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چکیده
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The research on Fuzzy Logic Control Systems (FLCs) in industrial operations is critical due to several factors that underscore its necessity and importance. Industrial processes often involve complex, non-linear systems where traditional control methods may fail. Fuzzy logic provides an effective solution by handling vague data, making it easier to manage systems characterized by uncertainty, variability, and ambiguity. This ability to handle imprecise information is essential for optimizing industrial operations. With industries increasingly relying on automation to improve productivity, the flexibility of FLCs enables the automation of processes that were previously too complex for traditional systems. This leads to more adaptive and resilient operations, particularly in areas like manufacturing and robotics. Additionally, FLCs contribute to the optimization of resource usage by dynamically adjusting system inputs and processes based on real-time data. This reduces waste, improves energy efficiency, and enhances overall operational cost-effectiveness. Fuzzy logic systems also offer greater robustness than traditional control methods. They can tolerate minor fluctuations and errors in input values, making them ideal for industries where precision and stability are essential. Lastly, many industrial systems involve multiple interacting variables. FLCs excel in managing these relationships, ensuring smooth transitions between different operational states and maintaining consistent performance across varying conditions. By addressing the inherent complexities of industrial operations, research into FLCs enhances the efficiency, reliability, and adaptability of industrial systems, making it a highly significant area of study in automation and process control.
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