遗传算法在故障安全控制系统多故障中的应用

Genetic Design of Multivariable Fail-safe Control System

着重于故障安全控制系统在单个以及多个调节器故障情况下,使系统仍然保持稳定以及拥有良好的系统性能。因此,多变量故障安全控制系统是设计重点。进化计算技术(Evolutionary Computing Techniques)改变了控制系统设计原理。相比使用传统的办法比如伪逆(Pseudo inverse)设计方案,进化算法(Evolutionally Algorithm)能更好的优化设计系统,其用成本函数(Cost Function)和最优化(Optimization)进化出结果。在进化算法里,有多种系统性能指标优化系统性能,比如积分平方差算子(Integral Squared Error Operator)就用作成本函数来设计控制器。本文着重运用遗传算法优化这种控制系统的控制器,使这种控制系统的性能随运算时间的增加而变好。

In this thesis the design of multivariable fail-safe control under single and multiple failures are considered, the goal of this thesis is making sure the fail-safe control system remain stable and optimal performance simultaneously. The invention of evolutionary computing techniques has changed the design philosophy for control system design. Such algorithms evolve solutions using cost functions and optimization. There are a variety of system performance indicators such as integral squared error operator has been used as cost functions to design controllers using such algorithms. Therefore, the main objective of this thesis is to use the genetic algorithms to involve fail-safe multivariable controllers, such that they perform well in the time-domain.