The fault diagnosis inverse problem with Ant Colony Optimization and Ant Colony Optimization with dispersion

Echevarría, Lídice Camps; Velho, Haroldo Fraga de Campos; Becceneri, José Carlos; Neto, Antônio José da Silva; Llanes‐Santiago, Orestes

doi:10.1016/j.amc.2013.11.062

Cited by 16 publications

(2 citation statements)

References 23 publications

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“…In [26] an analysis of communication policies by using ACO, specifically demonstrated that the relative effectiveness of alternative communication policies changes as the ACO cost functions increase or decrease. In [27] the results demonstrate the applicability of ACO, as well as the fact that parameter values allow for more diversification of the search result in a more accurate diagnostic result, and path planning in the fault diagnosis of the Inverted-Pendulum System. Furthermore, ACO has been frequently utilized to fine-tune the parameters of PID controllers.…”

Section: Introductionmentioning

confidence: 72%

A New Hybrid Ant Colony Optimization Based PID of the Direct Torque Control for a Doubly Fed Induction Motor

Mahfoud

Derouich

Ouanjli

et al. 2022

WEVJ

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Due to its advantages, the Proportional Integral Derivative (PID) controller has been the most widely used controller in the industrial sector. It allows linear systems to have good performance, but if the system is subjected to physical variation conditions, the system’s behavior becomes non-linear, in which case the PID controller is insufficient. The use of the PID controller for speed control in rotating machines, such as the doubly fed induction motor (DFIM) is widely used, but the non-linearity of the machine parameters allows for undesirable behaviors, resulting in overshoots and torque ripples. For this reason, several techniques have been adopted to increase the DTC’s robustness. One finds the integration of artificial intelligence as optimization algorithms. These algorithms are used to generate gains close to the optimum, converging the behavior of the DFIM to its optimum. In this work, an Ant Colony Optimization (ACO) algorithm was proposed to adjust the PID controller gains of the DTC control to control the DFIM, using a combined weighting cost function, to obtain efficient torque and speed control. This paper presents a new hybrid structure resulting from the intelligent ACO-DTC control implemented on Matlab-Simulink. The performance results extracted from the simulation showed the effectiveness of the intelligent ACO-DTC control, which provides satisfactory performance in terms of rapidity, stability, precision, and torque ripples compared to the conventional DTC.

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Section: Introductionmentioning

confidence: 72%

A New Hybrid Ant Colony Optimization Based PID of the Direct Torque Control for a Doubly Fed Induction Motor

Mahfoud

Derouich

Ouanjli

et al. 2022

WEVJ

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“…The most widely used method to solve such a problem is its least squares (LSQ) formulation as the minimization of an error function between the real measurements and their calculated values, similar to the above improved parameter estimation methods. Meanwhile, meta-heuristics for LSQ optimization are popular due to their inherent advantages, like their global optimum and the few requirements for problem formulation [11,12]. However, the running speed of the LSQ-based method is slow owing to its time-consuming iterative optimization of fault parameters.…”

mentioning

confidence: 99%

A Hybrid Inverse Problem Approach to Model-Based Fault Diagnosis of a Distillation Column

et al. 2020

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Early-stage fault detection and diagnosis of distillation has been considered an essential technique in the chemical industry. In this paper, fault diagnosis of a distillation column is formulated as an inverse problem. The nonlinear least squares algorithm is used to evaluate fault parameters embedded in a nonlinear dynamic model of distillation once abnormal symptoms are detected. A partial least squares regression model is built based on fault parameter history to explicitly predict the development of fault parameters. With the stripper of Tennessee Eastman process as example, this novel approach is tested for step- and random-type faults and several factors affecting its efficiency are discussed. The application result shows that the hybrid inverse problem approach gives the correct change of fault parameter at a speed far faster than the base approach with only a nonlinear model.

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Global Optimization in Space Engineering

Fliege

Coutinho²

2022

Encyclopedia of Optimization

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The fault diagnosis inverse problem with Ant Colony Optimization and Ant Colony Optimization with dispersion

Cited by 16 publications

References 23 publications

A New Hybrid Ant Colony Optimization Based PID of the Direct Torque Control for a Doubly Fed Induction Motor

A New Hybrid Ant Colony Optimization Based PID of the Direct Torque Control for a Doubly Fed Induction Motor

A Hybrid Inverse Problem Approach to Model-Based Fault Diagnosis of a Distillation Column

Global Optimization in Space Engineering

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