Article
Automation & Control Systems
Guoliang Zhao, Degang Wang
Summary: In this paper, a non-uniform sampling method is introduced for tensor product model transformation to consider local extrema, allowing for nearly exact sampling of the system. This adaptive approach improves the performance of the PDC controller and achieves the best results.
ASIAN JOURNAL OF CONTROL
(2021)
Article
Computer Science, Artificial Intelligence
Kehua Yuan, Wentao Li, Weihua Xu, Tao Zhan, Libo Zhang, Shuai Liu
Summary: The study conducted a numerical evaluation of the performance of type-1 and type-2 fuzzy models in terms of accuracy and computing overhead, revealing trade-offs between the two. The experiments on 15 publicly available datasets showed that type-2 fuzzy models outperformed type-1 models in accuracy and development time.
INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS
(2021)
Article
Computer Science, Theory & Methods
Jiri Mockor
Summary: New notions of relational, closure, or partition powerset theories in categories are introduced, generalizing classical constructions in powerset objects of all subsets or fuzzy sets on a given set. These new types of powerset theories are defined as categories whose objects have defined structures on the original powerset objects. Examples of these new powerset objects are also provided.
FUZZY SETS AND SYSTEMS
(2021)
Article
Automation & Control Systems
Jiabao He, Feng Xu, Xueqian Wang, Bin Liang
Summary: This paper presents several methods to improve the stabilization conditions of Takagi-Sugeno fuzzy descriptor systems (TSFDS). Firstly, by introducing a modified non-quadratic fuzzy Lyapunov function and a PDC controller, the stabilization problems of TSFDS are reformulated as checking negativity of triple fuzzy summations, allowing the relaxed methods of T-S fuzzy systems to be directly applied to descriptor systems. Secondly, a non-quadratic fuzzy Lyapunov function is designed that combines membership functions of derivative matrices and state matrices, and both sufficient and asymptotically necessary conditions for TSFDS are presented using a non-PDC controller based on Polya's theorem. All conditions are formulated as LMIs, and simulation examples demonstrate the improvements and effectiveness of these methods.
Article
Computer Science, Artificial Intelligence
Yuhan Luo, Minna Ni, Feng Zhang
Summary: This paper proposes an interval-valued Pythagorean fuzzy set-based FBS model integrating AHP and HOQ methods to improve the accuracy of user requirements in the product design process. The feasibility and effectiveness of the proposed method are demonstrated through an application example. The results show that the proposed FBS model can effectively reduce subjectivity and ambiguity, improve the accuracy and information richness of user requirements, and highlight the design focus.
ADVANCED ENGINEERING INFORMATICS
(2023)
Article
Automation & Control Systems
Ihsan Kaya, Esra Ilbahar, Ali Karasan
Summary: Attribute control charts (ACCs) effectively evaluate process situations by considering nonconforming items (NCIs) and defects. Traditional control charts (CCs) need adjustments to account for uncertainties caused by human evaluations, measurement errors, and process situations. The integration of fuzzy set theory (FST) into CCs has improved modeling of uncertainties, including non-membership value and hesitancy function. This paper focuses on Pythagorean fuzzy sets (PFSs), which are used in the re-designed ACCs to capture the vagueness, hesitancy, and uncertainties of human evaluations. The proposed PFS-based CCs are applied to a real case study, demonstrating their accuracy, sensitivity, and flexibility in analyzing process stability.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2023)
Article
Automation & Control Systems
Artit Visavakitcharoen, Wudhichai Assawinchaichote, Yan Shi, Chrissanthi Angeli
Summary: This manuscript proposes a fuzzy integral controller with an event-triggered strategy for a class of nonlinear continuous singularly perturbed systems. The proposed method utilizes the Takagi-Sugeno fuzzy model, integral feedback, and event-triggered mechanism to manipulate the effects of the parasitic parameter and achieves similar performance to conventional controllers with less steady-state error and fewer events. Examples of electrical engineering problems are presented to demonstrate the effectiveness of the proposed method.
Article
Chemistry, Multidisciplinary
Przemyslaw Ilczuk, Magdalena Kycko
Summary: This article presents a risk analysis method based on fuzzy sets for increasing the safety of investment processes in the railroad traffic control industry. The identified risks in CCS design were analyzed using various methods and the best solution was proposed.
APPLIED SCIENCES-BASEL
(2023)
Article
Computer Science, Artificial Intelligence
Rongrong Yu, Ye-Hwa Chen, Baokun Han, Han Zhao
Summary: This article explores control design and performance enhancement for uncertain mechanical systems. A hierarchical performance requirement is considered, with the first level focusing on deterministic aspects and the second level on optimality. The proposed control design involves a tunable design parameter that can be optimized to meet both levels of performance requirements. Overall, the article accomplishes a two-level control design task by solving an optimization problem to determine the optimal design parameter.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2021)
Article
Computer Science, Information Systems
Chih-Hui Chiu, Yao-Ting Hung, Ya-Fu Peng
Summary: In this study, a dual Takagi-Sugeno (TS) fuzzy control scheme is applied to control an omnidirectional inverted pendulum (ODIP), achieving real-time control of the ODIP system and solving the coupling problem. Through methods such as fuzzy modeling and parallel distributed compensation, an effective control scheme is proposed.
Article
Mathematics
Houssem Jerbi, Mourad Kchaou, Attia Boudjemline, Mohamed Amin Regaieg, Sondes Ben Aoun, Ahmed Lakhdar Kouzou
Summary: This paper discusses the problem of reliable control design for a specific class of fuzzy descriptor systems with characteristics such as time-varying delay, sensor failure, and randomly occurred non-linearity. By introducing a new method for controller design, the performance and robustness of the system are improved.
Article
Computer Science, Artificial Intelligence
Qiao Lin, Xin Chen, Chao Chen, Jonathan M. Garibaldi
Summary: In this article, a novel quality control algorithm based on fuzzy uncertainty is proposed to quantify the quality of deep learning-based segmentation results. Test-time augmentation and Monte Carlo dropout are used to capture data and model uncertainties, and a fuzzy set is generated to describe the captured uncertainty. The fuzziness of the generated fuzzy set is used to calculate image-level segmentation uncertainty and infer the segmentation quality.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2023)
Article
Automation & Control Systems
Bela Takarics, Balint Vanek
Summary: This paper proposes a control design methodology for active flutter suppression in the aeroservoelastic (ASE) aircraft of the European project FLEXOP, aiming to stabilize aeroelastic modes robustly. The control design is based on a control-oriented linear parameter-varying (LPV) model, derived via a bottom-up modeling approach. The LPV observer-based state feedback control structure is applied with constraints on the maximal control value to avoid input saturation, and the scheduling parameters of the LPV models are split into measured and uncertain parameters for robust control design.
ASIAN JOURNAL OF CONTROL
(2021)
Article
Computer Science, Artificial Intelligence
Jing Xu, Yugang Niu, Hak-Keung Lam
Summary: This article discusses the design of a control synthesis method for singularly perturbed nonlinear systems under a nonperiodic multirate sampling mechanism, and provides guidance on the choice of maximum allowable sampling time intervals for multirate sensors. The sampled system is converted into a fuzzy singularly perturbed model, and sufficient conditions for stabilizing the multirate sampled system are derived. A linear matrix inequality-based design method is proposed, and the upper bound of the perturbation parameter is determined to compute the maximum allowable sampling time interval for fast states. The optimal match is detected for a tradeoff among stability, performance, and cost. The obtained results are demonstrated in an example system.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2023)
Article
Computer Science, Artificial Intelligence
Erliang Yao, Deyu Li, Yanhui Zhai, Chao Zhang
Summary: In this article, two novel multilabel feature selection methods are proposed from the perspective of discerning sample pairs. These methods address the issues of ineffective feature distinction and high time complexity in existing approaches for multilabel data. Experimental results demonstrate that the proposed algorithms outperform other methods in terms of performances and the running time.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2022)
