Recent implementations of multiple-input multiple-output adaptive controllers for reduction of broadband noise and vibrations provide considerably improved performance over traditional adaptive algorithms. The most significant performance improvements are in terms of speed of convergence, the udamount of reduction, and stability of the algorithm. Nevertheless, if the error in the model of the relevant transfer functions becomes too large then the system may become unstable or lose performance. On-line adaptation of the model is possible in principle but, for rapid changes in the model, necessitates uda large amount of additional noise to be injected in the system. It has been known for decades that a combination of high-authority control (HAC) and low-authority control (LAC) could lead to improvements with respect to parametric uncertainties and unmodeled dynamics. In this paper a full digital implementation of such a control system is presented in which the HAC (adaptive MIMO control) is implemented on a CPU and in which the LAC (decentralized control) is implemented on a high-speed Field Programmable Gate Array. Experimental results are given in which it is demonstrated that the HAC/LAC combination leads to performance advantages in terms of stabilization under parametric uncertainties and reduction of the error signal.
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