High Performance Motion Tracking Control for Electronic Manufacturing

Motion control requirements in electronic manufacturing demand both higher speeds and greater precision to accommodate continuously shrinking part/feature sizes and higher densities. However, improving both performance criteria simultaneously is difficult because of resonances that are inherent to the underlying positioning systems. This paper presents an experimental study of a feedforward controller that was designed for a point-to-point motion control system on a modern and state of the art laser processing system for electronics manufacturing. We systematically apply model identification, inverse dynamics control, iterative refinement (to address modeling inaccuracies), and adaptive least mean square to achieve high speed trajectory tracking. The key innovations lie in using the identified model to generate the gradient descent used in the iterative learning control, encoding the result from the learning control in a finite impulse response filter and adapting the finite impulse response coefficients during operation using the least-mean-square update based on position, velocity, and acceleration feedforward signals. Experimental results are provided to show the efficacy of the proposed approach, a variation of which has been implemented on the production machine.