The performance of adaptive systems that consist of microscale on-chip elements [microelectromechanical mirror (µ-mirror) arrays and a VLSI stochastic gradient descent microelectronic control system] is analyzed. The µ-mirror arrays with 5 × 5 and 6 × 6 actuators were driven with a control system composed of two mixed-mode VLSI chips implementing model-free beam-quality metric optimization by the stochastic parallel perturbative gradient descent technique. The adaptation rate achieved was near 6000 iterations/s. A secondary (learning) feedback loop was used to control system parameters during the adaptation process, further increasing the adaptation rate.