Active Noise Control in Ducts Using Genetic Algorithms

This paper addresses the problem of actively control acoustic noise in ducts through the application of genetic algorithm and genetic programming (termed GENETIC CONTROL). Genetic programming is applied to structure a control strategy and genetic algorithm to adapt the resulting model parameters in real time. For application in real time situations, a gain/delay model was finally coded in the chromosome. The software was designed to run in a parallel DSP TMS320C44 architecture managing processors communication and shared memory with high performance. A mono-processor version was developed to actively reduce acoustic noise in ducts in real time. Two important situations in the presence of acoustic feedback and in its absence through microphone confinement are analyzed in the paper. The most striking result is the convergence of the genetic programming solution structuring a functional control strategy which is exactly the gain/delay model optimized by the GA approach as anticipated by the theory and experiment. We call Genetic Control the search of a control model by genetic programming and real time adaptation by genetic algorithm.