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Automatic Error Correction of Position Sensors for Servo Motors via Iterative Learning
한석희,하태균,허헌,하인중,고명삼,Han, Seok-Hee,Ha, Tae-Kyoon,Huh, Heon,Ha, In-Joong,Ko, Myoung-Sam The Institute of Electronics and Information Engin 1994 전자공학회논문지-B Vol.b31 No.9
In this paper, we present an iterative learning method of compensating for position sensor error. The previously known compensation algorithms need a special perfect position sensor or a priori information about error sources, while ours does not. to our best knowledge, any iterative learning approach has not been taken for sensor error compensation. Furthermore, our iterativelearning algorithm does not have the drawbacks of the existing interativelearning control theories. To be more specivic, our algorithm learns an uncertain function itself rather than its special time-trajectory and does not reuquest the derivatives of measurement signals. Moreover, it does not require the learning system to start with the same initial condition for all iterations. To illuminate the generality and practical use of our algorithm, we give the rigorous proof for its convergence and some experimental results.
김창환(Chang-Hwan Kim),하인중(In-Joong Ha),하태균(Tae-Kyoon Ha),고명삼(Myoung-Sam Ko),김동일(Dong-Il Kim) 대한전자공학회 1992 대한전자공학회 학술대회 Vol.1992 No.10
In this paper, we present a DSP-based high dynamic performance torque control scheme of variable reluctance motors(VRM's) for DD(Direct Drive) robots via function inversion technique. The VRM with our controller behaves like DC motors, and hence developed torque tracks given torque command accurately with no torque ripples. Furthermore, our torque control algorithm ensures the production of maximum constant torque under maximum current limitation, minimizes power loss in each phase resistance, and takes magnetic saturation effect into account. Also, since our control algorithm is represented in the form of look-up table, it can be easily implemented with simple digital circuits and this tabular design method is computationally more accurate and simpler compared to the prior methods.