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.

本文提出了一种新型的灰色决策-微分进化（GD-DE）优化的内模控制器，用于时变不确定性和控制饱和状态下的非线性气动弹性叶片系统（ABS）的控制。提出了用于饱和补偿的两端口内部模型控制结构。控制器的滤波参数由提出的GD-DE算法进行了优化，该算法是基于灰色决策关联理论和微分进化算法设计的。与传统的IMC调整方法和其他基于进化算法的技术相比，GD-DE优化的调整技术具有优越性。通过从时变不确定性到较大的周期性或随机时变不确定性的全面模拟来分析鲁棒性。还涉及带有输入/输出干扰的实际条件。仿真结果表明，所提出的控制器在各种条件下的动态性能大大提高，鲁棒性更强，饱和补偿更好，优于现有的自适应IMC控制器和其他高级控制器。