基于人工免疫算法的优化在非线性系统PID控制器整定中的应用

IF 1.3 Q4 AUTOMATION & CONTROL SYSTEMS

International Journal of Automation and Control Pub Date : 2015-08-04 DOI:10.1504/IJAAC.2015.070955

M. Sahraoui, M. Khelfi, Mohammed Salem

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引用次数: 4

摘要

本文介绍了一种新发展的进化算法。本文提出了一种新的非线性系统PID控制器的整定方法，该方法采用人工免疫算法(AIA)对PID参数进行优化。这个算法的灵感来自于免疫系统对身体有害疾病和感染的防御。本文介绍了应用基于两个适应度函数的AIA技术对经典PID控制器的三项进行最优整定，以实现对非线性过程的控制。在一个质量-弹簧阻尼器系统上对该算法进行了仿真。仿真结果表明，遗传AIA是一种有效的PID控制器参数优化方法。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Application of artificial immune algorithm-based optimisation in tuning a PID controller for nonlinear systems

This paper is dedicated to present one of newly developed evolutionary algorithm. We consider a new way to tune the PID controller of nonlinear systems where the parameters of PID are optimised using the optimisation method called artificial immune algorithm (AIA). This algorithm is inspired from the immune system defends to the body against harmful diseases and infections. This paper describes the application of AIA technique based on two fitness function to optimally tune the three terms of the classical PID controller, to control a nonlinear process. Simulations of the proposed algorithm are carried out over a mass-spring damper system. The results of simulation indicate that the genetic AIA is an effective method for parameter optimisation of PID controllers.

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来源期刊

International Journal of Automation and Control AUTOMATION & CONTROL SYSTEMS-

自引率

41.70%

发文量

期刊介绍： IJAAC addresses the evolution and realisation of the theory, algorithms, techniques, schemes and tools for any kind of automation and control platforms including macro, micro and nano scale machineries and systems, with emphasis on implications that state-of-the-art technology choices have on both the feasibility and practicability of the intended applications. This perspective acknowledges the complexity of the automation, instrumentation and process control methods and delineates itself as an interface between the theory and practice existing in parallel over diverse spheres. Topics covered include: -Control theory and practice- Identification and modelling- Mechatronics- Application of soft computing- Real-time issues- Distributed control and remote monitoring- System integration- Fault detection and isolation (FDI)- Virtual instrumentation and control- Fieldbus technology and interfaces- Agriculture, environment, health applications- Industry, military, space applications