Genetic fuzzy system for servo motors with a buck converter

Lee, Cheng-Lin; Leu, Yih-Guang; Lin, Jheng-Yi; Yang, Hao-Cheng; Wang, Wei-Yen

doi:10.1109/icsmc.2011.6084018

Cited by 1 publication

(1 citation statement)

References 24 publications

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“…In the model-free control strategies, proportional-integral-differential (PID) control has serious hysteresis that is unbeneficial to the stability of the system (Gao, 2006a). Adaptive control (Na et al , 2013), neural networks (NNS) (Fukuda and Shibata, 1992), fuzzy systems (Lee et al , 2011) and their combination (Abbasimoshaei et al , 2020; Abbasi Moshaii et al , 2019) have heavy computational burden; hence, they are not suitable for real-time control (Na et al , 2013; Wang et al , 2019; Lin and Wai, 2001). To reduce the response time and the computational burden, Extended-State-Observer (ESO) was first proposed as the core of active disturbance rejection control (ADRC) (Han, 2009).…”

Section: Introductionmentioning

confidence: 99%

Linear-extended-state-observer-based prescribed performance control for trajectory tracking of a robotic manipulator

Zhang

et al. 2021

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Purpose Trajectory tracking error of robotic manipulator has limited its applications in trajectory tracking control systems. This paper aims to improve the trajectory tracking accuracy of robotic manipulator, so a linear-extended-state-observer (LESO)-based prescribed performance controller is proposed. Design/methodology/approach A prescribed performance function with the convergence rate, maximum overshoot and steady-state error is derived for the output error transformation, whose stability can guarantee trajectory tracking accuracy of the original robotic system. A LESO is designed to estimate and eliminate the total disturbance, which neither requires a detailed system model nor a heavy computation load. The stability of the system is proved via the Lyapunov theory. Findings Comparative experimental results show that the proposed controller can achieve better trajectory tracking accuracy than proportional-integral-differential control and linear active disturbance rejection control. Originality/value In the LESO-based prescribed performance control (PPC), the LESO was incorporated into the PPC design, it solved the problem of stabilizing the complex transformed system and avoided the costly offline identification of dynamic model and estimated and eliminated the total disturbance in real-time with light computational burden. LESO-based PPC further improved control accuracy on the basis of linear-active-disturbance-rejection-control. The new proposed method can reduce the trajectory tracking error of the robotic manipulators effectively on the basis of simplicity and stability.

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Section: Introductionmentioning

confidence: 99%

Linear-extended-state-observer-based prescribed performance control for trajectory tracking of a robotic manipulator

Zhang

et al. 2021

View full text Add to dashboard Cite

show abstract

Genetic fuzzy system for servo motors with a buck converter

Cited by 1 publication

References 24 publications

Linear-extended-state-observer-based prescribed performance control for trajectory tracking of a robotic manipulator

Linear-extended-state-observer-based prescribed performance control for trajectory tracking of a robotic manipulator

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