The Application Research Of Active Vehicle Pipe Noise Control Based On Genetic Algorithm

Recently, with the advent of high-performance DSP chips and related digital signal processing technology matures, adaptive active noise control technology has achieved rapid development and fruitful results in various fields. Currently, most control algorithm of systems are designed on the basis of linear adaptive filter theory in the field of adaptive active control, these linear algorithms have many advantages, such as simple structure, low computational complexity and easy to implement etc., for example the FxLMS algorithm. However, nonlinear problems will inevitably encounter in actual control, if we use the linear algorithm to deal with the problems now, the system will not be effective for noise reduction, therefore, we need use nonlinear algorithm for processing.Genetic algorithm is a random search algorithm for dealing with complex systems issues which is designed by simulating the mechanism of “survival of the fittest” during the biological evolution. It is very suitable for dealing with complex nonlinear problems in active noise control because of not depending on the gradient and having excellent parallel search ability and adaptability in the process of optimization calculation.This paper will use the standard genetic algorithm and improved algorithm as the control algorithm of system to deal with the nonlinear path problems of the engine exhaust duct active noise control system. It designed the single channel feedforward adaptive active noise control system based on based on FxLMS algorithm, genetic algorithm, multi-population genetic algorithms and genetic-BP neural network algorithm by analyzing and researching engine exhaust pipe sound field characteristics, active control theory, genetic algorithms and other related control theory. It establish the system simulation model using MATLAB/Simulink software to comparative analyzing the noise reduction ability, convergence speed and system stability of each algorithm in the pathways linear correlation and nonlinear correlation and researching the related control parameters which affect the noise reduction performance. The system hardware and software was designed, debugged and carried out on the core DSP chip TMS320F28335.Finally, this paper summarizes all the work, points out that the innovations and shortcomings, and scans future research, provides a certain theoretical basis and reference for the application of genetic algorithm in adaptive active noise control and the actual development of the system.