RETRACTED: Constrained cuckoo search algorithm and Takagi-Sugeno fuzzy models for predictive control

Taeib, Adel; Salhi, Hichem; Châari, Abdelkader

doi:10.1177/0142331220966308

Cited by 2 publications

(2 citation statements)

References 57 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In CS algorithm, a cuckoo’s egg in each nest represents a solution and the egg that cuckoo does not put in the nest represents a new solution. The goal is to replace the bad solution in the nest with the new solution or potential optimal solution (Ladhari et al, 2019; Taeib et al, 2021). In order to make the description more convenient in this algorithm, the following three provisions are made:…”

Section: Basic Theorymentioning

confidence: 99%

A two-stage classifier switchable aluminum electrolysis fault diagnosis method

Gao

Zhang

Shi

et al. 2021

Transactions of the Institute of Measurement and Control

View full text Add to dashboard Cite

Traditional aluminum electrolysis fault diagnosis methods have problems such as low accuracy, small forecast advance, and high CPU usage, which make their popularity low in enterprises. Aiming at the above problems, a fault diagnosis method with switchable two-level classifiers is designed. The input data are first judged by the first-level algorithm. If it is determined that there is no fault, the result will be output directly. If it is determined that there is a fault in the electrolytic cell, the data will be transferred to the second-level network for specific fault diagnosis. The first level is based on the Random Forest algorithm with simple structure and good two-class classification effect and is optimized by the improved cuckoo algorithm. The second level is based on an improved DBN-DNN (Deep Belief Neural Network–Deep Neural Network) algorithm, and the training method is given. Experimental results show that this method can switch between different algorithms according to different situations, save computing resources, realize that a computer can monitor multiple electrolytic cells, and reduce investment costs. In addition, the accuracy and forecast advance have been significantly improved, which has promoted the popularization of fault diagnosis systems in aluminum electrolysis enterprises.

show abstract

Section: Basic Theorymentioning

confidence: 99%

A two-stage classifier switchable aluminum electrolysis fault diagnosis method

Gao

Zhang

Shi

et al. 2021

Transactions of the Institute of Measurement and Control

View full text Add to dashboard Cite

show abstract

“…The authors finally applied the hybrid algorithm-based load frequency controller on a hybrid power system with multiple areas and sources for its robustness and effectiveness verification. A. Taeib et al [39] formulated an innovative Model Predictive Control (MPC) technique for nonlinear systems by combining Takagi-Sugeno (TS) fuzzy models and constrained CSA. The authors validated the efficacy of the hybridization scheme by executing it on a Three Tank System (TTS).…”

Section: Introductionmentioning

confidence: 99%

Fitness Dependent Optimizer Based Computational Technique for Solving Optimal Control Problems of Nonlinear Dynamical Systems

et al. 2023

View full text Add to dashboard Cite

This paper presents a pragmatic approach established on the hybridization of nature-inspired optimization algorithms and Bernstein Polynomials (BPs), achieving the optimum numeric solution for Nonlinear Optimal Control Problems (NOCPs) of dynamical systems. The approximated solution for NOCPs is obtained by the linear combination of BPs with unknown parameters. The unknown parameters are evaluated by the conversion of NOCP to an error minimization problem and the formulation of an objective function. The Fitness Dependent Optimizer (FDO) and Genetic Algorithm (GA) are used to solve the objective function, and subsequently the optimal values of unknown parameters and the optimum solution of NOCP are attained. The efficacy of the proposed technique is assessed on three real-world NOCPs, including Van der Pol (VDP) oscillator problem, Chemical Reactor Problem (CRP), and Continuous Stirred-Tank Chemical Reactor Problem (CSTCRP). The final results and statistical outcomes suggest that the proposed technique generates a better solution and surpasses the recently represented methods in the literature, which eventually verifies the efficiency and credibility of the recommended approach.INDEX TERMS bernstein polynomials, dynamical systems, fitness dependent optimizer, genetic algorithm, nonlinear optimal control problems, optimization problem, optimization techniques.

show abstract

RETRACTED: Constrained cuckoo search algorithm and Takagi-Sugeno fuzzy models for predictive control

Cited by 2 publications

References 57 publications

A two-stage classifier switchable aluminum electrolysis fault diagnosis method

A two-stage classifier switchable aluminum electrolysis fault diagnosis method

Fitness Dependent Optimizer Based Computational Technique for Solving Optimal Control Problems of Nonlinear Dynamical Systems

Contact Info

Product

Resources

About