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.
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