An improved genetic algorithm (IGA) was proposed. It can optimize the proportional-integral-derivative(PID) neural network decoupling controller's connecting weight value, so that it makes the PID controller's parameser to be optimized and realizes the decoupling control of multivariate nonlinearity systems. The IGA is superior to the elementary genetic algorithm. In the PID controller's parameter optimization, the IGA uses less calculations, is more efficient, and faster in convergence. When the optimized PID controller was applied to unified chaoticsystems, good control results were obtained by simulation experimentation, so t was proved that the PID controller when applied to unified chaotic systems wa effective.
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