将自适应局部搜索和基于经验的扰动学习纳入人工兔子优化器,改善直流电机调速性能

IF 5 2区 工程技术 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC International Journal of Electrical Power & Energy Systems Pub Date : 2024-10-19 DOI:10.1016/j.ijepes.2024.110266
Rizk M. Rizk-Allah , Davut Izci , Serdar Ekinci , Ali Diabat , Absalom E. Ezugwu , Laith Abualigah
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引用次数: 0

摘要

直流(DC)电机在实际工程应用中的广泛使用导致了对精确速度控制的需求,从而使控制器成为直流电机系统的一个重要方面。比例积分派生(PID)控制器因其简单有效而被广泛采用。然而,最近的发展引入了分数阶 PID(FOPID)控制器,为具有非线性动态特性的复杂系统提供了更好的控制性能。要充分发挥 FOPID 控制器的优势,高效的调节方法必不可少。在本研究中,我们提出了具有增强策略的人工兔子优化(ARO)算法,称为 IARO,用于优化直流电机调速的 FOPID 控制器。IARO 算法结合了自适应局部搜索(ALS)机制和基于经验的扰动学习(EPL)策略,解决了 ARO 算法的不足,并提供了更好的探索-开发平衡。我们在 CEC2020 基准函数上验证了 IARO 相对于竞争算法的优越性,展示了解决方案稳定性和一致性的提高。然后,我们将 IARO 算法应用于调整直流电机速度调节的 FOPID 控制器。该问题被表述为一个约束最小化任务,在遵守关键设计要求的同时优化时间加权绝对误差成本函数的积分。比较仿真证明,与其他基于算法的 FOPID 控制器相比,IARO 算法能够获得更优越的成本函数值和更快的收敛速度。与其他已报道的算法相比,基于 IARO 的 FOPID 控制器具有更高的稳定性、更平滑的速度响应、更大的增益余量和更宽的带宽。此外,为了进一步验证基于 IARO 的设计方法的实用性,还进行了硬件实施。基于 IARO 的 FOPID 控制器在跟踪多步参考输入方面表现出了卓越的准确性,并能稳健地拒绝外部干扰,优于其他最新的基于优化的控制器。此外,基于 IARO 的 PID 控制器在关键时域指标方面也取得了更好的性能,包括更低的过冲、更快的上升时间、更短的平稳时间和最小化的峰值时间。
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Incorporating adaptive local search and experience-based perturbed learning into artificial rabbits optimizer for improved DC motor speed regulation
The widespread utilization of direct current (DC) motors in real-life engineering applications has led to the need for precise speed control, making controllers a crucial aspect of DC motor systems. Proportional-integral-derivative (PID) controllers have been widely adopted due to their simplicity and effectiveness. However, recent advancements have introduced fractional order PID (FOPID) controllers that offer improved control performance for complex systems with nonlinear dynamics. To fully leverage FOPID controller’s benefits, an efficient tuning method is essential. In this study, we propose artificial rabbits optimization (ARO) algorithm with enhanced strategies, called IARO, to optimize the FOPID controller for DC motor speed regulation. The IARO algorithm incorporates an adaptive local search (ALS) mechanism and an experience-based perturbed learning (EPL) strategy, addressing the shortcomings of ARO and providing better exploration–exploitation balance. We validate the superiority of IARO over competitive algorithms on the CEC2020 benchmark functions, showcasing improved solution stability and consistency. The IARO algorithm is then applied to tune the FOPID controller for DC motor speed regulation. The problem is formulated as a constraint minimization task, optimizing the integral of time-weighted absolute error cost function while adhering to critical design requirements. Comparative simulations demonstrate the IARO algorithm’s ability to achieve superior cost function values and faster convergence compared to other algorithms' based FOPID controllers. The IARO-based FOPID controller exhibits enhanced stability, smoother speed response, larger gain margin, and wider bandwidth compared to other reported algorithms. Additionally, a hardware implementation is also conducted to further validate the practical applicability of IARO based design method. The IARO-based FOPID controller showed remarkable accuracy in tracking multi-step reference inputs and robustly rejected external disturbances, outperforming other recent optimization-based controllers. Additionally, the IARO-based PID controller achieved better performance in key time-domain metrics, including lower overshoot, faster rise time, shorter settling time, and minimized peak time.
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来源期刊
International Journal of Electrical Power & Energy Systems
International Journal of Electrical Power & Energy Systems 工程技术-工程:电子与电气
CiteScore
12.10
自引率
17.30%
发文量
1022
审稿时长
51 days
期刊介绍: The journal covers theoretical developments in electrical power and energy systems and their applications. The coverage embraces: generation and network planning; reliability; long and short term operation; expert systems; neural networks; object oriented systems; system control centres; database and information systems; stock and parameter estimation; system security and adequacy; network theory, modelling and computation; small and large system dynamics; dynamic model identification; on-line control including load and switching control; protection; distribution systems; energy economics; impact of non-conventional systems; and man-machine interfaces. As well as original research papers, the journal publishes short contributions, book reviews and conference reports. All papers are peer-reviewed by at least two referees.
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