基于改进灰狼算法的桥式起重机系统 II 型模糊滑模控制参数优化

Zhiqiang Sun, Zhe Sun, Xiangpeng Xie, Zhixin Sun
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引用次数: 0

摘要

桥式起重机是一种复杂的非线性动态系统,具有驱动不足的特点,这使得控制器难以有效控制负载的空间摆动。此外,系统内外的不确定性也会对控制性能产生不利影响。为解决这些问题,II 类模糊滑动模式控制器已被证明能有效提高有效载荷的防摆动控制性能。然而,由于参数调整优化问题错综复杂,而且在处理非线性和不确定性方面存在潜在挑战,特别是在复杂的动态系统中,本文提出了一种基于动态螺旋狩猎机制的灰狼算法。这种改进赋予了算法更快的收敛速度和更高的鲁棒性,使二阶分数阶滑动模态控制器(FSMC)的参数调整更加有效。通过测试和比较,所提出的算法展示了卓越的收敛速度和求解精度性能。最后,在桥式起重机系统的两种条件下进行的仿真验证验证了所提方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Parameter optimization of type II fuzzy sliding mode control for bridge crane systems based on improved grey wolf algorithm
Bridge cranes are complex nonlinear dynamic systems with underactuated characteristics, making it challenging for controllers to man age the spatial swing of the load effectively. Additionally, uncertainties both within and outside the system adversely impact control performance. To address these issues, a Type‐II fuzzy sliding mode controller has proven effective in enhancing the anti‐swing control performance of the payload. However, due to the intricate parameter adjustment optimization problem and potential challenges in dealing with nonlinearity and uncertainty, especially in complex dynamic systems, this paper proposes a grey wolf algorithm based on a dynamic spiral hunting mechanism. This enhancement endows the algorithm with improved convergence speed and higher robustness, enabling more effective parameter tuning for the second‐order fractional‐order sliding mode controller (FSMC). The proposed algorithm demonstrates superior convergence speed and solution accuracy performance through testing and comparison. Finally, simulation verification under two conditions of the bridge crane system validates the effectiveness of the proposed approach.
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