The design and properties of an adaptive enhanced fuzzy sliding-mode control (AEFSMC) system for an indirect field-oriented induction motor (IM) drive to track periodic commands are addressed in this ...study. A newly designed EFSMC system, in which a translation-width idea is embedded into the FSMC, is introduced initially. Moreover, to confront the uncertainties existed in practical applications, an adaptive tuner, which is derived in the sense of the Lyapunov stability theorem, is utilized to adjust the EFSMC parameter for further assuring robust and optimal control performance. The indirect field-oriented IM drive with the AEFSMC scheme possesses the salient advantages of simple control framework, free from chattering, stable tracking control performance, and robust to uncertainties. In addition, numerical simulation and experimental results due to periodic sinusoidal commands are provided to verify the effectiveness of the proposed control strategy, and its advantages are indicated in comparison with FSMC and EFSMC systems.
Automated production systems typically comprise numerous electrical servo drives, many of which conduct positioning motions, e.g. for handling or manipulation tasks. The power electronics of modern ...multi-axis systems often comprise coupled DC-links, enabling for internal exchange of recuperative brake energy. However, the motion sequences of manipulators are often commanded at maximum dynamics for minimum time motion, neglecting possible optimization potential, e.g. available idle time, leading to inefficient energy management. A robust trajectory optimization approach based on the particle swarm algorithm and well-established path planning methods is presented for the adaption of multi-axis positioning tasks with only two parameters per axis and positioning motion during system run-time. Experimental results prove that, depending on the positioning task and chosen optimization constraints, energy demands are distinctly reduced. The approach is applicable to diverse multi-axis configurations and enables for considerable energy savings without additional hardware invest.
In this study, an adaptive fuzzy sliding-mode control (AFSMC) system with an integral-operation switching surface is adopted to control the position of an
electrical servo drive. The AFSMC system is ...comprised of a fuzzy control design and a hitting control design. In the fuzzy control design a fuzzy controller is designed to mimic a feedback linearization (FL) control law. In the hitting control design a hitting controller is designed to compensate the approximation error between the FL control law and the fuzzy controller. The tuning algorithms are derived in the sense of the Lyapunov stability theorem, thus the stability of the system can be guaranteed. Moreover, to relax the requirement for the bound of approximation error, an error estimation mechanism is investigated to observe the bound of approximation error real-time. Experimental results verify that the proposed control systems can achieve favorable tracking performance and robust with regard to parameter variations and external load disturbance.
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