Motion control of an electrostrictive actuator
Electrostrictive actuator is a relatively new category of smartmaterial transducers. However, a major deficiency of electrostrictive actuator is the limitation of motion accuracy caused by inherent non-linearity and hysteresis. This paper presents a new iterative learning control algorithm to improve the positioning/tracking accuracy of an electrostrictive actuator. In this algorithm, the iterative gain is not fixed but variable according to both the previous trial result and the nominal input/output relationship of the electrostrictive actuator. The convergence to the objective position/motion is theoretically proved. The effectiveness of this algorithm is experimentally verified through actual positioning and tracking control of a stacked electrostrictive actuator. Experimental results showed that using this gain-variable iterative learning control algorithm, not only can the stability of precision positioning be dramatically improved, but also precise and non-delay tracking of motion can be rapidly achieved. (C) 2003 Elsevier Ltd. All rights reserved.
motion control electrostrictive actuator learning control algorithm