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Study of the design and tuning methods of PIDudcontroller based on fuzzy logic and genetic algorithm

机译:PID ud的设计与整定方法研究模糊逻辑和遗传算法的混合控制器

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摘要

This project tries to explore the potential of using soft computing methodologies in controllers and their advantages over conventional methods. PID controller, being the most widely used controller in industrial applications, needs efficient methods to control the different parametersudof the plant. This thesis asserts that the conventional approach of PID tuning is not very efficient due to the presence of non-linearity in the system of the plant. The output of the conventional PID system has a quite high overshoot and settling time.udThe main focus of this project is to apply two specific soft-computing techniques viz. fuzzy logic and genetic algorithm to design and tuning of PID controller to get an output with better dynamic and static performance. The application of fuzzy logic to the PID controller imparts it the ability of tuning itself automatically in an on-line process while the application of genetic algorithm toudthe PID controller makes it give an optimum output by searching for the best set of solutions for the PID parameters. The project also discusses the benefits and the short-comings of both the methods. The simulation outputs are the MATLAB results obtained for a step input to a third-order plant.
机译:该项目试图探索在控制器中使用软计算方法的潜力及其相对于传统方法的优势。 PID控制器是工业应用中使用最广泛的控制器,它需要有效的方法来控制工厂的不同参数。该论文断言,由于电厂系统中存在非线性,传统的PID调节方法不是很有效。传统PID系统的输出具有相当高的过冲和建立时间。 ud该项目的主要重点是应用两种特定的软计算技术,即。采用模糊逻辑和遗传算法对PID控制器进行设计和整定,以获得具有较好动态和静态性能的输出。模糊逻辑在PID控制器上的应用赋予了它在线过程中自动调整自身的能力,而遗传算法在PID控制器上的应用则通过寻找最佳解来获得最优输出。 PID参数。该项目还讨论了这两种方法的优点和缺点。仿真输出是针对三阶工厂的步进输入获得的MATLAB结果。

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