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This paper investigates the problem of designing a fuzzy state feedback controller to stabilize an uncertain fuzzy system with time-varying delay. Based on Lyapunov criterion and Razumikhin theorem, some sufficient conditions are derived under which the parallel-distributed fuzzy control can stabilize the whole uncertain fuzzy time-delay system asymptotically. By Schur complement, these sufficient conditions can be easily transformed into the problem of LMIs. Furthermore, the tolerable bound of the perturbation is also obtained. A practical example based on the continuous stirred tank reactor (CSTR) model is given to illustrate the control design and its effectiveness.
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http://dx.doi.org/10.1109/tsmcb.2003.818437 | DOI Listing |
PLoS One
September 2025
Department of Maths and Computer Science, Faculty of Science, University of Kinshasa, Kinshasa, The Democratic Republic of the Congo.
Reliable and timely fault diagnosis is critical for the safe and efficient operation of industrial systems. However, conventional diagnostic methods often struggle to handle uncertainties, vague data, and interdependent multi-criteria parameters, which can lead to incomplete or inaccurate results. Existing techniques are limited in their ability to manage hierarchical decision structures and overlapping information under real-world conditions.
View Article and Find Full Text PDFJ Environ Manage
September 2025
School of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran.
Agricultural supply chains face significant challenges in achieving food security and sustainability, particularly due to climate change and waste production. Effectively managing these supply chains, especially in the context of uncertainties, is crucial for optimizing resource use and minimizing waste. This research develops a multi-objective optimization for designing a sustainable and responsive closed-loop agricultural supply chain network, focusing on jujube products under uncertain conditions.
View Article and Find Full Text PDFDisabil Rehabil Assist Technol
September 2025
Department of Education, Fuzhou University of International Studies and Trade, Fuzhou, China.
This study explores the integration of traditional Chinese "Fu" culture into the moral education system for students with disabilities across K-12 and higher education through artificial intelligence. By leveraging soft computing to handle cultural ambiguities, it constructs an adaptive educational framework that aligns students' cognitive characteristics with curriculum demands, thereby enhancing their identification with Chinese culture. Guided by the theory of the "Second Combination," the research employs AI-powered soft computing to analyze the semantic and cognitive dimensions of "Fu" culture.
View Article and Find Full Text PDFCancer Invest
September 2025
Department of Computer Science and Engineering (CS), Saveetha Engineering College, Chennai, India.
Lung cancer detection (LCD) is a process of identifying an occurrence of lung cancer (LC) or irregularities in the lungs. Early detection of lung cancer is crucial for improving patient survival and enabling effective treatment. Computed Tomography (CT) images and Positron emission tomography (PET) are employed for screening and detecting LC.
View Article and Find Full Text PDFSci Rep
September 2025
Faculty of Computers and Artificial Intelligence, Benha University, Benha, Egypt.
Citrus fruits, especially lemons, play a vital economic and nutritional role worldwide but are increasingly threatened by a wide range of diseases that diminish yield quality and quantity. Traditional manual and automated methods for disease detection requires domain expert, ample observation time, and is often ineffective during early infection stages. This paper presents a novel automated approach for the symptom based detection and classification of citrus leaf diseases using a nonlinear Fuzzy Rank-Based Ensemble (NL-FuRBE) methodology, enhanced by image quality improvement techniques.
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