eldo_user

Optimization
Robust Optimization Using Corners
* DRAIN CHARAC W=25U L=25U AT VBS=0.0
.INCLUDE d25x25.dat
.DC DATA=DATA_D25X25 ! DATA DRIVEN ANALYSIS
.OBJECTIVE DC LABEL=FIT_IDRAIN I(V101) ! DOUBLE DC SWEEP OPTIMIZATION
+ GOAL=DATA_D25X25(IDS) TYPVAL=1E-4
* DRAIN CHARAC W=25U L=2.5U AT VBS=0.0
.ALTER DRAIN 25X2P5 AT VBS=0
M25X25D1 101 102 0 103 NMOS W=25U L=2.5U NRS=0.12 NRD=0.12
.INCLUDE d25x2p5.dat
.DC DATA=DATA_D25X2P5
.OBJECTIVE DC LABEL=FIT_IDRAIN I(V101)
+ GOAL=DATA_D25X2P5(IDS) TYPVAL=1E-3
The parameter TYPAL has been used to globally rescale the objectives (the extracted measures
and the associated target values), such that the low current data is not dominated by others data.
Optimization Results
The optimization was performed on a 32-bit Linux machine and the results generated during the
optimization process are shown in Table 13-11:
Table 13-11. Nmos Example Results
Minimum Error Global Error Maximum Error
Length L=25U 0.0 1.1×10 −18 3.5×10 −9
Length L=2.5U 0.0 6.4×10 −17 3.0×10 −8
These values are the result of a synthetic problem. The circuit parameters were fixed, the data
was then generated, and the circuit was optimized after performing a perturbation of the initial
point. This is why the global error is so small. The residuals are almost zero. This is not the case
with realistic data where the physical measurements involve some variability in the current
curves.
Related Topics
Optimization Options
Inner and Outer Sweep Parameters
Robust Optimization Using Corners
Netlist file: aop_optim.cir
Eldo® User's Manual, 15.3 677