A TRACKING ROBUST LEARNING CONTROL FOR MICRO SCALE
ACTUATOR SYSTEMS
الباحث الأول:
Ali Al-Ghanimi1,
الباحثين الآخرين:
Abdal-Razak Shehab1, Adnan Alamili1
المجلة:
International Journal of Mechatronics and Applied Mechanics, 2021, Issue 10, Vol. I
تاريخ النشر:
None
مختصر البحث:
Abstract: In this paper, a robust sliding mode-based learning control (RSMLC) scheme is developed
for a micro-scale actuator (MSA) system. By exploiting the instantaneous information of the system
closed-loop stability, a sliding mode controller b…
Abstract: In this paper, a robust sliding mode-based learning control (RSMLC) scheme is developed
for a micro-scale actuator (MSA) system. By exploiting the instantaneous information of the system
closed-loop stability, a sliding mode controller based on the recursive learning technique is
designed. The proposed control approach can govern the sliding variable and tracking error
between the desired references and actual displacement of the MSA to asymptotically converge to
zero. Unlike conventional sliding mode control (CSMC), no prior knowledge of MSA system
uncertainties and parameters variation is required in the RSMLC design. Besides, there is no
explicit switching element in the RSMLC structure, it can be considered as a chattering free control
method. Meanwhile, the inherent high robustness property of the CSMC is fully preserved in the
proposed controller. Where the learning algorithm continuously adjusts the closed-loop response
based on the most recent history of closed-loop stability. Thus, the stability and convergence
analysis of the RSMLC is proved rigorously. Simulation studies have been conducted for a
piezoelectric actuator (PEA) system, as a prototype of MSA. For comparison reasons, these results
are presented correspondingly with CSMC results to demonstrate the effectiveness of the proposed
controller over the CSMC.
