In this dissertation, adaptive predictive feedback control is used to suppress plate vibrations. The adaptive predictive controller consists of an on-lineidentification technique coupled with a control scheme. Various system identification techniques are investigated and implemented including batch least squares, projection algorithm, and recursive least squares. The control algorithms used include Generalized Predictive Control and Deadbeat Predictive Control. This dissertation combines system identification and control to regulate broadband disturbances inmodally-densestructures. As it is assumed that the system to be regulated is unknown or time varying, the control schemes presented in this work have the ability to identify and regulate a plant with only an initial estimate of the system order. In addition, theoretical development and experimental results presented in this work confirm the fact that an adaptive controller operating in the presence of disturbances will automatically incorporate an internal noise model of the disturbance perturbing the plant if the system model order is chosen sufficiently large. It is also shown that the adaptive controller has the ability to track changes in the disturbance spectrum as well as track a time varying plant under certain conditions. This work presents a broadbandmulti-inputmulti-outputcontrol scheme which utilizes both the DSP processor and the PC processor in order to handle the computational demand of broadband regulation of amodally-denseplant. Also, the system identification technique and the control algorithm may be combined to produce a direct adaptive control scheme which estimates the control parameters directly from input and output data. Experimental results for various control techniques are presented using an acoustic plant, a rectangular plate with clamped boundary conditions, and a time varying plate.