Nonlinear system identification based on ANFIS-Hammerstein model using Gravitational search algorithm

Cuevas, Erik; Diaz, Parris; Ávalos, Omar; Zaldívar, Daniel; Pérez‐Cisneros, Marco

doi:10.1007/s10489-017-0969-1

Cited by 51 publications

(17 citation statements)

References 49 publications

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“…As an example, Table 1 [25] shows the parameter estimation results for a penicillin fed-batch fermentation process by three different methods, including Nonlinear Programming Method (NPM) [26], Particle Swarm Optimization (PSO) [27], and Gravitational Search Algorithm (GSA) [28]. This table illustrates the fact that different parameter estimation methods have identified mean values of model parameters, while the standard deviations of one parameter by different methods are not identical.…”

Section: Model Stochastics In Industrial Processesmentioning

confidence: 99%

Quality-Relevant Monitoring of Batch Processes Based on Stochastic Programming with Multiple Output Modes

Shen

Zheng

et al. 2020

Processes

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To implement the quality-relevant monitoring scheme for batch processes with multiple output modes, this paper presents a novel methodology based on stochastic programming. Bringing together tools from stochastic programming and ensemble learning, the developed methodology focuses on the robust monitoring of process quality-relevant variables by taking the stochastic nature of batch process parameters explicitly into consideration. To handle the problem of missing data and lack of historical batch data, a bagging approach is introduced to generate individual quality-relevant sub-datasets, which are used to construct the corresponding monitoring sub-models. For each model, stochastic programming is used to construct an optimal quality trajectory, which is regarded as the reference for online quality monitoring. Then, for each sub-model, a corresponding control limit is obtained by computing historical residuals between the actual output and the optimal trajectory. For online monitoring, the current sample is examined by all sub-models, and whether the monitoring statistic exceeds the control limits is recorded for further analysis. The final step is ensemble learning via Bayesian fusion strategy, which is under the probabilistic framework. The implementation and effectiveness of the developed methodology are demonstrated through two case studies, including a numerical example, and a simulated fed-batch penicillin fermentation process.

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Section: Model Stochastics In Industrial Processesmentioning

confidence: 99%

Quality-Relevant Monitoring of Batch Processes Based on Stochastic Programming with Multiple Output Modes

Shen

Zheng

et al. 2020

Processes

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“…Mining method was first named for mining ore; the main construction method is ''drilling excavation,'' ''steel and wood support,'' and this construction method mostly needs drilling hole blasting, so it is also called drilling method [13,14]. The mining method is mainly applied to the construction of subway stations with rock formations and tunnels from hard rock formations to the fourth century strata with certain self-stability ability [15,16]. At present, the mining method is widely used in the construction of subway tunnel, and the construction experience is quite mature [17,18].…”

Section: Application Of Mining Lawmentioning

confidence: 99%

Safety diagnosis of TBM for tunnel excavation and its effect on engineering

Wei

Song

Wang

et al. 2020

Neural Comput & Applic

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Since the development of tunnel construction technology, different tunnel excavation technologies have also been derived for different conditions. The safety diagnosis before the TBM mining method is particularly important. With the technology of safety diagnosis, the excavation process has the following effects on the tunnel engineering work. Great guarantee. The purpose of this paper is to study the excavation process of tunnel machinery for safety diagnosis before mining by TBM. It mainly includes step excavation method, full-section excavation method, guide pit excavation method and other technologies. This article uses a city subway construction project as an example to discuss in-depth the study of tunnel machinery excavation technology before the safety diagnosis of the mining method. The specific project is a city subway line with a total length of about 25.464 km and a total of 22 stations, including 9 transfer station. Based on field engineering experiments, the problems encountered in tunnel mechanical excavation are studied. The experimental data show that the results obtained through engineering tests can guarantee the safe and stable construction of the tunnel project, and the safety rate can reach 90%. The experimental results show that the obtained results can ensure the safety of tunnel mechanical excavation.

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“…In this research work, a concerted strategic bid with the aims of benefit maximization with the amalgamation of RESs with conventional power supplies is suggested. Using the novel heuristic approach Gravitational Search Algorithm (GSA) [30] - [35], this problem was solved. GSA is well-established depending on gravity law and mass interactions with its application to a power system problem.…”

Section: Introductionmentioning

confidence: 99%

Strategic Bidding in the Presence of Renewable Sources for Optimizing the Profit of the Power Suppliers

et al. 2021

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The fast globalization of renewable energy-based technologies has enabled its wide speared utilization as well. This has shaped a new prospect of operation in the modern electricity system. But, its dependency on environmental factors leads to an uncertain scenario in the day-ahead electricity market. During this period, compromises are made in the genuine process of expenditure and resources of the producers to offset the capacity that decreases the profits for the producers. In general, a significant variety of scenarios need to be taken into account when describing uncertainty, thereby necessitating the need for techniques of scenario reduction. Therefore, to manage the intractable effects of solar radiation and wind speed instability, the function of the Beta and Weibull distribution of probability is implemented, respectively, and scenarios are minimized using forward-reduction algorithms. Besides, an underestimation and overestimation of the cost function are used to calculate the deviation of renewable influence. Thus, this paper is suggesting a valuable bidding strategy to maximize the remuneration of electricity producers in the presence of rival competitors and the instability of solar and wind energy. This problem has been prepared by taking the benchmark IEEE 30-bus network with and without renewable energy sources, and this problem has been solved by using the Gravitational Search Algorithm. The observations of the outcome demonstrate the appropriateness of the projected bid strategy in the presence of volatility of renewable energy.

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Nonlinear system identification based on ANFIS-Hammerstein model using Gravitational search algorithm

Cited by 51 publications

References 49 publications

Quality-Relevant Monitoring of Batch Processes Based on Stochastic Programming with Multiple Output Modes

Quality-Relevant Monitoring of Batch Processes Based on Stochastic Programming with Multiple Output Modes

Safety diagnosis of TBM for tunnel excavation and its effect on engineering

Strategic Bidding in the Presence of Renewable Sources for Optimizing the Profit of the Power Suppliers

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