Optimal design of discrete-time fractional-order PID controller for idle speed control of an IC engine

Q3 Engineering
Yi Yang, Haiyan Zhang, Wangling Yu, Lizhe Tan
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引用次数: 12

Abstract

This paper aims at proposing a discrete-time fractional-order PID (FOPID) controller, which can stabilise the variation of the idle speed of an internal combustion engine due to the occurrence of the external load disturbance. The nonlinear idle speed dynamics is linearised to be approximated by a first order plus dead time (FOPDT) model so that the FOPID controller can be initialised by a Ziegler-Nichols type tuning rule. The initialised FOPID controller can stabilise the linearised model, but it may lose its control capability in nonlinear idle speed dynamics. Therefore, an optimisation problem is solved through genetic algorithm (GA) to minimise a cost function within a small region around the FOPID's initial parameters. The optimal discrete-time FOPID controller are compared to a conventional discrete-time PID controller. The simulation study reveals that the optimal discrete-time FOPID controller secures an excellent control performance to the nonlinear idle speed model.
内燃机怠速控制离散时间分数阶PID控制器的优化设计
本文旨在提出一种离散时间分数阶PID (FOPID)控制器,以稳定内燃机怠速因外部负载扰动而发生的变化。将非线性怠速动力学线性化,近似为一阶加死区时间(FOPDT)模型,使FOPID控制器可以通过齐格勒-尼科尔斯型调谐规则初始化。初始化的FOPID控制器可以稳定线性化模型,但在非线性怠速动力学中可能失去控制能力。因此,通过遗传算法(GA)在FOPID初始参数周围的小区域内最小化代价函数来解决优化问题。将最优离散时间FOPID控制器与传统离散时间PID控制器进行了比较。仿真研究表明,最优离散FOPID控制器对非线性怠速模型具有良好的控制性能。
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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来源期刊
International Journal of Powertrains
International Journal of Powertrains Engineering-Automotive Engineering
CiteScore
1.20
自引率
0.00%
发文量
25
期刊介绍: IJPT addresses novel scientific/technological results contributing to advancing powertrain technology, from components/subsystems to system integration/controls. Focus is primarily but not exclusively on ground vehicle applications. IJPT''s perspective is largely inspired by the fact that many innovations in powertrain advancement are only possible due to synergies between mechanical design, mechanisms, mechatronics, controls, networking system integration, etc. The science behind these is characterised by physical phenomena across the range of physics (multiphysics) and scale of motion (multiscale) governing the behaviour of components/subsystems.
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