Adaptive fuzzy control of a belt-driven precision positioning table

Because of their lower cost, higher speed, and longer travel, belt drive positioning systems are quite desirable over screw-driven systems. However, belt drive systems are inherently difficult to control due to belt flexibility, stretch, backlash, and other nonlinearities. In this paper, a composite fuzzy controller, consisting of a feedback fuzzy controller and a feedforward acceleration compensator, is introduced to control a belt drive precision positioning table. Using a linear encoder with a resolution of 0.5mum, zero final positioning error and RMS track following error of around 30mum are obtained. A self-tuning scheme based on Evolutionary Computation (EC), is. then proposed to make this controller adaptive. The Evolutionary Computation optimizes the controller gains by experimentally running the controller on the actual system with a step command. The test results of the actual system have demonstrated the effectiveness and efficiency of the proposed self-tuning technique.