We present a new method for mismatch analysis and automatic yield optimization of analog integrated circuits with respect to global, local and operational tolerances. Effectiveness and efficiency of yield estimation and optimization are guaranteed by consideration of feasibility regions and by performance linearization at worst-case points. The proposed methods were successfully applied to two example circuits for an industrial fabrication process.

In this paper, a new method for analog circuit sizing with respect to manufacturing and operating tolerances is presented. Two types of robustness objectives are presented, i.e. parameter distances for the nominal design and worstcase distances for the design centering. Moreover, the generalized boundary curve is presented as a method to determine a parameter correction within an iterative trust region algorithm. Results show that a significant reduction in computational costs is achieved using the presented robustness objectives and generalized boundary curve.

In this report a method for the design centering of analog circuits, based on worstcase distances (WCD) is presented. In order to keep the linearization error small, only the WCDs and not the strongly nonlinear objective function itself is linearized. For the resulting nonlinear trust-region problem the generalized boundary curve (GBC) is derived as a method to determine a solution with a good ratio between error reduction and norm of the parameter correction. This parameter correction is used in a standard iterative trust-region optimization algorithm. Results calculated on a circuit example show a signifcant reduction of iterations compared to a standard gradient-based optimization algorithm. Thus, design centering becomes applicable within industrial analog circuit design.