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Incremental SMC-based CNF control strategy considering magnetic ball suspension and inverted pendulum systems through cuckoo search-genetic optimization algorithm

机译:通过布谷鸟搜索-遗传优化算法考虑磁悬浮和倒立摆系统的基于SMC的增量CNF控制策略

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A kind of incremental sliding mode control (SMC) approach in connection with the well-known composite nonlinear feedback (CNF) control strategy is newly considered in this research to deal with the nonlinear magnetic ball suspension and inverted pendulum systems, as well. The incremental SMC approach is in fact proposed to handle the aforementioned underactuated systems under control, which have a lower number of actuators than degrees of freedom. Based on the outcomes of the investigation presented here, the small overshoot and short settling time of the system response are fulfilled. In fact, the proposed CNF control strategy comprises two parts: the first term assures the stability of the closed-loop nonlinear system and provides a fast convergence response. The second term reduces its overshoot. The genetic-cuckoo hybrid algorithm is designed to minimize tracking errors for the purpose of finding the most suitable sliding surface coefficients. Finally, the finite time stability for the closed-loop system is proved, theoretically.
机译:这项研究中新考虑了一种与著名的复合非线性反馈(CNF)控制策略相结合的增量滑模控制(SMC)方法,以应对非线性磁球悬挂和倒立摆系统。实际上,提出了增量SMC方法来处理在控制下的上述欠驱动系统,该系统的驱动器数量少于自由度。根据此处介绍的调查结果,可以满足较小的过冲和较短的系统响应建立时间。实际上,所提出的CNF控制策略包括两部分:第一项确保闭环非线性系统的稳定性并提供快速的收敛响应。第二项减少其过冲。遗传杜鹃混合算法旨在最大程度地减少跟踪误差,以找到最合适的滑动表面系数。最后,从理论上证明了闭环系统的有限时间稳定性。

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