Pseudocoevolutionary genetic algorithms for power electronic circuits optimization

This correspondence presents pseudocoevolutionary genetic algorithms (GAs) for power electronic circuit (PEC) optimization. Circuit parameters are optimized through two parallel coadapted GA-based optimization processes for the power conversion stage (PCS) and feedback network (FN), respectively. Each process has tunable and untunable parametric vectors. The best candidate of the tunable vector in one process is migrated into the other process as an untunable vector through a migration controller, in which the migration strategy is adaptively controlled by a first-order projection of the maximum and minimum bounds of the fitness value in each generation. Implementation of this method is suitable for systems with parallel computation capacity, resulting in considerable improvement of the training speed. Optimization of a buck regulator for meeting requirements under large-signal changes and at steady state is illustrated. Simulation predictions are verified with experimental results

[1]  R.D. Middlebrook,et al.  Low-Frequency Characterization of Switched dc-dc Converters , 1972, IEEE Transactions on Aerospace and Electronic Systems.

[2]  M. Clique,et al.  A General Model for Switching Converters , 1977, IEEE Transactions on Aerospace and Electronic Systems.

[3]  R.D. Middlebrook,et al.  Modelling and analysis of switching DC-to-DC converters in constant-frequency current-programmed mode , 1979, 1979 IEEE Power Electronics Specialists Conference.

[4]  P.R.K. Chetty,et al.  Current Injected Equivalent Circuit Approach to Modeling Switching DC-DC Converters , 1981, IEEE Transactions on Aerospace and Electronic Systems.

[5]  Malik E. Elbuluk,et al.  A General Approach to Sampled-Data Modeling for Power Electronic Circuits , 1986, IEEE Transactions on Power Electronics.

[6]  A General Approach to Sampled-Data Modeling for Power Electronic Circuits , 1986, IEEE Transactions on Power Electronics.

[7]  G. Verghese,et al.  Averaged and sampled-data models for current mode control: a re-examination , 1989, 20th Annual IEEE Power Electronics Specialists Conference.

[8]  R. D. Middlebrook,et al.  Modeling current-programmed buck and boost regulators , 1989 .

[9]  M. Zarudi,et al.  Analysis of common switching converters using Z transform , 1993 .

[10]  Michael de la Maza,et al.  Book review: Genetic Algorithms + Data Structures = Evolution Programs by Zbigniew Michalewicz (Springer-Verlag, 1992) , 1993 .

[11]  A. S. Kislovski.  On the role of physical insight in small signal analysis of switching power converters , 1993, Proceedings Eighth Annual Applied Power Electronics Conference and Exposition,.

[12]  Kenneth A. De Jong,et al.  A Cooperative Coevolutionary Approach to Function Optimization , 1994, PPSN.

[13]  M. Bialko,et al.  System for optimisation of electronic circuits using genetic algorithm , 1996, Proceedings of Third International Conference on Electronics, Circuits, and Systems.

[14]  C. Q. Lee,et al.  Generalized state-space averaging approach for a class of periodically switched networks , 1997 .

[15]  Henry Shu-Hung Chung,et al.  Steady-state analysis of PWM DC/DC switching regulators using iterative cycle time-domain simulation , 1998, IEEE Trans. Ind. Electron..

[16]  Vassilios Petridis,et al.  Varying fitness functions in genetic algorithm constrained optimization: the cutting stock and unit commitment problems , 1998, IEEE Trans. Syst. Man Cybern. Part B.

[17]  Ranga Vemuri,et al.  A genetic approach to simultaneous parameter space exploration and constraint transformation in analog synthesis , 1999, ISCAS'99. Proceedings of the 1999 IEEE International Symposium on Circuits and Systems VLSI (Cat. No.99CH36349).

[18]  Kenneth A. De Jong,et al.  Cooperative Coevolution: An Architecture for Evolving Coadapted Subcomponents , 2000, Evolutionary Computation.

[19]  Erick Cantú-Paz,et al.  A Survey of Parallel Genetic Algorithms , 2000 .

[20]  Jun Zhang,et al.  Implementation of a decoupled optimization technique for design of switching regulators using genetic algorithms , 2001 .