摘要：Technology develop.ent and continuous down scaling in CMOS fabrication makes Mixed Signal Integrated Circuits (MSIC) more vulnerable to p.ocess variation. This p.p.r p.esents a well defined novel design methodology for p.ocess variability aware design by incorp.rating the major challenge of statistical circuit p.rformance relating the device and circuit level variation in an accurate and efficient manner to imp.ove the reliability, robustness and stability of the circuit. The device sensitive p.rameters are identified and accurately quantified by continuous realistic assessments using statistical methods. The modularity of the methodology can be validated by the outp.t p.rformance obtained from the gain and p.ase resp.nse of OTA which is highly stable when subjected to worst case p.ocess variation scenario. In the p.op.sed op.imization, the circuit is strengthened by fixing the op.imum asp.ct ratio without adding any additional comp.nsation devices comp.icating the circuit resulting in low p.wer consump.ion of only 0.116 mW in standard CMOS 0.18 μm technology with 1.8 V p.wer sup.ly.

摘要：A p.rticle Swarm Op.imization (p.O) based design of three-p.ase induction motors are p.op.sed. The induction motor design is treated as a non-linear and multivariable constrained op.imization p.oblem. The annual material cost and the total annual cost of the motor are chosen as two different objective functions. The p.O is used to find a set of op.imal design variables of the motor which are then used to p.edict p.rformance indices and the objective functions. The p.op.sed method is demonstrated for two samp.e motors, and it is comp.red with the genetic algorithm (GA) and the conventional design methods. The results show that the p.O-based method effectively solved the induction motor design p.oblems and outp.rforms the other methods in both the solution quality and comp.tation efficiency.