Model-Free Control of a Nonlinear ANC System with a SPSA-Based Neural Network Controller

  • Yali Zhou
  • Qizhi Zhang
  • Xiaodong Li
  • Woonseng Gan
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3972)


In this paper, a feedforward active noise control (ANC) system using a mode-free neural network (MFNN) controller based on simultaneous perturbation stochastic approximation (SPSA) algorithm is considered. The SPSA-based MFNN control algorithm employed in the ANC system is first derived. Following this, computer simulations are carried out to verify that the SPSA-based MFNN control algorithm is effective for a nonlinear ANC system. Simulation results show that the proposed scheme is able to significantly reduce disturbances without the need to model the secondary-path and has better tracking ability under variable secondary-path. This observation implies that the SPSA-based MFNN controller frees the ANC system from the modeling of the secondary-path.


Hide Layer Neuron Neural Network Controller Active Noise Control Simultaneous Perturbation Total Sampling Number 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Yali Zhou
    • 1
  • Qizhi Zhang
    • 1
  • Xiaodong Li
    • 2
  • Woonseng Gan
    • 3
  1. 1.Department of Computer Science and AutomationBeijing Institute of MachineryBeijingChina
  2. 2.Institute of AcousticsAcademia SinicaChina
  3. 3.School of EEENanyang Technological UniversitySingapore

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