ACTIVE CONTROL OF NONLINEAR NOISE PROCESSES IN A LINEAR DUCT

This paper investigates two scenarios in active noise control (ANC) th at lead to performance degradation with conventional linear control te chniques. The first scenario addresses the noise itself. The low-frequ ency noise, traveling as plane waves in a duct, is usually assumed to be broadband random or periodic tonal noise. Linear techniques applied to actively control this noise have been shown to be successful. Howe ver, in many practical applications, the noise often arises from dynam ical systems, which cause the noise to be nonlinear and deterministic or stochastic, colored, and non-Gaussian, Linear techniques cannot ful ly exploit the coherence in the noise and, therefore, perform suboptim ally. The other scenario is that the actuator in an ANC system has bee d shown to be nonminimum phase. One of the tasks of the controller, in ANC systems, is to model the inverse of the actuator. Obviously, a li near controller is not able to perform that task. To combat the proble ms, as mentioned above, a nonlinear controller has been implemented in the ANC system. It is shown in this paper that the nonlinear controll er consists of two parts: a linear system identification part and a no nlinear prediction part. The standard filtered-x algorithms cannot be used with a nonlinear controller, and therefore, the control scheme wa s reconfigured. Computer simulations have been carried out and confirm the theoretical derivations for the combined nonlinear and linear con troller.