User Guide

Conver
g
ence 4
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more efficient to find the approximate location of the
desired solution (perhaps by performing a number of
analyses sweeping out ranges of the parameters) before
starting the optimization process.
Conver
g
ence
When running an optimization, the PSpice Optimizer varies the
parameter values and measures the resulting performance. For
each subsequent iteration, the optimizer chooses each parameter
step to reduce the error between the design’s measured and
specified target performance.
If the optimizer finds a solution where all of the specifications
are met, then the process has converged. There are several
common reasons why the process may fail to converge:
• There is no solution to the problem as specified.
• The simulation and/or evaluations are not accurate enough
to allow the solution to be found.
• A limit on the number of simulations or elapsed time is
encountered.
• The optimizer finds a spurious numerical minimum which is
not the desired solution.
To improve convergence, consider the following techniques:
• In the second case, use more accurate measurement
techniques (possibly with the aid of help circuitry).
• In the last case, restart from a different starting point which
might lead to a different solution.
Parameter Bounds
The PSpice Optimizer performs bound-constrained
minimization. This means it will solve problems where one or