielded better performance for the new fuzzy control scheme when compared to the classical structure, in both the joint position errors for similar or smaller values of applied torques, showing the expected tolerance to parametric deviations and uncertainties that all fuzzy controllers possess.

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Fuzzy logic based multistage relaying model for cascaded intelligent fault protection scheme

Cited by 9 publications

References 4 publications

Fuzzy Based Algorithm for Stage-I of Cascaded Intelligent Relaying

Fuzzy Based Algorithm for Stage-I of Cascaded Intelligent Relaying

Fuzzy Adaptive Type II Controller for Two-Mass System

Sectorial Fuzzy Controller Plus Feedforward for the Trajectory Tracking of Robotic Arms in Joint Space

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