A novel grey decision-DE optimized internal model controller for vibration control of nonlinear uncertain aeroelastic blade system. (December 2020)

• Record Type: Journal Article
• Authors: Li, Nailu; Yang, Hua; Zhu, Weijun; Liu, Chao
• Is Part Of: ISA transactions. Volume 107(2021)
• Page Start: 27
• Page End: 39
• Publication Date: 2020-12
• Subjects: Vibration control -- Aeroelastic blade system -- Differential evolution -- Grey decision -- Internal model control; Engineering instruments -- Periodicals; Engineering instruments; Periodicals; Electronic journals; 629.805
• DOI: 10.1016/j.isatra.2020.07.036
• Languages: English
• ISSNs: 0019-0578

Abstract

Abstract: In this paper, a novel grey decision-differential evolution (GD-DE) optimized internal model controller is proposed for the control of nonlinear aeroelastic blade system (ABS) under time-varying uncertainties and control saturations. Two-port internal model control structure is presented for saturation compensation. The filter parameter of the controller is optimally tuned by proposed GD-DE algorithm, which is designed based on the grey decision incidence theory and differential evolution algorithm. The superiority of GD-DE optimized tuning technique is verified, compared to conventional IMC tuning method and other evolutionary algorithm based techniques. The robustness is analysed by comprehensive simulations from time-invariant uncertainties to large periodic or random time-varying uncertainties. The realistic condition with input/output disturbances is also involved. Simulation results show that the proposed controller outperforms existing adaptive IMC controller and other advanced controllers with greatly improved dynamic performance, stronger robustness and better saturation compensation on various conditions. Highlights: Nonlinear aeroelastic blade system with large periodic/random time-varying uncertainties. Design of grey decision modified differential evolution (GD-DE) algorithm. GD-DE optimized two-port IMC vibration controller is proposed. A comparative performance analysis with conventional adaptive IMC controller.