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Digital signal processor based intelligent fractional-order sliding-mode control for a linear voice coil actuator

机译:基于数字信号处理器的线性音圈执行器智能小数阶滑模控制

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摘要

In this study, a digital signal processor (DSP) based intelligent fractional-order sliding-mode control (IFOSMC) is proposed to control a linear voice coil actuator (VCA) for the tracking of reference trajectory. First, a dynamic model of the VCA is analysed considering the system uncertainties. Subsequently, a sliding-mode control (SMC) and a fractional-order SMC (FOSMC) are developed for the VCA control system. With increased degrees of freedom for the control parameters, the FOSMC can improve the control performance of the SMC. However, because the uncertainties of the VCA are unclear, designing hitting control laws for the SMC and FOSMC is difficult. Thus, the IFOSMC is proposed for improving the adaptability and robustness of the control system. For the IFOSMC, a compensatory fuzzy neural network observer is designed to replace the hitting control directly while a switching compensator is developed to compensate for the observation error smoothly. A Lyapunov method is used to derive the adaptive laws for tuning the control parameters of the IFOSMC online. Experimentations regarding nominal and parameter variation cases were undertaken through the DSP. Experimental results show that the proposed IFOSMC significantly improves the control performances of the SMC and FOSMC with regard to the VCA control system.
机译:该文提出一种基于数字信号处理器(DSP)的智能分数阶滑模控制(IFOSMC)来控制线性音圈执行器(VCA)跟踪参考轨迹。首先,考虑系统不确定性,分析了VCA的动态模型;随后,为VCA控制系统开发了滑模控制(SMC)和小阶SMC(FOSMC)。随着控制参数自由度的增加,FOSMC可以提高SMC的控制性能。然而,由于VCA的不确定性不明确,因此很难为SMC和FOSMC设计命中控制律。因此,提出了IFOSMC来提高控制系统的适应性和鲁棒性。针对IFOSMC算法,设计了一种补偿模糊神经网络观测器,直接取代了击球控制,同时开发了一种开关补偿器,以平滑地补偿观测误差。利用Lyapunov方法推导了IFOSMC控制参数的自适应规律。通过DSP进行了有关标称和参数变化情况的实验。实验结果表明,所提出的IFOSMC显著提高了SMC和FOSMC相对于VCA控制系统的控制性能。

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