自动巡航控制系统模糊逼近PI控制器的设计与实现

P. Maji, S. K. Patra, K. Mahapatra
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引用次数: 1

摘要

模糊逻辑系统已被广泛应用于利用启发式知识来控制非线性和复杂的动态系统。但这些系统计算复杂,资源密集。提出了一种用于自动巡航控制系统的模糊逻辑逼近PID控制器(FLAC)的开发与移植技术。ACC是一个高度非线性过程,由于参数变化大,控制难度大。因此,基于启发式知识的合适的控制器将易于开发并提供有效的解决方案。但采用模糊控制器(FLC)的主要问题是其复杂性。此外,规则库的设计需要关于系统的有效启发式知识,而这种知识很少能找到。因此,本文采用了一种新的规则提取方法来推导FLAC。然后将该控制器移植到具有时序和内存优化的C6748 DSP硬件上。之后,它被无缝连接到网络,以支持远程可重构性。利用Simulink模型对某型汽车巡航控制系统进行了处理器在环测试,并进行了性能分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Design and Implementation of Fuzzy Approximation PI Controller for Automatic Cruise Control System
Fuzzy logic systems have been widely used for controlling nonlinear and complex dynamic systems by programming heuristic knowledge. But these systems are computationally complex and resource intensive. This paper presents a technique of development and porting of a fuzzy logic approximation PID controller (FLAC) in an automatic cruise control (ACC) system. ACC is a highly nonlinear process and its control is trivial due to the large change in parameters. Therefore, a suitable controller based on heuristic knowledge will be easy to develop and provide an effective solution. But the major problem with employing fuzzy logic controller (FLC) is its complexity. Moreover, the designing of Rulebase requires efficient heuristic knowledge about the system which is rarely found. Therefore, in this paper, a novel rule extraction process is used to derive a FLAC. This controller is then ported on a C6748 DSP hardware with timing and memory optimization. Later, it is seamlessly connected to a network to support remote reconfigurability. A performance analysis is drawn based on processor-in loop test with Simulink model of a cruise control system for vehicle.
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