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Article
Automation & Control Systems
Mohammad Hosein Sabzalian et al.
Summary: This study presents a novel observer-based fuzzy control method for chaotic systems with unmeasurable states, unknown input constraints and unknown dynamics. The proposed control system shows good performance in the face of disturbances, uncertainties, unknown and time-varying input nonlinearities, unmeasurable states, and noisy faults, and is more effective compared to other types of fuzzy systems.
INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE
(2023)
Article
Automation & Control Systems
Hooman Mohammadi Moghadam et al.
Summary: This paper introduces a new type-2 fuzzy logic control (T2FLC) for active/reactive power regulation and energy storage management in an independent microgrid. By tuning the rules of T2FLCs and optimizing the parameters using a Kalman filter, the system is able to achieve good performance in various disturbed scenarios. Additionally, managing the electrical storage system in a specific way helps the system separate from mechanical inertia and reduce voltage oscillations caused by output power variations.
TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL
(2022)
Article
Computer Science, Artificial Intelligence
Muhammet Deveci et al.
Summary: This study ranks and classifies the indicators affecting the site selection of vehicle shredding facilities using a Delphi approach based on interval type-2 fuzzy sets. The results show that financial benefit is the most important indicator, and critical indicators include acquisition cost, affected population, and demand fluctuations.
APPLIED SOFT COMPUTING
(2022)
Article
Computer Science, Artificial Intelligence
Andrew Xavier Raj Irudayaraj et al.
Summary: This paper proposes an improved form of chaotic based atom search optimization (IASO) algorithm by adapting one-dimensional chaotic map. The performance of the proposed algorithm is evaluated and compared with the ASO algorithm using benchmark functions. The results demonstrate that the proposed algorithm outperforms in terms of mean, standard deviation, and best values. Additionally, the proposed algorithm is applied to solve the automatic load frequency control (ALFC) problem in a multi-area, multi-source hybrid power system (HPS), and the results show significant improvement compared to the ASO algorithm. The stability and effectiveness of the proposed algorithm are further analyzed through sensitivity analysis and real-time application testing.
APPLIED SOFT COMPUTING
(2022)
Article
Computer Science, Artificial Intelligence
Abdollah Amirkhani et al.
Summary: This paper presents a framework for the design of a genetically evolved cognitive tracking controller based on IT2-FCM, utilizing a systematic approach based on genetic algorithms to optimize parameters and learn fuzzy rules. Experimental results demonstrate the superiority of the proposed cognitive control system over conventional and fuzzy controllers.
INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS
(2022)
Article
Automation & Control Systems
Hengameh Mirhajianmoghadam et al.
Summary: This study explores how emotions align with model predictive control (MPC), proposing emotion-based neural cognitive networks (HENN) and hierarchical HENN (H2ENN) to address the computational cost issue in nonlinear MPC. Theoretical analysis proves the convergence of the learning algorithm. H2ENN demonstrates better accuracy and lower computational cost in controlling a nonlinear robot manipulator compared to traditional neural network methods.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2022)
Article
Automation & Control Systems
Yekai Yang et al.
Summary: This work addresses the SMC problem for discrete-time interval type-2 fuzzy singularly perturbed systems. A dynamic event-triggering scheme and epsilon-independent conditions are proposed for stability and reachability, and an optimization control design framework with a learning-based iterative algorithm is established. The proposed SMC scheme is verified through simulation results.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2022)
Article
Automation & Control Systems
Dongyu Li et al.
Summary: In this article, the definition and relevant sufficient condition for simultaneous arrival to origin (SATO) convergence are proposed. The differences between classical and norm-normalized sign functions are studied along with their applications in sliding-mode control design. It is found that the norm-normalized sign function enables SATO convergence and achieves consensus in a networked system.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2022)
Article
Computer Science, Information Systems
Yekai Yang et al.
Summary: This work investigates the self-triggered control issue for interval type-2 (IT2) fuzzy systems. A self-triggered scheme is used to determine the transmission of the system state. A self-triggered IT2 fuzzy controller is designed, which allows flexible selection of fuzzy rules and membership functions (MFs) independent of the controlled fuzzy system. The relationship between the triggered state and the system state is explicitly established, and the boundaries of MFs in the local operation region are given.
INFORMATION SCIENCES
(2022)
Article
Computer Science, Artificial Intelligence
Shaohua Luo et al.
Summary: This article proposes a hierarchical neural network structure to solve the problem of optimal synchronization for coupled fractional-order chaotic electromechanical devices. The presented scheme includes an adaptive neural feedforward policy and an optimal neural feedback policy to force the slave system to synchronize with the master system. The simulation results verify the effectiveness of the proposed scheme in achieving optimal synchronization and maintaining dynamic stability.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2022)
Article
Computer Science, Artificial Intelligence
Rajendra Kumar Khadanga et al.
Summary: This paper proposes a novel strategy, named MGWO-CS algorithm, by combining the Modified Grey wolf optimization algorithm and the Cuckoo search algorithm. The superiority of the proposed algorithm in terms of implementation time and solution quality is compared with the original algorithm through benchmark test functions. Furthermore, the effectiveness of the proposed algorithm is demonstrated by designing a TID controller for a two-area power system with a photovoltaic system.
APPLIED SOFT COMPUTING
(2022)
Article
Computer Science, Artificial Intelligence
S. Mohammad Tahamipour-Z et al.
Summary: In this paper, a hybrid framework of interval type-2 fuzzy systems and generalized fuzzy hyperbolic models (GFHMs) is proposed for modeling and controlling nonlinear systems. Experimental results demonstrate the advantages of this approach in handling uncertainty, simplifying computational structure, and improving tracking performance.
APPLIED SOFT COMPUTING
(2022)
Article
Multidisciplinary Sciences
Qinwei Fan et al.
Summary: This paper presents a novel parametric conjugate gradient method based on the secant equation for training Elman neural network. The theoretical convergence of the algorithm is rigorously proved, and the feasibility and correctness of the method are demonstrated through numerical experiments.
ADVANCED THEORY AND SIMULATIONS
(2022)
Article
Management
Cong-Cong Li et al.
Summary: With the advancement of information and network technology, data-driven methodologies have become crucial in decision-making processes due to the generation of large amounts of data from the Internet. However, there is limited research on personalized individual semantics (PIS) in the context of multi-attribute decision-making (MADM). This study proposes a data-driven learning model that analyzes PIS to support a multi-attribute decision-making model considering pre-existing classification of the alternatives. The feasibility of the proposed model is justified through case studies and comparisons with other methods.
OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE
(2022)
Article
Energy & Fuels
Yan Cao et al.
Summary: A new predictive frequency management system is proposed for multi-area microgrids, which utilizes deep learning and singular value decomposition to model uncertainties and improve the robustness and regulation accuracy of the system.
Article
Computer Science, Artificial Intelligence
Wei Dong et al.
Summary: The paper presents an adaptive optimal fuzzy logic based energy management solution for multi-energy microgrids, addressing the intermittent and stochastic nature of highly penetrated renewable energy sources and demand. By using a novel offline meta-heuristic optimization algorithm, the solution enables real-time energy dispatch to meet various operational criteria.
APPLIED SOFT COMPUTING
(2021)
Article
Computer Science, Artificial Intelligence
Selman Karagoz et al.
Summary: This paper highlights the importance of managing end-of-life vehicles (ELVs) and the need for an additional ELV recycling facility in Istanbul. It introduces a novel approach to address the multi-criteria and highly uncertain nature of the facility location problem. The potential and applicability of the proposed method is demonstrated through a real-life case study in Istanbul, showing its validity and consistency compared to existing state-of-the-art methods.
APPLIED SOFT COMPUTING
(2021)
Article
Computer Science, Information Systems
Hua Zheng et al.
Summary: This paper proposes a method for relaxed stabilization of T-S fuzzy systems, obtaining stability conditions through MF unified space extremum calculation technique and piecewise Lyapunov function, and designing a state-feedback local controller to close the loop. Both MF extremum enveloping and piecewise linear approximation methods are utilized to achieve relaxed stability and robustness conditions for the system.
INFORMATION SCIENCES
(2021)
Article
Environmental Sciences
Ziyan Zhang et al.
Summary: This study developed a method for predicting haze concentration based on one-dimensional convolutional neural networks, with an accuracy of over 95%, which can support other studies on haze prediction.
Article
Computer Science, Information Systems
Xiaoxue Wu et al.
Summary: The study introduces hbrPredictor, a method that combines interactive machine learning and active learning for HBR prediction. It significantly reduces the number of bug reports needed for training the prediction model while enhancing the diversity and generalization ability of training samples through uncertainty sampling. Experimental results show that hbrPredictor outperforms baselines in security bug report prediction, achieving maximum values of F1-score (0.7939) and AUC (0.8789), and can reach optimal performance with a significantly reduced number of bug reports for both small-sized and large-sized datasets.
INFORMATION AND SOFTWARE TECHNOLOGY
(2021)
Article
Computer Science, Information Systems
Sultan Noman Qasem et al.
Summary: In this study, a new self-organizing interval type-3 fuzzy logic system is proposed with an adaptive fuzzy kernel size to enhance the robustness against non-Gaussian noise. Simulation examples demonstrate that the introduced system and learning algorithm outperform other types of fuzzy neural networks and conventional learning techniques in terms of accuracy. The proposed learning method shows improved robustness against non-Gaussian noise compared to traditional Kalman filters.
INFORMATION SCIENCES
(2021)
Article
Automation & Control Systems
Tiechao Wang et al.
Summary: An adaptive interval type-2 fuzzy event-triggered saturation control scheme is proposed for a photovoltaic power system with uncertain equivalent resistances and grid voltage disturbances. The use of interval type-2 fuzzy logic systems has shown to effectively handle the uncertain nonlinear dynamics. Through backstepping control design and command filtered techniques, an event-triggered saturation controller is designed to ensure constrained control signals, with bounded variables in the closed-loop photovoltaic system according to Lyapunov theory. Simulation results confirm the effectiveness and superiority of the presented control method.
INTERNATIONAL JOURNAL OF FUZZY SYSTEMS
(2021)
Article
Automation & Control Systems
Ardashir Mohammadzadeh et al.
Summary: This paper proposes a novel control approach for a class of uncertain nonlinear system with unmodeled dynamics, modeling each output with several first-order dynamic fractional-order fuzzy systems and selecting the best dynamic model at a period of time. The adaptation laws for the consequent parameters of IT3FLSs are derived through stability analysis of the fractional-order systems based on the linear matrix inequality approach, and the effectiveness of the scheme is verified through simulations and experimental examination.
INTERNATIONAL JOURNAL OF FUZZY SYSTEMS
(2021)
Review
Engineering, Electrical & Electronic
Qianwen Xu et al.
Summary: In DC microgrids, advanced control technologies are necessary to address the challenges brought by constant power loads and pulsed power loads. These technologies include model predictive control, backstepping control, sliding-mode control, passivity-based control, disturbance estimation techniques, intelligent control, and nonlinear modeling approaches. Furthermore, these techniques can also be applied in other high-power applications.
IEEE JOURNAL OF EMERGING AND SELECTED TOPICS IN POWER ELECTRONICS
(2021)
Article
Engineering, Electrical & Electronic
Samira Asadi et al.
Summary: This article investigates fault detection and reconstruction in direct current microgrids with nonlinear loads. A novel robust nonlinear detector utilizing sliding mode and polytopic LPV approaches is proposed. Experimental results show the effectiveness of the proposed method in comparison to other state-of-the-art methods.
IEEE JOURNAL OF EMERGING AND SELECTED TOPICS IN POWER ELECTRONICS
(2021)
Article
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APPLIED SOFT COMPUTING
(2020)
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IEEE TRANSACTIONS ON SMART GRID
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IEEE TRANSACTIONS ON FUZZY SYSTEMS
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IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY
(2019)
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IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2019)
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IEEE TRANSACTIONS ON SMART GRID
(2018)
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(2018)
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IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2016)
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IEEE TRANSACTIONS ON CYBERNETICS
(2016)
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Mohammand Narimani et al.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2009)
