Özbek Necdet Sinan, Eker İlyas
Department of Electrical & Electronics Engineering, Faculty of Engineering, Adana Alparslan Türkeş Science and Technology University, Adana, Turkey; Department of Electrical & Electronics Engineering, Faculty of Engineering, Çukurova University, Adana, Turkey.
Department of Electrical & Electronics Engineering, Faculty of Engineering, Çukurova University, Adana, Turkey.
ISA Trans. 2020 Feb;97:14-35. doi: 10.1016/j.isatra.2019.08.009. Epub 2019 Aug 7.
This study addresses an experimental investigation of a novel modified Smith Predictor (SP) based fractional fuzzy gain-scheduled control scheme in control of a time-delayed thermal process. The control strategy employees a fuzzy algorithm to adjust convenient controller parameters based on the system's operating conditions. Performance enhancement of the closed-loop system enables more robust behavior in the presence of disturbance while reducing energy consumption by producing a smooth control signal in comparison with the traditional integer order SP structures. The proposed controller comprises self-tuning capabilities at runtime which makes it adaptive in nature. The motivation of the present paper is in both points of theory and experimental application. The theoretical contribution is to propose a new Smith Predictor based fractional order fuzzy dead-time compensation scheme that can handle uncertainties, parameter variations, and internal/external disturbances. The practical contribution is to apply the proposed control scheme to a real-time air-heating process. The performances of the elaborated control strategies are investigated in both computer simulation and experimental application under different operating conditions. The proposed fractional fuzzy control scheme is found superior to the classical PI-PD SP and integer fuzzy controllers for temperature profile tracking tasks. Moreover, complementary comments are highlighted on the advantages and drawbacks of each controller.
本研究针对一种基于新型改进型史密斯预估器（SP）的分数阶模糊增益调度控制方案在时滞热过程控制中的应用进行了实验研究。该控制策略采用模糊算法，根据系统运行条件调整合适的控制器参数。与传统整数阶SP结构相比，闭环系统性能的提升使其在存在干扰时具有更强的鲁棒性，同时通过产生平滑的控制信号降低了能耗。所提出的控制器具有运行时的自整定能力，本质上具有自适应特性。本文的动机在于理论和实验应用两个方面。理论贡献在于提出了一种基于史密斯预估器的新型分数阶模糊死区时间补偿方案，该方案能够处理不确定性、参数变化以及内部/外部干扰。实际贡献在于将所提出的控制方案应用于实时空气加热过程。在不同运行条件下，通过计算机仿真和实验应用研究了详细控制策略的性能。结果表明，所提出的分数阶模糊控制方案在温度曲线跟踪任务中优于经典的PI-PD SP和整数模糊控制器。此外，还着重阐述了每个控制器的优缺点。
