Lyapunov-Based Adaptive Control for the Permanent Magnet Synchronous Motor Driving a Robotic Load

2017 ◽  
Vol 26 (11) ◽  
pp. 1750168 ◽  
Author(s):  
Javier Moreno-Valenzuela ◽  
Yajaira Quevedo-Pillado ◽  
Regino Pérez-Aboytes ◽  
Luis González-Hernández

This paper is inspired on the structure of the field-oriented control by presenting an analytical and practical study of an adaptive nested controller for trajectory tracking control of a permanent magnet synchronous motor (PMSM) driving a single-link arm. The originality of the new approach relies in the use of adaptive control to compensate the electrical and mechanical dynamics and in the presentation of a rigorous closed-loop system stability analysis based on Lyapunov theory. It is worthwhile to notice that the new controller resembles the pure field-oriented control except for the adaptive terms. The new scheme is compared with other methodologies as with the classical nonadaptive field-oriented control algorithm and with an adaptive controller proposed in the literature. A better tracking accuracy is obtained with the proposed adaptive scheme.

2011 ◽  
Vol 268-270 ◽  
pp. 509-512 ◽  
Author(s):  
Zhi Yong Qu ◽  
Zheng Mao Ye

Permanent magnet synchronous motor systems are usually used in industry. This kind of systems is nonlinear in nature and generally difficult to control. The ordinary linear constant gain controller will cause overshoot or even loss of system stability. Application of adaptive controller to a permanent magnet synchronous motor system is investigated in this paper. The dynamic model of the system is given and the stability is also analyzed using Popov's criterion. The steady state error can be eliminated using adaptive controller combined with an integration term. Simulation results show the performance of adaptive controller with fast response and less overshoot.


2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Hongchang Ding ◽  
Xiaobin Gong ◽  
Yuchun Gong

For high-speed permanent magnet synchronous motor (PMSM), its efficiency is significantly affected by the performance of permanent magnets (PMs), and the phenomenon of demagnetization will occur with the increase of PM temperature. So, the temperature detection of PMs in rotor is very necessary for the safe operation of PMSM, and direct detection is difficult due to the rotation of rotor. Based on the relationship between permanent magnet flux linkage and its temperature, in this paper, a new temperature estimation method using model reference fuzzy adaptive control (MRFAC) is proposed to estimate PM temperature. In this method, the model reference adaptive system (MRAS) is built to estimate the permanent magnet flux linkage, and the fuzzy control method is introduced into MRAS, which is used to improve the accuracy and applicable speed range of parameters estimated by MRAS. Different permanent magnet flux linkages are estimated in MRFAC based on the variation of stator resistance, which corresponds to different working temperatures measured by thermal resistance, and the PM temperature will be obtained according to the estimated permanent magnet flux linkage. At last, the back electromotive force (BEMF) is measured on the experimental motor, and the flux linkage and PM temperature of the experimental motor are deduced according to the BEMF. Compared with the experimental results, the estimated PM temperature is very close to the actual test value, and the error is less than 5%, which verifies that the proposed method is suitable for the estimation of PM temperature.


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